US20050149259A1 - System and method for updating, enhancing, or refining a geographic database using feedback - Google Patents

System and method for updating, enhancing, or refining a geographic database using feedback Download PDF

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Publication number
US20050149259A1
US20050149259A1 US11/044,139 US4413905A US2005149259A1 US 20050149259 A1 US20050149259 A1 US 20050149259A1 US 4413905 A US4413905 A US 4413905A US 2005149259 A1 US2005149259 A1 US 2005149259A1
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United States
Prior art keywords
data
database
geographic
vehicles
collection equipment
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US11/044,139
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Kevin Cherveny
Aaron Crane
Lawrence Kaplan
John Jasper
Russell Shields
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Here Global BV
Original Assignee
Kevin Cherveny
Aaron Crane
Kaplan Lawrence M.
John Jasper
Russell Shields
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Priority to US11/044,139 priority Critical patent/US20050149259A1/en
Publication of US20050149259A1 publication Critical patent/US20050149259A1/en
Assigned to NAVTEQ B.V. reassignment NAVTEQ B.V. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: NAVTEQ NORTH AMERICA, LLC
Assigned to HERE GLOBAL B.V. reassignment HERE GLOBAL B.V. CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: NAVTEQ B.V.
Abandoned legal-status Critical Current

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/38Electronic maps specially adapted for navigation; Updating thereof
    • G01C21/3804Creation or updating of map data
    • G01C21/3833Creation or updating of map data characterised by the source of data
    • G01C21/3841Data obtained from two or more sources, e.g. probe vehicles
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/38Electronic maps specially adapted for navigation; Updating thereof
    • G01C21/3804Creation or updating of map data
    • G01C21/3807Creation or updating of map data characterised by the type of data
    • G01C21/3811Point data, e.g. Point of Interest [POI]
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/38Electronic maps specially adapted for navigation; Updating thereof
    • G01C21/3804Creation or updating of map data
    • G01C21/3807Creation or updating of map data characterised by the type of data
    • G01C21/3815Road data
    • G01C21/3819Road shape data, e.g. outline of a route
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/38Electronic maps specially adapted for navigation; Updating thereof
    • G01C21/3804Creation or updating of map data
    • G01C21/3807Creation or updating of map data characterised by the type of data
    • G01C21/3815Road data
    • G01C21/3822Road feature data, e.g. slope data
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/38Electronic maps specially adapted for navigation; Updating thereof
    • G01C21/3804Creation or updating of map data
    • G01C21/3833Creation or updating of map data characterised by the source of data
    • G01C21/3848Data obtained from both position sensors and additional sensors
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968Systems involving transmission of navigation instructions to the vehicle
    • G08G1/0969Systems involving transmission of navigation instructions to the vehicle having a display in the form of a map

Definitions

  • the present invention relates to a system and method for updating and enhancing a geographic database, and more particularly, the present invention relates to a system and method for updating and enhancing a geographic database based on feedback from field use of the geographic data.
  • the geographic data set includes information about the positions of roads and intersections in or related to a specific geographical area, and may also include information about one-way streets, traffic signals, stop signs, turn restrictions, street addresses, alternative routes, hotels, restaurants, museums, stadiums, offices, automobile dealerships, auto repair shops, etc.
  • the optional positioning system may employ any of several well-known technologies to determine or approximate one's physical geographic location.
  • the positioning system may employ a GPS-type system (global positioning system), a “dead-reckoning”-type system, or combinations of these, or other systems, all of which are known in the art.
  • the navigation application portion of the navigation system is a software program that uses the detailed geographic data set and the positioning system (when employed).
  • the navigation application program may provide the user with a graphical display (e.g. a “map”) of a specific location in the geographical area.
  • the navigation application may provide the user with data indicating his own location and specific directions to locations in the geographical area from wherever he is located.
  • Computer-based navigation systems may exist as a single unit that may be installed in a vehicle, or even carried by persons.
  • the navigation application and geographic data set may be provided as software products that are sold or licensed to users to load in personal computers.
  • Systems operating on personal computers may be stand-alone or connected by a communication link to a central or regional system.
  • Organizations, such as trucking companies, package delivery services, and emergency dispatch units may employ navigation systems to track fleets and ensure the quickest routes to destinations.
  • the navigation systems may also be made available on-line from a central system to multiple users on an “as needed” basis, or from on-line services such as services available on the Internet and private dial-up services.
  • Directions can include detours around construction delays.
  • Directions may be provided to street addresses, intersections, or to entities by name, such as to restaurants, hotels and service stations.
  • a publisher of geographic data may obtain the information that becomes part of geographic data sets from field personnel sent to the locations to record the information or from aerial photographs or municipal records or other sources. Geographic information, however, becomes outdated as new roads are built, existing roads are changed, traffic signals are installed, businesses change their hours of operation, new businesses open, existing businesses close, etc. When changes occur, data in the geographic data set becomes inaccurate and its utility is thereby lessened.
  • Information identifying changes are collected using the same techniques as described above. Once the information regarding changes is collected, it is incorporated into a master geographic data set. The publisher of geographic databases then periodically distributes updated geographic data reflecting the changes to end-user. However, the process of acquiring information regarding changes is time-consuming and expensive. Moreover, existing methods of acquiring updated data may become increasingly expensive as geographic databases become more detailed and extensive in scope.
  • a system and method are desired that would provide for a more efficient acquisition of information reflecting changes and corrections in geographic areas to navigation systems. Further, a system and method are desired that allow the accuracy of the data in a geographic database to be enhanced.
  • a first aspect of the present invention is directed to a system for updating, enhancing and/or refining a geographic database.
  • a geographic database includes data representing physical features in the geographic region, and, optionally, attributes of such features.
  • the system includes a plurality of data collecting sensors. Each of the data collecting sensors is installed in a separate one of a plurality of vehicles each of which is capable of traveling on roads in a geographic region. Each of the data collecting sensors provides outputs indicative of one or more features in the geographic region as the vehicle in which it is installed travels on the roads in the geographic region.
  • a computer program executes a feedback process on the geographic database using the outputs of the data collecting sensors.
  • a first part of the feedback program compares the outputs of the data collecting sensors to the data identifying the physical features and provides results representative of the comparisons.
  • a second part of the feedback program is responsive to the results from the first part and determines the significance of the comparisons.
  • a third part of the feedback program modifies the data in the geographic database based upon the significance determined by the second part of the program.
  • the data in the geographic database representing physical features in the geographic region are updated, enhanced, or refined based upon the significance determined by the feedback program.
  • the data which has been updated, enhanced, or refined is used to provide updated, enhanced, or refined data in end-user vehicles, some of which may include the vehicles in which data collecting sensors have been installed.
  • sensors in end-users' vehicles are calibrated to high levels of accuracy using the data which has been updated, enhanced or refined using a feedback process.
  • an out-of-calibration sensor in an end-user's vehicle is detected and re-calibrated using the data which has been updated, enhanced or refined using a feedback process.
  • levels of confidence of accuracy are assigned to data in the geographic database representing physical features in the geographic region, thereby enabling the data to be used for purposes requiring high levels of confidence.
  • the data collecting sensors may be used to sense the geographic position of the vehicle (derived from GPS, dead-reckoning, or other positioning systems), vehicle speed, road gradient, lane width (derived from radar, and other similar systems), signage (derived from cameras), road direction (derived from an on-board compass or other heading-determining means), and various other physical features.
  • the data in the geographic database may represent roads (or road segments) and their positions, as well as other attributes relating to roads.
  • the present invention is directed to a method of updating a geographic database by the steps of storing road data that includes a plurality of map positions in the geographic database.
  • a plurality of actual positions traveled is determined by a vehicle by repeatedly sensing actual position while the vehicle moves. At least a portion of the plurality of actual positions is matched with a plurality of map positions in the geographic database.
  • a position difference is calculated between each actual position in the plurality of actual positions and the plurality of map positions.
  • Each actual position for which the position difference exceeds a predetermined tolerance level is stored as a plurality of unmatched positions.
  • FIG. 1 is a diagram illustrating a system according to a first embodiment.
  • FIGS. 2A-2C are diagrams illustrating alternative embodiments of the data collection vehicles shown in FIG. 1 .
  • FIG. 3 is a flow chart illustrating a method for processing sensor data using the system of FIG. 1 .
  • FIGS. 4A-4E illustrate the application of the method of using the system of Figure to update a geographic data set.
  • FIGS. 5A-5L illustrates the method of using the system in FIG. 1 as applied to a sample portion of a geographic data set.
  • FIGS. 6A-6E illustrate an enhancement to the method of using the system of FIG. 1 .
  • FIGS. 7A-7D illustrate another enhancement to the method of using the system of FIG. 1 .
  • FIGS. 8A-8G illustrate a method of using the system in FIG. 1 as applied to non-positional features of a geographical area.
  • FIG. 9 is a diagram illustrating a data entity record in the geographic database including an indication of the confidence level.
  • FIG. 10 is a flow chart indicating the steps for performing another aspect of a feedback process using data collection vehicles.
  • FIG. 11 is a flow chart indicating the steps for re-calibrating an out-of-calibration sensor in a vehicle.
  • a system 9 for updating and enhancing a geographic database includes a central geographic data manager 10 .
  • the central geographic data manager 10 includes a central geographic database 20 .
  • the geographic database 20 includes data that represents physical features in a geographical area 47 .
  • the central geographic database 20 may include data descriptive of position data in terms of points 44 on the map and of links, or segments of roads 45 .
  • the central geographic database 20 may also include data representing road gradients, road widths, lane widths and shoulder widths, and data that is descriptive of stationary objects such as stop signs, buildings, bridge supports, etc.
  • the central geographic database 20 may include non-positional features such as speed limits, the direction of travel allowed on the roads and the directions of allowed turns.
  • the central geographic database 20 may include other types of information as well, for example, types of restaurants, museum hours, etc.
  • Each of the data collection vehicles 50 includes a data collection system 39 .
  • Each data collection system 39 includes one or more sensors capable of collecting data representing physical features about the environment of the vehicle or the vehicle's physical position as the vehicle is moving or while it is stopped. As each of the data collection vehicles 50 moves on the roads (or is stopped) in the geographic area 47 , the sensors in the data collection system of the vehicle sense physical features.
  • These data collection vehicles 50 may include vehicles in which in-vehicle navigation systems are installed, or vehicles which have only data collection system equipment without on-board navigation systems, or may include both types of vehicles.
  • the plurality of vehicles 50 may include vehicles which are owned (or leased) by private party end-users as well as fleet vehicles. Some of the data collection vehicles 50 include local copies of a geographic database 56 (shown in FIGS. 2A and 2B ) which may be a copy or version of a portion of the central geographic database 20 . The data collection vehicles 50 communicate data derived from their data collection systems to the central geographic data manager 10 using suitable communications links 49 .
  • FIGS. 2A-2C illustrate alternative embodiments of the data collection vehicles 50 .
  • FIG. 2A illustrates an embodiment of a data collection vehicle 50 ( 1 ) which processes sensor data 54 into filtered sensor data 55 F for communication to the central geographic data manager 10 .
  • the data collection vehicle 50 ( 1 ) includes a data collection system 39 ( 1 ) which includes a vehicle computing system 52 , a sensor data processor 53 , a communications manager 58 , a local map database 56 , and one or more sensors 60 .
  • the data collection vehicle 50 ( 1 ) may also include an update manager 59 which is not necessarily part of the data collection system 39 ( 1 ).
  • parts of the data collection system 39 ( 1 ) may be shared with an in-vehicle navigation system.
  • the sensors 60 , the vehicle computing system 52 and the map database 56 may be components of an in-vehicle navigation system and may be used by the vehicle driver for such purposes.
  • the outputs of the one or more sensor devices 60 provide sensor device data 54 .
  • the sensor devices 60 may include a GPS (Global Positioning System), an imaging system (e.g. radar, cameras, etc.), a gyroscope, a compass, an odometer and other sensors.
  • the sensor devices 60 output data 54 as the vehicle 50 ( 1 ) moves around the geographic region 47 or while it is stopped.
  • the output 54 from the sensor devices 60 is provided to the vehicle computing system 52 of the data collection system 39 ( 1 ).
  • the sensor data processor 53 uses the data 54 output from the sensors 60 to the vehicle computing system 52 , compares the sensor device data 54 with data in the local map database 56 .
  • the sensor data processor 53 may be implemented as a computer program executed on the CPU of the vehicle computing system 52 or may executed on a separate processor.
  • the sensor data processor 53 determine variances between the sensor device data 54 and the data in the local map database 56 based on comparisons between the sensor device data 54 and corresponding elements in the map database 56 .
  • the variances depend upon the type of data being compared. For example, if the output of a position sensor is being compared to a corresponding position in the local map database 56 , the variance may be a distance representing the difference between the two values. The variance may also include the relative direction of the difference.
  • the variance is compared to threshold levels above or below which the sensor output may be considered unmatched to a map database element. The threshold levels may be based on factors such as the tolerances of the sensors.
  • the sensor data processor 53 processes the sensor data 54 into filtered sensor data 55 F.
  • the filtered sensor data may include only the variances that exceed a certain predefined threshold.
  • the filtered sensor data may be temporarily stored on a data storage device (not shown) in the vehicle.
  • the communications manager 58 is used to transmit the filtered sensor data 55 F to the central geographic data manager 10 of FIG. 1 .
  • the communications manager 58 may utilize any appropriate means for data transmission, including wireless ( 49 in FIG. 1 ), cellular, modem uploads, e-mail, and so on.
  • Data may be communicated at any time. For example, data may be communicated as it is obtained.
  • the data 55 F may be stored and communicated at a fixed time, such as daily or weekly at a specified time.
  • the data 55 F may also be communicated to an intermediate data collection system and then transferred to the manager 10 .
  • data is collected in the vehicle on a disk and uploaded by modem or sent by mail to the manager 10 .
  • data may be selected from the filtered sensor data 55 F for communication to the central geographic data manager 10 .
  • data that indicates variances beyond a certain level may be selected for communication to the central geographic data manager 10 .
  • all of the filtered sensor data 55 F, including variances that indicate a perfect match between sensor device data and data in the local database 56 may be communicated to the central geographic data manager 10 .
  • the central geographic data manager 10 may determine the reliability of the geographic database 20 by confirming the accuracy of the existing data in the central geographic database 20 .
  • FIG. 2B illustrates another embodiment of a data collection vehicle 50 ( 2 ).
  • the embodiment 50 ( 2 ) of FIG. 2B collects raw sensor data and communicates it to the central geographic data manager 10 .
  • the data collection vehicle 50 ( 2 ) includes a data collection system 39 ( 2 ) which includes a sensor driver 51 , a vehicle computing system 52 , a communications manager 58 , a local map database 56 , and one or more sensors 60 .
  • the data collection vehicle 50 ( 2 ) may also include an update manager 59 which is not necessarily part of the data collection system 39 ( 2 ).
  • an in-vehicle navigation system may be used as part of the data collection system.
  • the outputs of the one or more sensor devices 60 provide sensor device data 54 .
  • the sensor devices 60 collect data as the vehicle 50 ( 2 ) moves around or stops in the geographic region 47 .
  • a sensor driver 51 which may be a software program, processes the sensor device data 54 into raw sensor data 55 R.
  • the functions performed by the sensor driver 51 may include, for example, converting essentially analog outputs of sensors 60 into appropriate digital data, scaling the data, time stamping the data, compressing the data, identifying the types of sensors that generate the data, organizing the raw data for storage purposes, and so on.
  • the raw sensor data 55 R may be temporarily stored in a data storage device (not shown) in the vehicle 50 ( 2 ).
  • the raw sensor data 55 R is communicated to the central data manager 10 .
  • the communications manager 58 which may be similar to the communications manager in the embodiment of FIG. 2A , may be used for this purpose.
  • FIG. 2C Another embodiment of a data collection vehicle 50 ( 3 ) is illustrated in FIG. 2C .
  • the data collection vehicle 50 ( 3 ) includes a data collection system 39 ( 3 ) including a sensor driver 51 , a temporary storage 63 , and sensors 60 . These components perform similar functions as the like numbered components in FIGS. 2A and 2B .
  • the data collection vehicle 50 ( 3 ) in FIG. 2C does not include an in-vehicle navigation system.
  • the data collection vehicle 50 ( 3 ) in FIG. 2C stores raw sensor data 55 R in the temporary storage 63 .
  • a user then transfers the data to a floppy disk or to a removable hard disk drive and physically sends the data to the central data manager 10 .
  • the data collection system 39 ( 3 ) in the vehicle may include a communications manager that provides functions, similar to those described above, to transfer the data to the central data manager.
  • the central geographic data manager 10 illustrated in FIG. 1 includes hardware and software components for receiving data 55 R and 55 F from the data collection vehicles 50 and for processing the data to generate updates, refinements, and/or enhancements to the central geographic database 20 .
  • the central geographic data manager 10 may also assign levels of reliability to data in the database 20 , as described below.
  • the hardware and software components need not be located in one location or operate on one computer. Different components may be located in different places with known communications techniques used to connect them.
  • the central geographic data manager 10 receives raw sensor data 55 R from the data collection vehicles 50 ( 2 ), 50 ( 3 ) that communicate non-filtered data at a raw data collector 28 .
  • the central geographic data manager 10 receives filtered data 55 F from the data collection vehicles 50 ( 1 ) at a filtered data collector 12 .
  • the filtered sensor data collector 12 and the raw sensor data collector 28 are interfaces to the communication links 49 and may be implemented by any suitable technology for receiving data.
  • Each collector handles the data received from its corresponding plurality of data collection vehicles 50 and forwards the data to the appropriate processes in the central geographic data manager 10 .
  • the filtered data collector 12 stores and organizes the filtered sensor data 55 F in a central filtered sensor database 14 .
  • the raw data collector 28 organizes the raw sensor data from the plurality of vehicles in a central raw data database 30 .
  • This collection of data is analyzed for variances by a central sensor data processor 32 .
  • the central sensor data processor is a computer program, similar to the local sensor data processor 53 of FIG. 2A , capable of calculating variances based on comparisons of the raw data with the geographic data in the central database 20 .
  • the central sensor data processor 32 stores variances as filtered sensor data in the filtered sensor database 14 .
  • the collection of data in the filtered sensor database 14 is analyzed by a statistical data analyzer 16 .
  • the statistical data analyzer 16 includes a computer program that applies statistical analysis techniques based on further comparisons with the geographic data in the central geographic database 20 .
  • the statistical analysis techniques may take into account thousands or millions of sensor readings to derive results with a high level of reliability and confidence.
  • the statistical data analyzer 16 determines updates to the central geographic database 20 based on whether the central filtered sensor data set 14 reflects statistically significant variances. (Various kinds of statistical techniques for analyzing data using large numbers of readings are known and may be used.)
  • the statistical analysis techniques can also take into account historical information. For example, if a highly traveled road segment that was sensed thousands of times a day for years suddenly had no reported sensor readings, it would be an indication that the road was no longer open. An appropriate update to the central database, or at least an indication to verify a possible change in the database record, would be processed accordingly.
  • the statistical data analyzer 16 may determine confidence levels for data elements in the central geographic database 20 .
  • confidence levels may be stored for data elements in the central geographic database 20 .
  • the confidence level is stored as an attribute of a data entity.
  • the confidence level may be expressed as a magnitude that is indicative of the certainty to which the data entity in the central geographic database 20 matches the actual physical feature in the geographic region.
  • the confidence level of an item of data may be increased or decreased according to the frequency and freshness with which the feature is sensed by the data collection vehicles.
  • a data entity D represents a road segment record having positional information attributes.
  • the road segment attributes include the latitude and longitude of the left and right nodes (L-LAT, L-LON, R-LAT, R-LON) of the road segment data entity D.
  • a confidence level attribute CL includes a value (e.g. 1-10) which expresses the confidence that the positional data is accurate. For example, a confidence level of “10” may indicate that, based upon the statistical analysis, there is a greater than 99% certainty that the positional data (L-LAT, L-LON, R-LAT, R-LON) is within 1 cm.
  • a confidence level of “8” may mean that, based upon statistical analysis, there is a 75% level of certainty that the positional data is within 1 meter, or that there is a 99% level of certainty that the positional data is within 15 meters.
  • the statistical data analyzer 16 also provides for any layout changes that may be necessary when the database is modified. Such layout changes may involve creating new links, modifying the geometry of existing links, and designating features known about the new and existing links.
  • the statistical data analyzer 16 provides a message 18 to initiate an update process 22 for the central geographic database 20 .
  • the update process 22 collects the individual changes to the central geographic database 20 from the statistical data analyzer 16 and stores the changes in a queue of update transactions for a distribution process 24 .
  • the steps performed in the manager 10 including the determination of variances, the collection of data from the vehicles, the analysis of statistical significance, and the updating of the central database, are performed on an ongoing and continuous basis. However, in alternative embodiments, it may be preferred to perform some of these tasks intermittently or periodically.
  • data reflecting the updating process applied to the central database is released to the end-users.
  • the release and/or distribution of data may be performed by an update distributor 26 Distribution may be accomplished electronically using the wireless communication links 49 .
  • the update distributor 26 may communicate updated information from the central data manager 10 directly back to the local communications managers 58 in the individual data collection vehicles 50 .
  • Other alternative means of distribution may be used including distribution of hard media, such as CD-ROM discs and PCMCIA cards, downloading to personal computers, and so on.
  • the end-users may include persons who use local versions 56 of geographic databases in their vehicles.
  • the end-users may also include various others including, for example, personal computer users 46 and networks 48 , such as on-line services, services that use the Internet and organizations that incorporate all or parts of the geographic database in applications such as emergency dispatch centers, truck fleet tracking and package delivery fleet tracking.
  • the releases may occur on a continuous basis, or may occur from time to time, or on a regular or irregular basis, a staggered basis, and so on.
  • the release of data reflecting the updating process can be made in any of several different formats.
  • the updated data may be released as a series of update transactions which are applied to each user's local copy of the geographic database, as needed.
  • versions of the entire database reflecting the updated data may be provided.
  • FIG. 3 A flow chart illustrating the process of the system 9 of FIG. 1 is shown in FIG. 3 .
  • the computing devices 32 in FIG. 1, 53 in FIG. 2A ) use output from sensors ( 60 in FIGS. 2A-2C ) to relate (Step S 2 in FIG. 3 ) to a geographic database ( 20 in FIG. 1, 56 in FIG. 2A ) and perform some action based on the interpretation of the sensor data and database content.
  • Variances, including zero-variances, between the perceived reality derived from the sensor data and the content of the map database can be stored as filtered sensor data (Steps D 1 , S 3 , S 4 in FIG. 3 ; 14 in FIG. 1 ; 55 F in FIG.
  • Steps D 2 , S 5 , S 6 in FIG. 3 After the update process has been applied to the central database ( 22 in FIG. 1 ), database updates are communicated to end-users of the database.
  • the raw data derived from the sensor devices may be stored in some medium and communicated to a separate system for comparison against the map database outside the scope of the vehicle navigation system.
  • vehicle sensors in the various end-users' vehicles are fine-tuned for very high levels of accuracy by a feedback process.
  • the feedback process uses the collection of sensor data from a large number of vehicles (using the process described above, for example) to provide highly accurate geographic data in the central database which in turn is distributed to individual end-user vehicles and used to adjust and calibrate the sensors in each of the individual end-user vehicles to conform to the known-to-be-highly accurate geographic data.
  • the continued use of data collection vehicles and the redistribution of known-to-be-highly accurate data to the individual end-users' vehicles for calibrating of the sensors in the vehicles forms a feedback loop which pumps up the accuracy of the sensors in each of the individual vehicles.
  • the accuracy that can be obtained in this manner can exceed the accuracy that could be obtained by any one vehicle or any one sensor measurement using conventional techniques.
  • a diagram illustrating this process is shown in FIG. 10 .
  • the levels of accuracy that can be achieved can be as high as 1 cm, or better. Given these levels of accuracy, it is possible to use a geographic database for vehicle control and safety systems. With high levels of accuracy in both the geographic database and the vehicle positioning sensors, the safety systems can automatically determine if the vehicle is deviating from the roadway, veering out of its lane, and so on. In conjunction with the high levels of accuracy, the safety systems or vehicle control systems use the confidence level attributes, described above, to confirm that the data is not only accurate but also reliable.
  • out-of-alignment sensors in a vehicle can be detected and corrected using a feedback process.
  • a feedback process to develop highly accurate data as described above, once geographic data is known-to-be highly accurate (i.e. its confidence level is high) as a result of statistical analysis of a large number of data records collected from a large number of vehicles over a significant period of time, if one vehicle using the data reports variances, then it can be determined that the sensors in the variance-reporting vehicle are likely out of calibration. Then, using only the variance data reported from the one vehicle and the known-to-be-highly accurate data, the sensors in the variance-reporting vehicle are re-calibrated to the same level of accuracy as all the other vehicles.
  • FIG. 11 A diagram illustrating this process is shown in FIG. 11 .
  • the data collection systems in each of the data collection vehicles provide data that identifies of the types of sensors being used to collect the data. Then, when variances from a vehicle are collected, the type of sensors measuring the variances are taken into account. For example, if a type of sensor reports variances that suggest it should be re-calibrated, it is first compared to similar kinds of sensors. This permits a better evaluation of the extent to which the particular type of sensor can be calibrated based on the accuracy which is achievable in like-equipped vehicles.
  • FIGS. 4A-4C Processing of a modification to an existing database based upon the collection of data from a single vehicle is illustrated in connection with FIGS. 4A-4C .
  • This example refers to positional information (latitude, longitude, and altitude) and illustrates attempts to match positional sensor data to the elements in a geographic database (e.g. the central geographic database 20 in FIG. 1 or the map database 56 in FIGS. 2A and 2B ). Similar steps would be used for other types of data.
  • FIG. 4A graphically depicts an area that may be represented in a geographic database.
  • FIG. 4A illustrates map positions 80 ( 1 ), 80 ( 2 ) . . . 80 ( n ) and map links 100 ( 1 ), 100 ( 2 ), . . . 100 ( n ) representing road segments, connecting the map positions 80 .
  • FIG. 4B a set of actual positions 90 ( 1 ) . . . 90 ( n ) established by the sensor devices on the vehicle are denoted as arrows with time sequence identifiers T 1 -T 14 .
  • the map matching process uses the vehicle's bearing, proximity to that link 100 ( 1 ), and various link features to place the vehicle on a matched link 100 ( 1 ).
  • the sensor data points are compared to map positions 80 and the matched link 100 ( 1 ) by determining the shortest distance from the sensor data point to the matched link 100 ( 1 ). If the resulting distance exceeds specified tolerance levels, or if sensor data conflicts with features of the matched link 100 ( 1 ), a record of this variance is created along with relevant sensor data.
  • the record, illustrated in FIG. 4C as a new link 110 ( 1 ), is then stored in the filtered sensor database ( 55 F of FIG. 2A or 14 of FIG. 1 ).
  • a link is traversed with all sensor samples within the tolerance level, a record is created in the filtered sensor database, certifying the accuracy of the matched link and its features and identifying the sensor device or devices used.
  • FIG. 4D illustrates the collection of data over time with numerous collections of sensor data, which would result in a database update as indicated in FIG. 4E .
  • the filtered sensor data includes information regarding potential new links and may be used to determine whether the geographic database is to be updated. During the update of the geographic database, features relative to the actual position may be determined from the sensor data. Data relating to such features may be included as filtered sensor data so that the features may be included in the update of the geographic database. For example, if only the data collection shown in FIGS. 4B and 4C were available, the new link 100 ( m ) (also labeled L 9 ) can be traversed from left to right (in the direction the collector vehicle traveled) based on the single collection of sensor data.
  • the restriction of allowing travel in the single direction may be added as a feature of the new link 100 ( m ) until sensor data is received to indicate that travel may be allowed in the other direction.
  • the filtered sensor data may provide information regarding other features that may be used during the update of the geographic database.
  • the addition of the new link 100 ( m ) forms two new links labeled 100 ( 1 )( 2 ) (also L 3 b ) and 100 ( 1 )( 1 ) (also L 3 a ) where previously only 100 ( 1 ) (labeled L 3 ) existed as illustrated in FIG. 4C .
  • the update of the geographic database may include a feature allowing vehicles to traverse from link L 3 a ) to L 9 (labeled 100 ( m )), but not from L 3 b to L 9 .
  • the feature may be revised if data supporting travel from L 3 b to L 9 is received.
  • FIGS. 5A-5L illustrate time sequence examples of using sensor data to update the geographic database.
  • FIGS. 5A-5F illustrate a method of using sensor data to update the geographic database for a single sample of sensor data.
  • FIGS. 5G-5L illustrate a method of using sensor data to update the geographic database after a second sample of data has been collected on the same link.
  • FIG. 5A contains a sample road network 120 and an example of a graphical representation 122 of the geographic database 20 (shown in FIG. 1 ) at its time of release.
  • the geographic database 20 contains no link for Market St. between 1st St. and 2nd St.
  • FIG. 5B illustrates the tracking of a vehicle with sensor devices generating actual positions 130 , in relation to both the road network 120 and the database 122 .
  • the unfilled triangles 130 U in FIG. 5C represent positions which were able to match to links in the database as denoted by the arrows.
  • the filled triangles 130 F in FIG. 5C represent positions which would exceed map matching tolerance levels and therefore induce the map matching process to store these positions as unmatched in the filtered sensor database.
  • the unmatched positions may be stored as an ordered set of points 136 as shown in FIG. 5D .
  • the contents of the entry in the filtered sensor database would be the previous link L 8 successfully matched, the latitude/longitude of each unmatched position, and the next link L 11 successfully matched.
  • the data analyzer processor 16 (in FIGS. 1 and 2 A) then derives a new link using the method illustrated in FIGS. 5E and 5F .
  • a new link may be derived by determining the shortest distance 180 from the first unmatched position 175 to the previous link L 8 , and splitting the link at that nearest point 190 on the link L 8 creating two new links L 8 A and L 8 B out of link L 8 .
  • the processor 16 determines the shortest distance 182 from the last unmatched position 176 to the next link L 11 matched, and splitting the link at that nearest point 192 on link L 11 , creating two new links L 11 A and L 11 B out of link L 11 .
  • the new link 100 ( q ) is constructed by joining all unmatched positions and terminating at the intersection of links L 11 A and L 11 B as shown in FIG. 5E .
  • the filtered position database is then updated to associate all unmatched positions with the new link 100 ( q ).
  • the resulting database content is illustrated in FIG. 5F .
  • features may be added to this new link which may include the direction of travel (from left to right), the average speed, and the fact that turns can legally be made from L 8 B to 100 ( q ), and from 100 ( q ) to L 11 A.
  • FIGS. 5G-5L illustrate a process of using sensor data to update the geographic database after a second sample of data has been collected.
  • FIG. 5G contains the same example of the road network 120 , and the depiction of the map database 122 as updated in FIGS. 5A-5F .
  • FIG. 5H contains a new set of sensor data points 202 for a vehicle traveling in the opposite direction.
  • FIG. 5I highlights the positions 202 U which exceeded map matching tolerance levels, but may have been determined to match the new link 100 ( q ).
  • the map matching process will store these positions 202 U with the filtered sensor data as an ordered set of points 206 as shown in FIG. 5J .
  • the filtered sensor data may include the previous link matched L 11 A, the ordered set of points 206 , the next link matched L 8 B, and the assumed match 100 ( q ).
  • the sensor data processor would then update the geographic database using a process described below with reference to FIGS. 5J, 5K and 5 L.
  • all ordered sets of points from the filtered sensor data which have been associated with the new link 100 ( q ), which in this example is the ordered sets of points 206 are identified.
  • all positions for the same direction of travel as the positions being processed are identified.
  • the positions represented by the ordered set of points 206 are for the direction opposite the direction of the new link 100 ( q ).
  • the ordered set of points 206 are then averaged using a sequential averaging or curve fitting technique to create a single sequence of positions.
  • intersection point 214 with the nearest link to the beginning position of the ordered set 206 is identified.
  • intersection point 216 with the nearest link to the ending position in the ordered set is also identified.
  • All points having a direction of travel opposite the direction of the ordered set of points 136 are then averaged using the sequential averaging or curve-fitting technique to create an opposite direction ordered set of points 136 A.
  • no points were collected in the second sample traveling in the same direction as the new link 100 ( q ). Therefore, the new link 100 ( q ), or points in the new link 100 ( q ), may be used for the opposite direction ordered set of points 136 A.
  • the distance between the sets of points in opposite directions 136 , 136 A is averaged by calculating half the distance from each point starting with the ordered set of points represented by the most points to yield a set of average points 136 M in FIG. 5J .
  • the average points 136 M are then designated as the new link 100 ( q )(new) in FIG. 5K .
  • the new link 100 ( q )(new) could be modified by moving it to correspond with the average points 136 C.
  • the link features may now be updated to identify the direction of travel as being both directions.
  • the average speed may also be updated. It may be assumed that turns can be legally made from L 11 B to 100 ( q )(new) and from 100 ( q )(new) to L 8 B.
  • the resulting database content is illustrated in FIG. 5L .
  • FIGS. 6A-6E The collection of data over time illustrated in FIG. 4D may be subjected to a process of trend analysis as illustrated in FIGS. 6A-6E .
  • the addition of link L 5 in FIG. 6C may be used as an update to the map database in FIG. 6A , based on the sensor data provided from the samples in FIG. 6B .
  • FIG. 6D illustrates that the path of the vehicle was actually a maneuver through a filling station.
  • FIG. 6E illustrates a trend analysis, with the dense lines 250 representing a high instance of sensor data positions and the dotted line 260 representing the single traversal of the vehicle whose path is defined in FIG. 6B . Applying statistical analysis of the entire sensor collection would result in the link L 5 being classified as statistically insignificant and not being added to the geographic map database 20 .
  • FIGS. 7A-7D further illustrate how geographic updates can be implemented using sensor data from a feedback loop with trend analysis.
  • a graphical illustration of a portion of the map database 20 in its original state is shown in FIG. 7A .
  • FIG. 7B represents the original database content with the heavier arcs 270 representing the average paths determined from sensor data. The two distinct arcs may be dependent upon bearing and statistical normalization.
  • a new arc 290 is generated at the geometrical center 292 of the tracking arcs T 1 and T 2 .
  • the original link L orig is then updated to reflect the new geometry defined by the new arc 290 . Curve fitting and other standard techniques could be employed alternatively to determine positional changes.
  • FIGS. 8 A- 8 B illustrate vehicles that are collecting road gradient information.
  • FIG. 8C illustrates a vehicle that is collecting information regarding road width, lane width, and shoulder width.
  • the information provided by the sensor devices is compared against the database and variance/confidence information is communicated through the loop described above with reference to FIGS. 3 and 4 A- 4 E.
  • This type of data is used by advanced vehicle safety systems, described above, because the more accurate and refined the database, the earlier and more intelligently system action can be taken. By reducing the margin of error for lane width, a system which detects erratic driving patterns can engage earlier and be more successful. A system which detects excessive speed during curve traversal can more accurately determine the maximum safe speed based on the bank of the curve.
  • Sensor devices which can identify objects in the path of a vehicle can be confused by permanent structures (for example signs, pillars, overpasses, poles, etc.). Maintaining an accurate model of these permanent structures can enable the sensor devices to filter out objects that may otherwise be interpreted as a potential hazard.
  • systems that identify road hazards can engage with the appropriate action more reliably.
  • Variances may be determined for database elements that represent objects when compared to images sensed from image sensors using a process similar to the process in FIG. 3 .
  • signs or other landmarks can be detected by cameras using image or shape detecting programs. The sign text on the signs is recorded and variances are stored, as described above.
  • the location of signs or other road side landmarks can be sensed, stored, and compared for variances.
  • These landmarks can include not only signs, but any detectable feature, including lamp posts, viaducts, etc.
  • the position of any detectable feature can be measured for variances and used for calibration, generating confidence levels, and so on. In this manner, the positions of many kinds of landmarks can be detected relatively inexpensively.
  • Knowledge of, and greater precision in, the position data for permanent structures also facilitates vehicle positioning useful in route guidance and other applications. For example, when a vehicle travels a significant distance along a straight road, the vehicle's position can become more uncertain as errors associated with the positioning sensors accumulate. Enhanced knowledge of the position of permanent structures along such straight roadways can serve as a landmarks to which the vehicle position can be corrected (or map-matched) when the landmark is sensed.
  • a vehicle includes sensors which may be similar to the sensors 60 in FIGS. 2A-2C .
  • the vehicle sensors have the capability to detect structures.
  • the structure-detecting sensor is a radar system.
  • the vehicle also includes an automatic vehicle control system and includes a local geographic database (similar to the database 56 of FIGS. 2A and 2B ).
  • the local geographic database has data that includes road side detectable features, such as sign posts, viaducts, lamp posts, and so on.
  • the local geographic database also includes data relating to roads. Using the detection of the road side structures, such as lamp posts, viaducts, and so on, the position of the vehicle in the geographic region can be determined by a map matching program. Map matching programs are known.
  • the position of the vehicle can be determined very accurately by matching the vehicles' position onto road segments in the geographic database.
  • the position of the vehicle can be fine-tuned by matching the position to the known positions of the detectable roadside landmarks.
  • an automatic safety system can be implemented that automatically avoids obstacles detected by the radar.
  • the sensor devices which for permanent structure analysis includes image sensors, determine static elements in the field of vision, compare the image footprint to the database and record the difference or confidence information as necessary.
  • FIGS. 8D, 8F and 8 G illustrate how image sensors identify signs according to sign location, dimension and content at 300 and sign post location at 302 .
  • FIGS. 8E and 8 G illustrate how image sensors may identify permanent structures such as guard rails 304 , bridge supports 306 and nearby structures 308 .
  • Sensor data may also be evaluated with respect to non-positional features that may be represented in the database to identify potential errors and establish confidence levels for these features.
  • features to evaluate include: direction of travel, divider location, speed limit, and turn restrictions.
  • the features of the links contained in the geographic database would be processed in the same manner as positional data. If one collector vehicle traverses a link in the opposite direction of travel as maintained in the map database 56 , but a significant number of other collections indicate tracking in the same direction of travel as maintained in the map database 56 , the single case may be archived as statistically insignificant.
  • the central geographic data manager 10 may collect only raw data or only filtered sensor data such that it would include only a raw sensor data collector 28 or a filtered sensor data collector 12 and the components used to process either raw sensor data or filtered sensor data.
  • the update distributor 26 may be responsible for distributing Updates according to a schedule, or in a manner.
  • Advantages of the embodiments of the systems described herein include the ability to receive data for processing database updates directly from users of the navigation system. Because the users of the navigation system may be numerous, this may reduce the need to take measures to determine if changes have occurred to the geographical area, such as, sending employees to verify the area such as by visiting the area and recording information or by taking aerial pictures or by checking municipal records.

Abstract

A method for updating a geographic database is disclosed. Data collecting equipment is installed in each of a plurality of vehicles each of which also has a navigation system. The data collection equipment is used to collect data while the vehicles are being driven along roads by their respective users. In addition, a method for assigning a confidence level to geographic data is disclosed. The confidence level is assigned to the geographic data as an attribute. In addition, a method for determining a position of a vehicle by sensing roadside structures is disclosed. Data indicating positions of roadside structures are contained in a geographic database. By matching positions of sensed roadside structures to data in the geographic database that indicates the positions of the structures, the position of the vehicle while traveling can be determined.

Description

    REFERENCE TO RELATED APPLICATION
  • The present application is a continuation of Ser. No. 10/298,798, filed Nov. 18, 2002, which was a continuation of Ser. No. 09/532,751 filed Mar. 22, 2000, now U.S. Pat. No. 6,516,267, which was a continuation of Ser. No. 08/951,767, filed Oct. 16, 1997, now U.S. Pat. No. 6,047,234.
  • BACKGROUND OF THE INVENTION
  • The present invention relates to a system and method for updating and enhancing a geographic database, and more particularly, the present invention relates to a system and method for updating and enhancing a geographic database based on feedback from field use of the geographic data.
  • Computer-based navigation systems for use on land have become available in a variety of forms and for a variety of applications. One exemplary type of system uses a geographic data set, a navigation application, and optionally, a positioning system. The geographic data set includes information about the positions of roads and intersections in or related to a specific geographical area, and may also include information about one-way streets, traffic signals, stop signs, turn restrictions, street addresses, alternative routes, hotels, restaurants, museums, stadiums, offices, automobile dealerships, auto repair shops, etc.
  • The optional positioning system may employ any of several well-known technologies to determine or approximate one's physical geographic location. For example, the positioning system may employ a GPS-type system (global positioning system), a “dead-reckoning”-type system, or combinations of these, or other systems, all of which are known in the art.
  • The navigation application portion of the navigation system is a software program that uses the detailed geographic data set and the positioning system (when employed). The navigation application program may provide the user with a graphical display (e.g. a “map”) of a specific location in the geographical area. The navigation application may provide the user with data indicating his own location and specific directions to locations in the geographical area from wherever he is located.
  • Computer-based navigation systems may exist as a single unit that may be installed in a vehicle, or even carried by persons. The navigation application and geographic data set may be provided as software products that are sold or licensed to users to load in personal computers. Systems operating on personal computers may be stand-alone or connected by a communication link to a central or regional system. Organizations, such as trucking companies, package delivery services, and emergency dispatch units may employ navigation systems to track fleets and ensure the quickest routes to destinations. The navigation systems may also be made available on-line from a central system to multiple users on an “as needed” basis, or from on-line services such as services available on the Internet and private dial-up services.
  • Individual users can use navigation systems to obtain directions to a desired destination thereby reducing travel time and expenses. The directions can include detours around construction delays. Directions may be provided to street addresses, intersections, or to entities by name, such as to restaurants, hotels and service stations.
  • One potential obstacle to providing enhanced features with a navigation system is the difficulty in maintaining up-to-date information in the geographic data set. A publisher of geographic data may obtain the information that becomes part of geographic data sets from field personnel sent to the locations to record the information or from aerial photographs or municipal records or other sources. Geographic information, however, becomes outdated as new roads are built, existing roads are changed, traffic signals are installed, businesses change their hours of operation, new businesses open, existing businesses close, etc. When changes occur, data in the geographic data set becomes inaccurate and its utility is thereby lessened.
  • Information identifying changes are collected using the same techniques as described above. Once the information regarding changes is collected, it is incorporated into a master geographic data set. The publisher of geographic databases then periodically distributes updated geographic data reflecting the changes to end-user. However, the process of acquiring information regarding changes is time-consuming and expensive. Moreover, existing methods of acquiring updated data may become increasingly expensive as geographic databases become more detailed and extensive in scope.
  • Another limitation with existing methods of data acquisition is accuracy. Even with high quality aerial photographs and other existing collection methods, the geographic coordinates of features may not always be entered in the database with a high level of precision. While existing methods are generally adequate to provide geographic data of sufficient accuracy for vehicle positioning in route guidance applications, greater geographical accuracy may be required for certain other applications, such as vehicle control.
  • Accordingly, a system and method are desired that would provide for a more efficient acquisition of information reflecting changes and corrections in geographic areas to navigation systems. Further, a system and method are desired that allow the accuracy of the data in a geographic database to be enhanced.
  • SUMMARY OF THE INVENTION
  • In view of the above, a first aspect of the present invention is directed to a system for updating, enhancing and/or refining a geographic database. A geographic database includes data representing physical features in the geographic region, and, optionally, attributes of such features. The system includes a plurality of data collecting sensors. Each of the data collecting sensors is installed in a separate one of a plurality of vehicles each of which is capable of traveling on roads in a geographic region. Each of the data collecting sensors provides outputs indicative of one or more features in the geographic region as the vehicle in which it is installed travels on the roads in the geographic region. A computer program executes a feedback process on the geographic database using the outputs of the data collecting sensors. A first part of the feedback program compares the outputs of the data collecting sensors to the data identifying the physical features and provides results representative of the comparisons. A second part of the feedback program is responsive to the results from the first part and determines the significance of the comparisons. A third part of the feedback program modifies the data in the geographic database based upon the significance determined by the second part of the program.
  • In a further aspect of the system, the data in the geographic database representing physical features in the geographic region are updated, enhanced, or refined based upon the significance determined by the feedback program.
  • In another aspect of the invention, the data which has been updated, enhanced, or refined, is used to provide updated, enhanced, or refined data in end-user vehicles, some of which may include the vehicles in which data collecting sensors have been installed.
  • According to another aspect of the invention, sensors in end-users' vehicles are calibrated to high levels of accuracy using the data which has been updated, enhanced or refined using a feedback process.
  • According to still another aspect of the invention, an out-of-calibration sensor in an end-user's vehicle is detected and re-calibrated using the data which has been updated, enhanced or refined using a feedback process.
  • In yet still another aspect of the invention, using a feedback process, levels of confidence of accuracy are assigned to data in the geographic database representing physical features in the geographic region, thereby enabling the data to be used for purposes requiring high levels of confidence.
  • In the aspects mentioned above, the data collecting sensors may be used to sense the geographic position of the vehicle (derived from GPS, dead-reckoning, or other positioning systems), vehicle speed, road gradient, lane width (derived from radar, and other similar systems), signage (derived from cameras), road direction (derived from an on-board compass or other heading-determining means), and various other physical features. The data in the geographic database may represent roads (or road segments) and their positions, as well as other attributes relating to roads.
  • In another aspect, the present invention is directed to a method of updating a geographic database by the steps of storing road data that includes a plurality of map positions in the geographic database. A plurality of actual positions traveled is determined by a vehicle by repeatedly sensing actual position while the vehicle moves. At least a portion of the plurality of actual positions is matched with a plurality of map positions in the geographic database. A position difference is calculated between each actual position in the plurality of actual positions and the plurality of map positions. Each actual position for which the position difference exceeds a predetermined tolerance level is stored as a plurality of unmatched positions.
  • DETAILED DESCRIPTION OF THE DRAWINGS
  • FIG. 1 is a diagram illustrating a system according to a first embodiment.
  • FIGS. 2A-2C are diagrams illustrating alternative embodiments of the data collection vehicles shown in FIG. 1.
  • FIG. 3 is a flow chart illustrating a method for processing sensor data using the system of FIG. 1.
  • FIGS. 4A-4E illustrate the application of the method of using the system of Figure to update a geographic data set.
  • FIGS. 5A-5L illustrates the method of using the system in FIG. 1 as applied to a sample portion of a geographic data set.
  • FIGS. 6A-6E illustrate an enhancement to the method of using the system of FIG. 1.
  • FIGS. 7A-7D illustrate another enhancement to the method of using the system of FIG. 1.
  • FIGS. 8A-8G illustrate a method of using the system in FIG. 1 as applied to non-positional features of a geographical area.
  • FIG. 9 is a diagram illustrating a data entity record in the geographic database including an indication of the confidence level.
  • FIG. 10 is a flow chart indicating the steps for performing another aspect of a feedback process using data collection vehicles.
  • FIG. 11 is a flow chart indicating the steps for re-calibrating an out-of-calibration sensor in a vehicle.
  • DETAILED DESCRIPTION OF THE PRESENTLY PREFERRED EMBODIMENTS
  • I. System Overview
  • Referring to FIG. 1, a system 9 for updating and enhancing a geographic database includes a central geographic data manager 10. The central geographic data manager 10 includes a central geographic database 20. The geographic database 20 includes data that represents physical features in a geographical area 47. The central geographic database 20 may include data descriptive of position data in terms of points 44 on the map and of links, or segments of roads 45. The central geographic database 20 may also include data representing road gradients, road widths, lane widths and shoulder widths, and data that is descriptive of stationary objects such as stop signs, buildings, bridge supports, etc. The central geographic database 20 may include non-positional features such as speed limits, the direction of travel allowed on the roads and the directions of allowed turns. The central geographic database 20 may include other types of information as well, for example, types of restaurants, museum hours, etc.
  • Located in the geographic region 47 are a plurality of data collection vehicles 50 (including vehicles 50(1), 50(2) . . . 50(n)). Each of the data collection vehicles 50 includes a data collection system 39. Each data collection system 39 includes one or more sensors capable of collecting data representing physical features about the environment of the vehicle or the vehicle's physical position as the vehicle is moving or while it is stopped. As each of the data collection vehicles 50 moves on the roads (or is stopped) in the geographic area 47, the sensors in the data collection system of the vehicle sense physical features. These data collection vehicles 50 may include vehicles in which in-vehicle navigation systems are installed, or vehicles which have only data collection system equipment without on-board navigation systems, or may include both types of vehicles. The plurality of vehicles 50 may include vehicles which are owned (or leased) by private party end-users as well as fleet vehicles. Some of the data collection vehicles 50 include local copies of a geographic database 56 (shown in FIGS. 2A and 2B) which may be a copy or version of a portion of the central geographic database 20. The data collection vehicles 50 communicate data derived from their data collection systems to the central geographic data manager 10 using suitable communications links 49.
  • II. Data Collection Vehicles
  • FIGS. 2A-2C illustrate alternative embodiments of the data collection vehicles 50.
  • FIG. 2A illustrates an embodiment of a data collection vehicle 50(1) which processes sensor data 54 into filtered sensor data 55F for communication to the central geographic data manager 10. The data collection vehicle 50(1) includes a data collection system 39(1) which includes a vehicle computing system 52, a sensor data processor 53, a communications manager 58, a local map database 56, and one or more sensors 60. (The data collection vehicle 50(1) may also include an update manager 59 which is not necessarily part of the data collection system 39(1).) In this embodiment of the data collection vehicle, parts of the data collection system 39(1) may be shared with an in-vehicle navigation system. For example, the sensors 60, the vehicle computing system 52 and the map database 56 may be components of an in-vehicle navigation system and may be used by the vehicle driver for such purposes.
  • The outputs of the one or more sensor devices 60 provide sensor device data 54. The sensor devices 60 may include a GPS (Global Positioning System), an imaging system (e.g. radar, cameras, etc.), a gyroscope, a compass, an odometer and other sensors. The sensor devices 60 output data 54 as the vehicle 50(1) moves around the geographic region 47 or while it is stopped. The output 54 from the sensor devices 60 is provided to the vehicle computing system 52 of the data collection system 39(1).
  • The sensor data processor 53, using the data 54 output from the sensors 60 to the vehicle computing system 52, compares the sensor device data 54 with data in the local map database 56. The sensor data processor 53 may be implemented as a computer program executed on the CPU of the vehicle computing system 52 or may executed on a separate processor. The sensor data processor 53 determine variances between the sensor device data 54 and the data in the local map database 56 based on comparisons between the sensor device data 54 and corresponding elements in the map database 56. The variances depend upon the type of data being compared. For example, if the output of a position sensor is being compared to a corresponding position in the local map database 56, the variance may be a distance representing the difference between the two values. The variance may also include the relative direction of the difference. The variance is compared to threshold levels above or below which the sensor output may be considered unmatched to a map database element. The threshold levels may be based on factors such as the tolerances of the sensors.
  • The sensor data processor 53 processes the sensor data 54 into filtered sensor data 55F. The filtered sensor data may include only the variances that exceed a certain predefined threshold. The filtered sensor data may be temporarily stored on a data storage device (not shown) in the vehicle.
  • In one embodiment of the data collection vehicle 50(1), the communications manager 58 is used to transmit the filtered sensor data 55F to the central geographic data manager 10 of FIG. 1. The communications manager 58 may utilize any appropriate means for data transmission, including wireless (49 in FIG. 1), cellular, modem uploads, e-mail, and so on. Data may be communicated at any time. For example, data may be communicated as it is obtained. Alternatively, the data 55F may be stored and communicated at a fixed time, such as daily or weekly at a specified time. The data 55F may also be communicated to an intermediate data collection system and then transferred to the manager 10. In another alternative embodiment, data is collected in the vehicle on a disk and uploaded by modem or sent by mail to the manager 10.
  • In the embodiment of FIG. 2A, data may be selected from the filtered sensor data 55F for communication to the central geographic data manager 10. For example, data that indicates variances beyond a certain level may be selected for communication to the central geographic data manager 10. Alternatively, all of the filtered sensor data 55F, including variances that indicate a perfect match between sensor device data and data in the local database 56 may be communicated to the central geographic data manager 10. By sending all of the filtered sensor data 55F, the central geographic data manager 10 may determine the reliability of the geographic database 20 by confirming the accuracy of the existing data in the central geographic database 20.
  • FIG. 2B illustrates another embodiment of a data collection vehicle 50(2). The embodiment 50(2) of FIG. 2B collects raw sensor data and communicates it to the central geographic data manager 10. The data collection vehicle 50(2) includes a data collection system 39(2) which includes a sensor driver 51, a vehicle computing system 52, a communications manager 58, a local map database 56, and one or more sensors 60. (The data collection vehicle 50(2) may also include an update manager 59 which is not necessarily part of the data collection system 39(2).) As in the embodiment of FIG. 2A, an in-vehicle navigation system may be used as part of the data collection system.
  • The outputs of the one or more sensor devices 60, which may be the same as those identified above, provide sensor device data 54 . The sensor devices 60 collect data as the vehicle 50(2) moves around or stops in the geographic region 47. A sensor driver 51, which may be a software program, processes the sensor device data 54 into raw sensor data 55R. (The functions performed by the sensor driver 51 may include, for example, converting essentially analog outputs of sensors 60 into appropriate digital data, scaling the data, time stamping the data, compressing the data, identifying the types of sensors that generate the data, organizing the raw data for storage purposes, and so on.) The raw sensor data 55R may be temporarily stored in a data storage device (not shown) in the vehicle 50(2). The raw sensor data 55R is communicated to the central data manager 10. The communications manager 58, which may be similar to the communications manager in the embodiment of FIG. 2A, may be used for this purpose.
  • Another embodiment of a data collection vehicle 50(3) is illustrated in FIG. 2C. The data collection vehicle 50(3) includes a data collection system 39(3) including a sensor driver 51, a temporary storage 63, and sensors 60. These components perform similar functions as the like numbered components in FIGS. 2A and 2B. As shown, the data collection vehicle 50(3) in FIG. 2C does not include an in-vehicle navigation system. The data collection vehicle 50(3) in FIG. 2C stores raw sensor data 55R in the temporary storage 63. A user then transfers the data to a floppy disk or to a removable hard disk drive and physically sends the data to the central data manager 10. Alternatively, the data collection system 39(3) in the vehicle may include a communications manager that provides functions, similar to those described above, to transfer the data to the central data manager.
  • III. Central Geographic Data Manager
  • A. Collection of Data From Vehicles
  • The central geographic data manager 10 illustrated in FIG. 1 includes hardware and software components for receiving data 55R and 55F from the data collection vehicles 50 and for processing the data to generate updates, refinements, and/or enhancements to the central geographic database 20. The central geographic data manager 10 may also assign levels of reliability to data in the database 20, as described below. The hardware and software components need not be located in one location or operate on one computer. Different components may be located in different places with known communications techniques used to connect them.
  • The central geographic data manager 10 receives raw sensor data 55R from the data collection vehicles 50(2), 50(3) that communicate non-filtered data at a raw data collector 28. The central geographic data manager 10 receives filtered data 55F from the data collection vehicles 50(1) at a filtered data collector 12. The filtered sensor data collector 12 and the raw sensor data collector 28 are interfaces to the communication links 49 and may be implemented by any suitable technology for receiving data. Each collector handles the data received from its corresponding plurality of data collection vehicles 50 and forwards the data to the appropriate processes in the central geographic data manager 10.
  • The filtered data collector 12 stores and organizes the filtered sensor data 55F in a central filtered sensor database 14. For vehicles that communicate raw data 55R to the central geographic data manager 10, the raw data collector 28 organizes the raw sensor data from the plurality of vehicles in a central raw data database 30. This collection of data is analyzed for variances by a central sensor data processor 32. The central sensor data processor is a computer program, similar to the local sensor data processor 53 of FIG. 2A, capable of calculating variances based on comparisons of the raw data with the geographic data in the central database 20. The central sensor data processor 32 stores variances as filtered sensor data in the filtered sensor database 14.
  • B. Updating/Enhancing the Central Database
  • The collection of data in the filtered sensor database 14 is analyzed by a statistical data analyzer 16. The statistical data analyzer 16 includes a computer program that applies statistical analysis techniques based on further comparisons with the geographic data in the central geographic database 20. The statistical analysis techniques may take into account thousands or millions of sensor readings to derive results with a high level of reliability and confidence. The statistical data analyzer 16 determines updates to the central geographic database 20 based on whether the central filtered sensor data set 14 reflects statistically significant variances. (Various kinds of statistical techniques for analyzing data using large numbers of readings are known and may be used.)
  • The statistical analysis techniques can also take into account historical information. For example, if a highly traveled road segment that was sensed thousands of times a day for years suddenly had no reported sensor readings, it would be an indication that the road was no longer open. An appropriate update to the central database, or at least an indication to verify a possible change in the database record, would be processed accordingly.
  • The statistical data analyzer 16 may determine confidence levels for data elements in the central geographic database 20. Referring to FIG. 9, confidence levels may be stored for data elements in the central geographic database 20. The confidence level is stored as an attribute of a data entity. The confidence level may be expressed as a magnitude that is indicative of the certainty to which the data entity in the central geographic database 20 matches the actual physical feature in the geographic region. The confidence level of an item of data may be increased or decreased according to the frequency and freshness with which the feature is sensed by the data collection vehicles. In FIG. 9, a data entity D represents a road segment record having positional information attributes. The road segment attributes include the latitude and longitude of the left and right nodes (L-LAT, L-LON, R-LAT, R-LON) of the road segment data entity D. A confidence level attribute CL includes a value (e.g. 1-10) which expresses the confidence that the positional data is accurate. For example, a confidence level of “10” may indicate that, based upon the statistical analysis, there is a greater than 99% certainty that the positional data (L-LAT, L-LON, R-LAT, R-LON) is within 1 cm. A confidence level of “8” may mean that, based upon statistical analysis, there is a 75% level of certainty that the positional data is within 1 meter, or that there is a 99% level of certainty that the positional data is within 15 meters.
  • The statistical data analyzer 16, the operation of which is discussed further below with reference to FIGS. 5A-5L, also provides for any layout changes that may be necessary when the database is modified. Such layout changes may involve creating new links, modifying the geometry of existing links, and designating features known about the new and existing links.
  • According to one method of updating, the statistical data analyzer 16 provides a message 18 to initiate an update process 22 for the central geographic database 20. The update process 22 collects the individual changes to the central geographic database 20 from the statistical data analyzer 16 and stores the changes in a queue of update transactions for a distribution process 24.
  • In one embodiment, the steps performed in the manager 10, including the determination of variances, the collection of data from the vehicles, the analysis of statistical significance, and the updating of the central database, are performed on an ongoing and continuous basis. However, in alternative embodiments, it may be preferred to perform some of these tasks intermittently or periodically.
  • C. Distributing Updates to Users
  • Referring to FIG. 1, at some point, data reflecting the updating process applied to the central database is released to the end-users. The release and/or distribution of data may be performed by an update distributor 26 Distribution may be accomplished electronically using the wireless communication links 49. In vehicles that have communications managers (such as in FIGS. 2A and 2B), the update distributor 26 may communicate updated information from the central data manager 10 directly back to the local communications managers 58 in the individual data collection vehicles 50. Other alternative means of distribution may be used including distribution of hard media, such as CD-ROM discs and PCMCIA cards, downloading to personal computers, and so on.
  • The end-users may include persons who use local versions 56 of geographic databases in their vehicles. The end-users may also include various others including, for example, personal computer users 46 and networks 48, such as on-line services, services that use the Internet and organizations that incorporate all or parts of the geographic database in applications such as emergency dispatch centers, truck fleet tracking and package delivery fleet tracking.
  • The releases may occur on a continuous basis, or may occur from time to time, or on a regular or irregular basis, a staggered basis, and so on. The release of data reflecting the updating process can be made in any of several different formats. According to one process for releasing updated data to end-users, the updated data may be released as a series of update transactions which are applied to each user's local copy of the geographic database, as needed. According to another process for releasing data to end-users, versions of the entire database reflecting the updated data may be provided.
  • A flow chart illustrating the process of the system 9 of FIG. 1 is shown in FIG. 3. The computing devices (32 in FIG. 1, 53 in FIG. 2A) use output from sensors (60 in FIGS. 2A-2C) to relate (Step S2 in FIG. 3) to a geographic database (20 in FIG. 1, 56 in FIG. 2A) and perform some action based on the interpretation of the sensor data and database content. Variances, including zero-variances, between the perceived reality derived from the sensor data and the content of the map database can be stored as filtered sensor data (Steps D1, S3, S4 in FIG. 3; 14 in FIG. 1; 55F in FIG. 2A) in a storage medium and communicated to a location in a central repository for database updating processing (16 in FIG. 1). The filtered sensor database (14 in FIG. 1) preferably will retain variances to allow statistical processing for more accurate updates. (Steps D2, S5, S6 in FIG. 3). After the update process has been applied to the central database (22 in FIG. 1), database updates are communicated to end-users of the database. (Alternatively, in the embodiments of FIGS. 2B and 2C, the raw data derived from the sensor devices may be stored in some medium and communicated to a separate system for comparison against the map database outside the scope of the vehicle navigation system.)
  • D. Feedback Calibration of Vehicle Sensors
  • In a further alternative embodiment, vehicle sensors in the various end-users' vehicles are fine-tuned for very high levels of accuracy by a feedback process. The feedback process uses the collection of sensor data from a large number of vehicles (using the process described above, for example) to provide highly accurate geographic data in the central database which in turn is distributed to individual end-user vehicles and used to adjust and calibrate the sensors in each of the individual end-user vehicles to conform to the known-to-be-highly accurate geographic data. In this manner, the continued use of data collection vehicles and the redistribution of known-to-be-highly accurate data to the individual end-users' vehicles for calibrating of the sensors in the vehicles forms a feedback loop which pumps up the accuracy of the sensors in each of the individual vehicles. The accuracy that can be obtained in this manner can exceed the accuracy that could be obtained by any one vehicle or any one sensor measurement using conventional techniques. A diagram illustrating this process is shown in FIG. 10.
  • Using the feedback calibration process described above, highly accurate data having a high confidence level can be developed. The levels of accuracy that can be achieved can be as high as
    Figure US20050149259A1-20050707-P00900
    1 cm, or better. Given these levels of accuracy, it is possible to use a geographic database for vehicle control and safety systems. With high levels of accuracy in both the geographic database and the vehicle positioning sensors, the safety systems can automatically determine if the vehicle is deviating from the roadway, veering out of its lane, and so on. In conjunction with the high levels of accuracy, the safety systems or vehicle control systems use the confidence level attributes, described above, to confirm that the data is not only accurate but also reliable.
  • In another alternative embodiment, out-of-alignment sensors in a vehicle can be detected and corrected using a feedback process. Using a feedback process to develop highly accurate data, as described above, once geographic data is known-to-be highly accurate (i.e. its confidence level is high) as a result of statistical analysis of a large number of data records collected from a large number of vehicles over a significant period of time, if one vehicle using the data reports variances, then it can be determined that the sensors in the variance-reporting vehicle are likely out of calibration. Then, using only the variance data reported from the one vehicle and the known-to-be-highly accurate data, the sensors in the variance-reporting vehicle are re-calibrated to the same level of accuracy as all the other vehicles. (It is understood that as a step in the process, it may be required to acquire data for a period of time from other data-collecting vehicles after the variances are collected from the variance-reporting vehicle to confirm that other data-collecting vehicles do not observe the same variances.) A diagram illustrating this process is shown in FIG. 11.
  • In further aspect of this embodiment, the data collection systems in each of the data collection vehicles provide data that identifies of the types of sensors being used to collect the data. Then, when variances from a vehicle are collected, the type of sensors measuring the variances are taken into account. For example, if a type of sensor reports variances that suggest it should be re-calibrated, it is first compared to similar kinds of sensors. This permits a better evaluation of the extent to which the particular type of sensor can be calibrated based on the accuracy which is achievable in like-equipped vehicles.
  • V. Processing Sensor Data
  • A. Comparing The Sensor Data And A Geographic Database
  • Processing of a modification to an existing database based upon the collection of data from a single vehicle is illustrated in connection with FIGS. 4A-4C. This example refers to positional information (latitude, longitude, and altitude) and illustrates attempts to match positional sensor data to the elements in a geographic database (e.g. the central geographic database 20 in FIG. 1 or the map database 56 in FIGS. 2A and 2B). Similar steps would be used for other types of data.
  • FIG. 4A graphically depicts an area that may be represented in a geographic database. FIG. 4A illustrates map positions 80(1), 80(2) . . . 80(n) and map links 100(1), 100(2), . . . 100(n) representing road segments, connecting the map positions 80. In FIG. 4B, a set of actual positions 90(1) . . . 90(n) established by the sensor devices on the vehicle are denoted as arrows with time sequence identifiers T1-T14. The map matching process uses the vehicle's bearing, proximity to that link 100(1), and various link features to place the vehicle on a matched link 100(1).
  • The sensor data points are compared to map positions 80 and the matched link 100(1) by determining the shortest distance from the sensor data point to the matched link 100(1). If the resulting distance exceeds specified tolerance levels, or if sensor data conflicts with features of the matched link 100(1), a record of this variance is created along with relevant sensor data. The record, illustrated in FIG. 4C as a new link 110(1), is then stored in the filtered sensor database (55F of FIG. 2A or 14 of FIG. 1).
  • If a link is traversed with all sensor samples within the tolerance level, a record is created in the filtered sensor database, certifying the accuracy of the matched link and its features and identifying the sensor device or devices used.
  • FIG. 4D illustrates the collection of data over time with numerous collections of sensor data, which would result in a database update as indicated in FIG. 4E.
  • B. Updating The Central Geographic Database
  • The filtered sensor data includes information regarding potential new links and may be used to determine whether the geographic database is to be updated. During the update of the geographic database, features relative to the actual position may be determined from the sensor data. Data relating to such features may be included as filtered sensor data so that the features may be included in the update of the geographic database. For example, if only the data collection shown in FIGS. 4B and 4C were available, the new link 100(m) (also labeled L9) can be traversed from left to right (in the direction the collector vehicle traveled) based on the single collection of sensor data. When the new link 100(m) is added to the central geographic database 20 during an update operation, the restriction of allowing travel in the single direction may be added as a feature of the new link 100(m) until sensor data is received to indicate that travel may be allowed in the other direction.
  • The filtered sensor data may provide information regarding other features that may be used during the update of the geographic database. For example, the addition of the new link 100(m) forms two new links labeled 100(1)(2) (also L3 b) and 100(1)(1) (also L3 a) where previously only 100(1) (labeled L3) existed as illustrated in FIG. 4C. The update of the geographic database may include a feature allowing vehicles to traverse from link L3 a) to L9 (labeled 100(m)), but not from L3 b to L9. The feature may be revised if data supporting travel from L3 b to L9 is received.
  • FIGS. 5A-5L illustrate time sequence examples of using sensor data to update the geographic database. FIGS. 5A-5F illustrate a method of using sensor data to update the geographic database for a single sample of sensor data. FIGS. 5G-5L illustrate a method of using sensor data to update the geographic database after a second sample of data has been collected on the same link.
  • FIG. 5A contains a sample road network 120 and an example of a graphical representation 122 of the geographic database 20 (shown in FIG. 1) at its time of release. The geographic database 20 contains no link for Market St. between 1st St. and 2nd St. FIG. 5B illustrates the tracking of a vehicle with sensor devices generating actual positions 130, in relation to both the road network 120 and the database 122. The unfilled triangles 130U in FIG. 5C represent positions which were able to match to links in the database as denoted by the arrows. The filled triangles 130F in FIG. 5C represent positions which would exceed map matching tolerance levels and therefore induce the map matching process to store these positions as unmatched in the filtered sensor database. The unmatched positions may be stored as an ordered set of points 136 as shown in FIG. 5D. The contents of the entry in the filtered sensor database would be the previous link L8 successfully matched, the latitude/longitude of each unmatched position, and the next link L11 successfully matched. The data analyzer processor 16 (in FIGS. 1 and 2A) then derives a new link using the method illustrated in FIGS. 5E and 5F.
  • A new link may be derived by determining the shortest distance 180 from the first unmatched position 175 to the previous link L8, and splitting the link at that nearest point 190 on the link L8 creating two new links L8A and L8B out of link L8. The processor 16 then determines the shortest distance 182 from the last unmatched position 176 to the next link L11 matched, and splitting the link at that nearest point 192 on link L11, creating two new links L11A and L11B out of link L11.
  • Beginning at the intersection of L8A and L8B, the new link 100(q)is constructed by joining all unmatched positions and terminating at the intersection of links L11A and L11B as shown in FIG. 5E. The filtered position database is then updated to associate all unmatched positions with the new link 100(q).
  • The resulting database content is illustrated in FIG. 5F. At this point, features may be added to this new link which may include the direction of travel (from left to right), the average speed, and the fact that turns can legally be made from L8B to 100(q), and from 100(q) to L11A.
  • FIGS. 5G-5L illustrate a process of using sensor data to update the geographic database after a second sample of data has been collected. FIG. 5G contains the same example of the road network 120, and the depiction of the map database 122 as updated in FIGS. 5A-5F. FIG. 5H contains a new set of sensor data points 202 for a vehicle traveling in the opposite direction. FIG. 5I highlights the positions 202U which exceeded map matching tolerance levels, but may have been determined to match the new link 100(q). The map matching process will store these positions 202U with the filtered sensor data as an ordered set of points 206 as shown in FIG. 5J. The filtered sensor data may include the previous link matched L11A, the ordered set of points 206, the next link matched L8B, and the assumed match 100(q). The sensor data processor would then update the geographic database using a process described below with reference to FIGS. 5J, 5K and 5L.
  • In updating the geographic database, all ordered sets of points from the filtered sensor data which have been associated with the new link 100(q), which in this example is the ordered sets of points 206, are identified. In addition, all positions for the same direction of travel as the positions being processed (in this example, the ordered sets of points 206) are identified. In this example, the positions represented by the ordered set of points 206 are for the direction opposite the direction of the new link 100(q). The ordered set of points 206 are then averaged using a sequential averaging or curve fitting technique to create a single sequence of positions.
  • An intersection point 214 with the nearest link to the beginning position of the ordered set 206 is identified. An intersection point 216 with the nearest link to the ending position in the ordered set is also identified.
  • All points having a direction of travel opposite the direction of the ordered set of points 136 are then averaged using the sequential averaging or curve-fitting technique to create an opposite direction ordered set of points 136A. In the example in FIG. 5J, no points were collected in the second sample traveling in the same direction as the new link 100(q). Therefore, the new link 100(q), or points in the new link 100(q), may be used for the opposite direction ordered set of points 136A.
  • The distance between the sets of points in opposite directions 136, 136A is averaged by calculating half the distance from each point starting with the ordered set of points represented by the most points to yield a set of average points 136M in FIG. 5J. The average points 136M are then designated as the new link 100(q)(new) in FIG. 5K. Alternatively, the new link 100(q)(new) could be modified by moving it to correspond with the average points 136C. The link features may now be updated to identify the direction of travel as being both directions. The average speed may also be updated. It may be assumed that turns can be legally made from L11B to 100(q)(new) and from 100(q)(new) to L8B. The resulting database content is illustrated in FIG. 5L.
  • C. Trend Analysis
  • The collection of data over time illustrated in FIG. 4D may be subjected to a process of trend analysis as illustrated in FIGS. 6A-6E. The addition of link L5 in FIG. 6C may be used as an update to the map database in FIG. 6A, based on the sensor data provided from the samples in FIG. 6B. However, FIG. 6D illustrates that the path of the vehicle was actually a maneuver through a filling station. FIG. 6E illustrates a trend analysis, with the dense lines 250 representing a high instance of sensor data positions and the dotted line 260 representing the single traversal of the vehicle whose path is defined in FIG. 6B. Applying statistical analysis of the entire sensor collection would result in the link L5 being classified as statistically insignificant and not being added to the geographic map database 20.
  • FIGS. 7A-7D further illustrate how geographic updates can be implemented using sensor data from a feedback loop with trend analysis. A graphical illustration of a portion of the map database 20 in its original state is shown in FIG. 7A. FIG. 7B represents the original database content with the heavier arcs 270 representing the average paths determined from sensor data. The two distinct arcs may be dependent upon bearing and statistical normalization. As illustrated in FIG. 7C, a new arc 290 is generated at the geometrical center 292 of the tracking arcs T1 and T2. The original link Lorig is then updated to reflect the new geometry defined by the new arc 290. Curve fitting and other standard techniques could be employed alternatively to determine positional changes.
  • D. Variances of Data Representing Other Features
  • The same process for determining variances used to collect basic positional information (latitude, longitude, and altitude) as shown in FIG. 3 can also be applied to other physical features which describe the physical road structure. For example, FIGS. 8A-8B illustrate vehicles that are collecting road gradient information. FIG. 8C illustrates a vehicle that is collecting information regarding road width, lane width, and shoulder width. The information provided by the sensor devices is compared against the database and variance/confidence information is communicated through the loop described above with reference to FIGS. 3 and 4A-4E. This type of data is used by advanced vehicle safety systems, described above, because the more accurate and refined the database, the earlier and more intelligently system action can be taken. By reducing the margin of error for lane width, a system which detects erratic driving patterns can engage earlier and be more successful. A system which detects excessive speed during curve traversal can more accurately determine the maximum safe speed based on the bank of the curve.
  • Sensor devices which can identify objects in the path of a vehicle can be confused by permanent structures (for example signs, pillars, overpasses, poles, etc.). Maintaining an accurate model of these permanent structures can enable the sensor devices to filter out objects that may otherwise be interpreted as a potential hazard. By increasing the confidence level of the database, as described above, systems that identify road hazards can engage with the appropriate action more reliably. Variances may be determined for database elements that represent objects when compared to images sensed from image sensors using a process similar to the process in FIG. 3. In connection with the detection of images, signs or other landmarks can be detected by cameras using image or shape detecting programs. The sign text on the signs is recorded and variances are stored, as described above. In addition, the location of signs or other road side landmarks can be sensed, stored, and compared for variances. These landmarks can include not only signs, but any detectable feature, including lamp posts, viaducts, etc. The position of any detectable feature can be measured for variances and used for calibration, generating confidence levels, and so on. In this manner, the positions of many kinds of landmarks can be detected relatively inexpensively.
  • Knowledge of, and greater precision in, the position data for permanent structures also facilitates vehicle positioning useful in route guidance and other applications. For example, when a vehicle travels a significant distance along a straight road, the vehicle's position can become more uncertain as errors associated with the positioning sensors accumulate. Enhanced knowledge of the position of permanent structures along such straight roadways can serve as a landmarks to which the vehicle position can be corrected (or map-matched) when the landmark is sensed.
  • In an embodiment illustrating this feature, a vehicle includes sensors which may be similar to the sensors 60 in FIGS. 2A-2C. The vehicle sensors have the capability to detect structures. In one embodiment, the structure-detecting sensor is a radar system. The vehicle also includes an automatic vehicle control system and includes a local geographic database (similar to the database 56 of FIGS. 2A and 2B). The local geographic database has data that includes road side detectable features, such as sign posts, viaducts, lamp posts, and so on. The local geographic database also includes data relating to roads. Using the detection of the road side structures, such as lamp posts, viaducts, and so on, the position of the vehicle in the geographic region can be determined by a map matching program. Map matching programs are known. Given the known locations of radar-detectable features, such as lamp posts, viaducts, for example, the position of the vehicle can be determined very accurately by matching the vehicles' position onto road segments in the geographic database. The position of the vehicle can be fine-tuned by matching the position to the known positions of the detectable roadside landmarks. With this level of accuracy, an automatic safety system can be implemented that automatically avoids obstacles detected by the radar.
  • As shown in FIGS. 8D-8G, the sensor devices, which for permanent structure analysis includes image sensors, determine static elements in the field of vision, compare the image footprint to the database and record the difference or confidence information as necessary. FIGS. 8D, 8F and 8G illustrate how image sensors identify signs according to sign location, dimension and content at 300 and sign post location at 302. FIGS. 8E and 8G illustrate how image sensors may identify permanent structures such as guard rails 304, bridge supports 306 and nearby structures 308.
  • Sensor data may also be evaluated with respect to non-positional features that may be represented in the database to identify potential errors and establish confidence levels for these features. Examples of features to evaluate include: direction of travel, divider location, speed limit, and turn restrictions. The features of the links contained in the geographic database would be processed in the same manner as positional data. If one collector vehicle traverses a link in the opposite direction of travel as maintained in the map database 56, but a significant number of other collections indicate tracking in the same direction of travel as maintained in the map database 56, the single case may be archived as statistically insignificant.
  • Embodiments of a system for updating a geographic database have been described. Alternative embodiments can be appreciated from this disclosure by one of ordinary skill in the art. For example, the central geographic data manager 10 may collect only raw data or only filtered sensor data such that it would include only a raw sensor data collector 28 or a filtered sensor data collector 12 and the components used to process either raw sensor data or filtered sensor data. In addition, no limitation is placed on the scheduling of the distribution of updates by the update distributor 26. Updates may be distributed according to a schedule, or in a manner.
  • Advantages of the embodiments of the systems described herein include the ability to receive data for processing database updates directly from users of the navigation system. Because the users of the navigation system may be numerous, this may reduce the need to take measures to determine if changes have occurred to the geographical area, such as, sending employees to verify the area such as by visiting the area and recording information or by taking aerial pictures or by checking municipal records.
  • Presently preferred embodiments of the present invention have been described. One of ordinary skill in the art can appreciate that other embodiments that fall within the scope of the claims are possible. It is intended that the foregoing detailed description be regarded as illustrative rather than limiting and that it is understood that the following claims including all equivalents are intended to define the scope of the invention.

Claims (21)

1-25. (canceled)
26. A method of collecting data for a geographic database comprising:
using data collection equipment in each of a plurality of end users' vehicles to collect data while said end users' vehicles are being driven along roads;
sending at least a portion of the data collected by said data collection equipment to a central database; and
updating the central database using the portion of the data collected.
27. The method of claim 26 wherein the data collected relates to geographic positions.
28. The method of claim 26 wherein the data collected relates to vehicle speed.
29. The method of claim 26 wherein the data collected relates to road gradient.
30. The method of claim 26 wherein the data collected relates to lane width.
31. The method of claim 26 wherein the data collected relates to signage.
32. The method of claim 26 wherein the data collected relates to road direction.
33. The method of claim 26 wherein the data collection equipment includes cameras.
34. The method of claim 26 wherein the data collection equipment includes radar systems.
35. The method of claim 26 wherein the data collection equipment includes compasses.
36. The method of claim 26 wherein the data collection equipment includes GPS units.
37. The method of claim 26 wherein the data collection equipment includes dead-reckoning units.
38. The method of claim 26 further comprising:
before the step of updating, comparing the portion of data collected to data already contained in said central database.
39. The method of claim 38 further comprising:
after the comparing step, indicating a confidence level associated with data contained in said central database.
40. The method of claim 26 further comprising:
prior to the step of sending, filtering the data collected while said end users' vehicles are being driven along roads.
41. The method of claim 26 wherein the data collection equipment in at least some of the plurality of end users' vehicles is part of a navigation system.
42. A system for collecting data for a geographic database comprising:
data collection equipment installed in each of a plurality of end users' vehicles, wherein said data collection equipment is operable to collect data while said end users' vehicles are being driven along roads;
a central database;
a communications system that sends at least a portion of the data collected by said data collection equipment to a central database; and
a central geographic data manager that receives the portion of the data collected by said data collection equipment and updates the central database using the portion of the data collected.
43. The system of claim 42 wherein the data collected relates to one of geographic positions, vehicle speed, road gradient, lane width, signage, and road direction.
44. A method of collecting data for a central geographic database and improving quality of data contained in the central geographic database, wherein the method comprises a process that
uses end users' vehicles, suitable equipped with data collection equipment, to collect data while said end users' vehicles are being driven along roads, and
thereafter sends at least a portion of the data collected by said data collection equipment to the central database where the central database is updated using the portion of the data collected,
whereupon data from the updated database is used to provide navigation related features to at least some of the end users.
45. The method of claim 44 wherein the data collected relates to one of geographic positions, vehicle speed, road gradient, lane width, signage, and road direction.
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Cited By (61)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040015115A1 (en) * 2002-05-07 2004-01-22 Dmitriy Sinyagin Method for treating wound, dressing for use therewith and apparatus and system for fabricating dressing
US20040088110A1 (en) * 2002-08-26 2004-05-06 Keizo Suzuki Method and apparatus for displaying navigation information
US20070035563A1 (en) * 2005-08-12 2007-02-15 The Board Of Trustees Of Michigan State University Augmented reality spatial interaction and navigational system
US20070124064A1 (en) * 2005-11-30 2007-05-31 Fujitsu Limited Map information updating system, central apparatus, map information updating method and recording medium
WO2007037986A3 (en) * 2005-09-21 2007-11-01 Boeing Co Creation of optimized terrain databases
US20080004761A1 (en) * 2006-06-30 2008-01-03 Denso Corporation Control information storage apparatus and program for same
US20080018497A1 (en) * 2006-07-18 2008-01-24 John Edward Farnham Integrated data logging unit
US20080082254A1 (en) * 2006-10-02 2008-04-03 Yka Huhtala Route-assisted GPS location sensing via mobile device
US20080147305A1 (en) * 2006-12-07 2008-06-19 Hitachi, Ltd. Car Information System, Map Server And On-Board System
US20080167594A1 (en) * 2007-01-10 2008-07-10 Oleg Siniaguine Wound dressing with controllable permeability
US20080177738A1 (en) * 2007-01-22 2008-07-24 Fujitsu Limited. Map data processing method and apparatus
US20090020554A1 (en) * 2004-07-16 2009-01-22 Polyremedy Inc. Wound dressing and apparatus for forming same
US20090030607A1 (en) * 2006-03-14 2009-01-29 Pioneer Corporation Position registering apparatus, route retrieving apparatus, position registering method, position registering program, and recording medium
US20090138497A1 (en) * 2007-11-06 2009-05-28 Walter Bruno Zavoli Method and system for the use of probe data from multiple vehicles to detect real world changes for use in updating a map
US20090204423A1 (en) * 2002-05-07 2009-08-13 Polyremedy, Inc. Wound Care Treatment Service Using Automatic Wound Dressing Fabricator
US20090216442A1 (en) * 2008-02-26 2009-08-27 Nokia Corporation Method, apparatus and computer program product for map feature detection
US20090326429A1 (en) * 2008-06-30 2009-12-31 Oleg Siniaguine Custom Patterned Wound Dressings Having Patterned Fluid Flow Barriers and Methods of Manufacturing and Using Same
US20100026804A1 (en) * 2007-04-27 2010-02-04 Aisin Aw Co., Ltd. Route guidance systems, methods, and programs
US20100049148A1 (en) * 2008-08-22 2010-02-25 Oleg Siniaguine Expansion Units for Attachment to Custom Patterned Wound Dressings and Custom Patterned Wound Dressings Adapted to Interface With Same
US20100088021A1 (en) * 2007-04-26 2010-04-08 Marcus Rishi Leonard Viner Collection methods and devices
US20100241447A1 (en) * 2008-04-25 2010-09-23 Polyremedy, Inc. Customization of wound dressing using rule-based algorithm
US20110161032A1 (en) * 2007-08-29 2011-06-30 Continental Teves Ag & Co.Ohg Correction of a vehicle position by means of landmarks
WO2011155929A1 (en) * 2010-06-09 2011-12-15 Tele Atlas North America Inc. Systems and methods for processing information related to a geographic region
US20120050489A1 (en) * 2010-08-30 2012-03-01 Honda Motor Co., Ltd. Road departure warning system
US20120101718A1 (en) * 2009-03-31 2012-04-26 Thinkwaresystems Corp Map-matching apparatus using planar data of road, and method for same
US20130131980A1 (en) * 2007-09-07 2013-05-23 On Time Systems, Inc. Resolving gps ambiguity in electronic maps
US8676506B1 (en) 2011-11-15 2014-03-18 Google Inc. Systems and methods for identifying missing signage
US20140236382A1 (en) * 2012-04-17 2014-08-21 Lytx, Inc. Server request for downloaded information from a vehicle-based monitor
US9043138B2 (en) 2007-09-07 2015-05-26 Green Driver, Inc. System and method for automated updating of map information
US9183679B2 (en) 2007-05-08 2015-11-10 Smartdrive Systems, Inc. Distributed vehicle event recorder systems having a portable memory data transfer system
US9201842B2 (en) 2006-03-16 2015-12-01 Smartdrive Systems, Inc. Vehicle event recorder systems and networks having integrated cellular wireless communications systems
CN105117396A (en) * 2009-09-15 2015-12-02 美国结构数据有限公司 Processes and systems for collaborative manipulation of data
US9226004B1 (en) 2005-12-08 2015-12-29 Smartdrive Systems, Inc. Memory management in event recording systems
US9240079B2 (en) 2012-04-17 2016-01-19 Lytx, Inc. Triggering a specialized data collection mode
US20160094359A1 (en) * 2014-09-25 2016-03-31 Dell Products, L.P. Event notifications in a shared infrastructure environment
US9402060B2 (en) 2006-03-16 2016-07-26 Smartdrive Systems, Inc. Vehicle event recorders with integrated web server
US9501878B2 (en) 2013-10-16 2016-11-22 Smartdrive Systems, Inc. Vehicle event playback apparatus and methods
US9554080B2 (en) 2006-11-07 2017-01-24 Smartdrive Systems, Inc. Power management systems for automotive video event recorders
US9594371B1 (en) 2014-02-21 2017-03-14 Smartdrive Systems, Inc. System and method to detect execution of driving maneuvers
US9610955B2 (en) 2013-11-11 2017-04-04 Smartdrive Systems, Inc. Vehicle fuel consumption monitor and feedback systems
CN106568453A (en) * 2015-11-13 2017-04-19 深圳市步科电气有限公司 AGV automatic path exploring system, and method thereof
US9633318B2 (en) 2005-12-08 2017-04-25 Smartdrive Systems, Inc. Vehicle event recorder systems
US9663127B2 (en) 2014-10-28 2017-05-30 Smartdrive Systems, Inc. Rail vehicle event detection and recording system
US9728228B2 (en) 2012-08-10 2017-08-08 Smartdrive Systems, Inc. Vehicle event playback apparatus and methods
US9738156B2 (en) 2006-11-09 2017-08-22 Smartdrive Systems, Inc. Vehicle exception event management systems
US9761067B2 (en) 2006-11-07 2017-09-12 Smartdrive Systems, Inc. Vehicle operator performance history recording, scoring and reporting systems
US20180031384A1 (en) * 2016-07-28 2018-02-01 Toyota Motor Engineering & Manufacturing North America, Inc. Augmented road line detection and display system
CN107851125A (en) * 2015-08-11 2018-03-27 大陆汽车有限责任公司 The processing of two step object datas is carried out by vehicle and server database to generate, update and transmit the system and method in accurate road characteristic data storehouse
US20180239032A1 (en) * 2015-08-11 2018-08-23 Continental Automotive Gmbh System and method for precision vehicle positioning
US10083607B2 (en) 2007-09-07 2018-09-25 Green Driver, Inc. Driver safety enhancement using intelligent traffic signals and GPS
US20180357839A1 (en) * 2015-06-30 2018-12-13 Robert Bosch Gmbh Method and device for uploading data of a motor vehicle
US10198942B2 (en) 2009-08-11 2019-02-05 Connected Signals, Inc. Traffic routing display system with multiple signal lookahead
CN109766405A (en) * 2019-03-06 2019-05-17 路特迩科技(杭州)有限公司 Traffic and travel information service system and method based on electronic map
US10311724B2 (en) 2007-09-07 2019-06-04 Connected Signals, Inc. Network security system with application for driver safety system
US10678776B1 (en) * 2010-10-06 2020-06-09 Google Llc Automated identification of anomalous map data
WO2020120696A1 (en) 2018-12-14 2020-06-18 Volkswagen Aktiengesellschaft Method, device, and computer program for a vehicle
US10930093B2 (en) 2015-04-01 2021-02-23 Smartdrive Systems, Inc. Vehicle event recording system and method
US11069257B2 (en) 2014-11-13 2021-07-20 Smartdrive Systems, Inc. System and method for detecting a vehicle event and generating review criteria
US11085774B2 (en) 2015-08-11 2021-08-10 Continental Automotive Gmbh System and method of matching of road data objects for generating and updating a precision road database
DE102020210515A1 (en) 2020-08-19 2022-03-24 Volkswagen Aktiengesellschaft Method for checking detected changes for an environment model of a digital environment map
EP3236212B1 (en) * 2016-04-22 2023-01-25 Volvo Car Corporation Method for generating navigation data and a navigation device for performing the method

Families Citing this family (413)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10361802B1 (en) 1999-02-01 2019-07-23 Blanding Hovenweep, Llc Adaptive pattern recognition based control system and method
US8352400B2 (en) 1991-12-23 2013-01-08 Hoffberg Steven M Adaptive pattern recognition based controller apparatus and method and human-factored interface therefore
US6526352B1 (en) * 2001-07-19 2003-02-25 Intelligent Technologies International, Inc. Method and arrangement for mapping a road
US7629899B2 (en) * 1997-10-22 2009-12-08 Intelligent Technologies International, Inc. Vehicular communication arrangement and method
US20040139049A1 (en) * 1996-08-22 2004-07-15 Wgrs Licensing Company, Llc Unified geographic database and method of creating, maintaining and using the same
US5999866A (en) * 1996-11-05 1999-12-07 Carnegie Mellon University Infrastructure independent position determining system
US6009355A (en) * 1997-01-28 1999-12-28 American Calcar Inc. Multimedia information and control system for automobiles
US7412398B1 (en) 1997-06-12 2008-08-12 Bailey G William Method for analyzing net demand for a market area utilizing weighted bands
US6604083B1 (en) * 1997-06-12 2003-08-05 G. William Bailey Market determination based on travel time bands
US8332247B1 (en) 1997-06-12 2012-12-11 G. William Bailey Methods and systems for optimizing network travel costs
US6148261A (en) * 1997-06-20 2000-11-14 American Calcar, Inc. Personal communication system to send and receive voice data positioning information
US6275231B1 (en) * 1997-08-01 2001-08-14 American Calcar Inc. Centralized control and management system for automobiles
JPH1165435A (en) * 1997-08-21 1999-03-05 Toyota Motor Corp Map data processor for vehicle
JP3546659B2 (en) * 1997-09-25 2004-07-28 トヨタ自動車株式会社 Vehicle data processing system, in-vehicle terminal device and navigation device constituting the system
DE19743705C1 (en) * 1997-10-02 1998-12-17 Ibs Integrierte Business Syste Method of collecting and combining positioning data from satellite location systems and other data
US6381533B1 (en) * 1997-10-16 2002-04-30 Navigation Technologies Corp. Method and system using positions of cellular phones matched to road network for collecting data
US6047234A (en) * 1997-10-16 2000-04-04 Navigation Technologies Corporation System and method for updating, enhancing or refining a geographic database using feedback
US20080154629A1 (en) * 1997-10-22 2008-06-26 Intelligent Technologies International, Inc. Vehicle Speed Control Method and Arrangement
US8209120B2 (en) * 1997-10-22 2012-06-26 American Vehicular Sciences Llc Vehicular map database management techniques
US10358057B2 (en) * 1997-10-22 2019-07-23 American Vehicular Sciences Llc In-vehicle signage techniques
US7266560B2 (en) * 1998-01-30 2007-09-04 Navteq North America, Llc Parcelized geographic data medium with internal spatial indices and method and system for use and formation thereof
US6697103B1 (en) 1998-03-19 2004-02-24 Dennis Sunga Fernandez Integrated network for monitoring remote objects
JP2000194726A (en) * 1998-10-19 2000-07-14 Sony Corp Device, method and system for processing information and providing medium
US6505165B1 (en) * 1999-01-28 2003-01-07 International Business Machines Corporation Method and apparatus for locating facilities through an automotive computing system
US7904187B2 (en) 1999-02-01 2011-03-08 Hoffberg Steven M Internet appliance system and method
US6343301B1 (en) * 1999-02-24 2002-01-29 Navigation Technologies Corp. Method and system for collecting data for updating a geographic database
US8630795B2 (en) 1999-03-11 2014-01-14 American Vehicular Sciences Llc Vehicle speed control method and arrangement
CA2266208C (en) * 1999-03-19 2008-07-08 Wenking Corp. Remote road traffic data exchange and intelligent vehicle highway system
EP1039265A1 (en) * 1999-03-23 2000-09-27 Sony International (Europe) GmbH System and method for automatically managing geolocation information
US6466862B1 (en) * 1999-04-19 2002-10-15 Bruce DeKock System for providing traffic information
US20060074546A1 (en) * 1999-04-19 2006-04-06 Dekock Bruce W System for providing traffic information
DE19930796A1 (en) * 1999-07-03 2001-01-11 Bosch Gmbh Robert Method and device for transmitting navigation information from a data center to a vehicle-based navigation system
DE19933638A1 (en) 1999-07-17 2001-01-18 Bosch Gmbh Robert Navigational method for a means of transportation
DE19933639A1 (en) * 1999-07-17 2001-01-18 Bosch Gmbh Robert Procedure for calculating a route from a start to a destination
DE19935770A1 (en) * 1999-07-23 2001-02-01 Ddg Ges Fuer Verkehrsdaten Mbh Feedback cascade
DE19935769C2 (en) * 1999-07-23 2002-02-07 Ddg Ges Fuer Verkehrsdaten Mbh Traffic condition forecast through feedback cascade
US7107286B2 (en) * 1999-07-26 2006-09-12 Geoqwest International Inc. Integrated information processing system for geospatial media
US6681231B1 (en) 1999-07-26 2004-01-20 The Real Estate Cable Network, Inc. Integrated information processing system for geospatial media
US6438491B1 (en) 1999-08-06 2002-08-20 Telanon, Inc. Methods and apparatus for stationary object detection
US6385539B1 (en) * 1999-08-13 2002-05-07 Daimlerchrysler Ag Method and system for autonomously developing or augmenting geographical databases by mining uncoordinated probe data
DE19938691A1 (en) * 1999-08-14 2001-02-15 Volkswagen Ag Traffic-guided influencing and/or support of motor vehicles involves detecting objects, including relative speed, using distance measurements to detect traffic situations
JP2003509710A (en) 1999-09-07 2003-03-11 ローベルト ボツシユ ゲゼルシヤフト ミツト ベシユレンクテル ハフツング Method for encoding and decoding objects in a traffic road network
WO2001020260A1 (en) * 1999-09-15 2001-03-22 Sirf Technology, Inc. Navigation system and method for tracking the position of an object
US6341255B1 (en) 1999-09-27 2002-01-22 Decell, Inc. Apparatus and methods for providing route guidance to vehicles
US7236462B2 (en) * 1999-10-04 2007-06-26 General Electric Company Method for data exchange with a mobile asset considering communication link quality
US6292724B1 (en) * 1999-10-12 2001-09-18 Micrologic, Inc. Method of and system and apparatus for remotely monitoring the location, status, utilization and condition of widely geographically dispresed fleets of vehicular construction equipment and the like and providing and displaying such information
US6366851B1 (en) 1999-10-25 2002-04-02 Navigation Technologies Corp. Method and system for automatic centerline adjustment of shape point data for a geographic database
US6674434B1 (en) * 1999-10-25 2004-01-06 Navigation Technologies Corp. Method and system for automatic generation of shape and curvature data for a geographic database
US6516273B1 (en) * 1999-11-04 2003-02-04 Veridian Engineering, Inc. Method and apparatus for determination and warning of potential violation of intersection traffic control devices
WO2001043104A1 (en) * 1999-12-10 2001-06-14 David Sitrick Methodology, apparatus, and system for electronic visualization of traffic conditions
ATE326747T1 (en) * 1999-12-15 2006-06-15 Vert Inc SYSTEM AND METHOD FOR MANAGING ADVERTISING AND INFORMATION DISPLAYS ON VEHICLES BASED ON AN E-COMMERCE WEBSITE
DE19962997B4 (en) * 1999-12-24 2010-06-02 Robert Bosch Gmbh Method for calibrating a sensor system
US6314365B1 (en) 2000-01-18 2001-11-06 Navigation Technologies Corp. Method and system of providing navigation services to cellular phone devices from a server
DE10004969A1 (en) 2000-02-04 2001-08-16 Bosch Gmbh Robert Method and device for managing traffic disruptions for navigation devices
GB2358975B (en) * 2000-02-05 2004-05-05 Jaguar Cars Motor vehicle trajectory measurement
DE10007348C2 (en) * 2000-02-18 2003-07-10 Harman Becker Automotive Sys navigation system
JP4599649B2 (en) * 2000-03-09 2010-12-15 株式会社エクォス・リサーチ Billing processing apparatus in data communication network
US7187947B1 (en) 2000-03-28 2007-03-06 Affinity Labs, Llc System and method for communicating selected information to an electronic device
US6381537B1 (en) * 2000-06-02 2002-04-30 Navigation Technologies Corp. Method and system for obtaining geographic data using navigation systems
US6253151B1 (en) * 2000-06-23 2001-06-26 Navigation Technologies Corp. Navigation system with feature for reporting errors
JP2002116689A (en) * 2000-07-06 2002-04-19 Pioneer Electronic Corp Updating method of road information in map information providing system, its updating server, server program and recording medium recorded with the program
US6977630B1 (en) * 2000-07-18 2005-12-20 University Of Minnesota Mobility assist device
US7375728B2 (en) * 2001-10-01 2008-05-20 University Of Minnesota Virtual mirror
US20050149251A1 (en) * 2000-07-18 2005-07-07 University Of Minnesota Real time high accuracy geospatial database for onboard intelligent vehicle applications
EP1305573B1 (en) * 2000-07-25 2008-04-30 Deutsche Telekom AG Method for providing traffic information
US20050091175A9 (en) * 2000-08-11 2005-04-28 Telanon, Inc. Automated consumer to business electronic marketplace system
US20090109037A1 (en) * 2000-08-11 2009-04-30 Telanon, Inc. Automated consumer to business electronic marketplace system
US20030130893A1 (en) * 2000-08-11 2003-07-10 Telanon, Inc. Systems, methods, and computer program products for privacy protection
US7339483B1 (en) 2000-08-11 2008-03-04 Telanon, Inc. Automated consumer to business electronic marketplace system
US6587781B2 (en) 2000-08-28 2003-07-01 Estimotion, Inc. Method and system for modeling and processing vehicular traffic data and information and applying thereof
US6873998B1 (en) * 2000-10-18 2005-03-29 Navteq North America, Llc System and method for updating a geographic database using satellite imagery
US6397143B1 (en) * 2000-10-26 2002-05-28 George Peschke Layout based method for map navigation
US6766319B1 (en) 2000-10-31 2004-07-20 Robert J. Might Method and apparatus for gathering and evaluating information
DE10055156A1 (en) * 2000-11-07 2002-05-16 Harman Becker Automotive Sys Method for generating a navigation map and navigation map
WO2002039367A1 (en) * 2000-11-10 2002-05-16 Martin Roger L Route data base generation procedures and systems, processes and products relating thereto
EP1340187A2 (en) * 2000-11-22 2003-09-03 Koninklijke Philips Electronics N.V. Candidate level multi-modal integration system
EP1213905B1 (en) 2000-12-06 2011-08-17 Siemens AG Location dependent data collection
GB0029656D0 (en) * 2000-12-06 2001-01-17 Roke Manor Research Location aware mobile phones
JP5041638B2 (en) 2000-12-08 2012-10-03 パナソニック株式会社 Method for transmitting location information of digital map and device used therefor
US6816798B2 (en) * 2000-12-22 2004-11-09 General Electric Company Network-based method and system for analyzing and displaying reliability data
DE10065593A1 (en) * 2000-12-28 2002-07-04 Bosch Gmbh Robert Method and device for generating road segment data for a digital map
US7058710B2 (en) * 2001-02-22 2006-06-06 Koyo Musen Corporation Collecting, analyzing, consolidating, delivering and utilizing data relating to a current event
EP1241447A1 (en) * 2001-03-13 2002-09-18 Matsushita Electric Industrial Co., Ltd. Information terminal and cartographic information providing system
US7548875B2 (en) 2001-06-27 2009-06-16 John Mikkelsen Media delivery platform
AU2002346211B2 (en) 2001-06-27 2008-06-12 Sony Corporation Integrated circuit device, information processing device, information recording device memory management method, mobile terminal device, semiconductor integrated circuit device, and communication method using mobile terminal device
US7552008B2 (en) * 2001-07-18 2009-06-23 Regents Of The University Of Minnesota Populating geospatial database for onboard intelligent vehicle applications
JP2003051095A (en) 2001-08-07 2003-02-21 Mazda Motor Corp Server, method and program for changing control gain of automobile
DE10146098B4 (en) * 2001-09-19 2005-05-19 Robert Bosch Gmbh Method for detecting and storing supplementary digitized route information and navigation system for this purpose
DE10148224A1 (en) * 2001-09-28 2003-04-30 Bosch Gmbh Robert Method and system for determining card data
US7089162B2 (en) * 2001-11-07 2006-08-08 Harman International Industries, Incorporated Navigation map creation system
DE10162335A1 (en) * 2001-12-18 2003-07-10 Zf Lemfoerder Metallwaren Ag Method and device for generating and updating a route and / or route status map
US6636799B2 (en) * 2001-12-21 2003-10-21 Motorola, Inc. Method and apparatus for modification of vehicular navigation information
US6687606B1 (en) 2002-02-21 2004-02-03 Lockheed Martin Corporation Architecture for automatic evaluation of team reconnaissance and surveillance plans
US6718261B2 (en) 2002-02-21 2004-04-06 Lockheed Martin Corporation Architecture for real-time maintenance of distributed mission plans
US6725152B2 (en) * 2002-02-21 2004-04-20 Lockheed Martin Corporation Real-time route and sensor planning system with variable mission objectives
US7647232B2 (en) 2002-02-21 2010-01-12 Lockheed Martin Corporation Real-time team coordination system for reconnaissance and surveillance missions
US7209051B2 (en) * 2002-03-05 2007-04-24 University Of Minnesota Intersection assistance system and method
US6816784B1 (en) * 2002-03-08 2004-11-09 Navteq North America, Llc Method and system using delivery trucks to collect address location data
US6651001B2 (en) * 2002-03-18 2003-11-18 Micrologics, Inc. Method of and system and apparatus for integrating maintenance vehicle and service personnel tracking information with the remote monitoring of the location, status, utilization and condition of widely geographically dispersed fleets of vehicular construction equipment and the like to be maintained, and providing and displaying together both construction and maintenance vehicle information
JP3903479B2 (en) * 2002-04-18 2007-04-11 日本電気株式会社 Information provision system
US7499949B2 (en) * 2002-08-07 2009-03-03 Navteq North America, Llc Method and system for obtaining recurring delay data using navigation systems
US7433889B1 (en) 2002-08-07 2008-10-07 Navteq North America, Llc Method and system for obtaining traffic sign data using navigation systems
US20040077347A1 (en) * 2002-08-30 2004-04-22 Ronald Lauber Modular analog wireless data telemetry system adapted for use with web based location information distribution method and method for developing and disseminating information for use therewith
AU2003288909A1 (en) * 2002-09-20 2004-04-08 Racom Products, Inc. Method for wireless data system distribution and disseminating information for use with web base location information
DE10244329A1 (en) * 2002-09-23 2004-04-01 Daimlerchrysler Ag Sensor device for a motor vehicle system
US7127352B2 (en) * 2002-09-30 2006-10-24 Lucent Technologies Inc. System and method for providing accurate local maps for a central service
DE10258470B4 (en) * 2002-12-09 2012-01-19 Volkswagen Ag Navigation device for motor vehicles
US7145478B2 (en) * 2002-12-17 2006-12-05 Evolution Robotics, Inc. Systems and methods for controlling a density of visual landmarks in a visual simultaneous localization and mapping system
JP4380151B2 (en) * 2002-12-20 2009-12-09 株式会社デンソー Map evaluation system and map evaluation device
DE10261028A1 (en) * 2002-12-24 2004-07-08 Robert Bosch Gmbh Process for the transmission of location-related information
US20040203909A1 (en) * 2003-01-01 2004-10-14 Koster Karl H. Systems and methods for location dependent information download to a mobile telephone
US8032659B2 (en) * 2003-01-21 2011-10-04 Nextio Inc. Method and apparatus for a shared I/O network interface controller
US6847887B1 (en) * 2003-03-04 2005-01-25 Navteq North America, Llc Method and system for obtaining road grade data
US7099882B2 (en) 2003-04-29 2006-08-29 Navteq North America, Llc Method and system for forming, updating, and using a geographic database
US6850841B1 (en) 2003-05-15 2005-02-01 Navtech North American, Llc Method and system for obtaining lane data
USRE47986E1 (en) 2003-05-15 2020-05-12 Speedgauge, Inc. System and method for evaluating vehicle and operator performance
US7302339B2 (en) * 2003-07-21 2007-11-27 Justin Gray Hazard countermeasure system and method for vehicles
GB0318194D0 (en) * 2003-08-02 2003-09-03 Nissan Technical Ct Europ Ltd Navigation system
AT500123B1 (en) * 2003-08-28 2007-01-15 Oesterreichisches Forschungs U METHOD AND ARRANGEMENT FOR DETERMINING THE ROUTES OF TRANSPORT PARTICIPANTS
US7079946B2 (en) * 2003-08-29 2006-07-18 Denso Corporation Iterative logical renewal of navigable map database
US20050060299A1 (en) * 2003-09-17 2005-03-17 George Filley Location-referenced photograph repository
US6856897B1 (en) 2003-09-22 2005-02-15 Navteq North America, Llc Method and system for computing road grade data
US7035733B1 (en) * 2003-09-22 2006-04-25 Navteq North America, Llc Method and system for obtaining road grade data
JP4604474B2 (en) * 2003-10-14 2011-01-05 株式会社エクォス・リサーチ Road information correction device
JP4606036B2 (en) * 2004-02-12 2011-01-05 アルパイン株式会社 Navigation system and map data update method
US7689321B2 (en) * 2004-02-13 2010-03-30 Evolution Robotics, Inc. Robust sensor fusion for mapping and localization in a simultaneous localization and mapping (SLAM) system
JP4684565B2 (en) * 2004-03-23 2011-05-18 三菱電機株式会社 Guidance information retrieval apparatus and guidance information retrieval system using the same
JP4703136B2 (en) * 2004-06-02 2011-06-15 トヨタ自動車株式会社 Line drawing processing equipment
US20050278386A1 (en) * 2004-06-15 2005-12-15 Geographic Data Technology, Inc. Geospatial information system and method for updating same
US7363151B2 (en) * 2004-06-21 2008-04-22 Matsushita Electric Industrial Co., Ltd. Map error information obtaining system and map error information obtaining method
US7620402B2 (en) 2004-07-09 2009-11-17 Itis Uk Limited System and method for geographically locating a mobile device
GB0418201D0 (en) * 2004-08-14 2004-09-15 Koninkl Philips Electronics Nv A fibre or filament
JP4581564B2 (en) * 2004-08-31 2010-11-17 株式会社デンソー Map display device
US7835856B2 (en) * 2004-10-25 2010-11-16 General Motors Llc Method and system for telematics location sensing
WO2006060518A2 (en) * 2004-11-30 2006-06-08 Circumnav Networks, Inc. Methods for deducing road geometry and connectivity
JP2006171456A (en) * 2004-12-16 2006-06-29 Denso Corp Method, apparatus, and program for evaluating accuracy of map data, and method for generating correction map data
US7908080B2 (en) 2004-12-31 2011-03-15 Google Inc. Transportation routing
US7355527B2 (en) * 2005-01-10 2008-04-08 William Franklin System and method for parking infraction detection
US7397424B2 (en) * 2005-02-03 2008-07-08 Mexens Intellectual Property Holding, Llc System and method for enabling continuous geographic location estimation for wireless computing devices
US9392406B2 (en) 2005-02-03 2016-07-12 Trueposition, Inc. Method and system for location-based monitoring of a mobile device
US8565788B2 (en) 2005-02-03 2013-10-22 Mexens Intellectual Property Holding Llc Method and system for obtaining location of a mobile device
US7360124B2 (en) * 2005-02-09 2008-04-15 Viasat Geo-Technologie Inc. Autonomous network fault detection and management system
US7275014B1 (en) 2005-02-10 2007-09-25 At&T Corporation Distributed graph layout for sensor node networks
JP4627007B2 (en) * 2005-05-06 2011-02-09 三菱電機株式会社 Map correction information selection device, map correction information selection method, and map correction information selection program
US20060271552A1 (en) * 2005-05-26 2006-11-30 Venture Capital & Consulting Group, Llc. Targeted delivery of content
US7636632B2 (en) * 2005-06-09 2009-12-22 Toyota Motor Engineering & Manufacturing North America, Inc. Intelligent navigation system
JP4654823B2 (en) 2005-08-03 2011-03-23 株式会社デンソー Road map data update system and road detection system
JP4645352B2 (en) * 2005-08-08 2011-03-09 株式会社デンソー Map information update system
JP5075331B2 (en) 2005-09-30 2012-11-21 アイシン・エィ・ダブリュ株式会社 Map database generation system
JP4760274B2 (en) * 2005-09-30 2011-08-31 株式会社豊田中央研究所 Map update device
US7720581B2 (en) * 2005-10-11 2010-05-18 Toshiba America Research, Inc. Monitoring of vehicle conditions utilizing cellular broadcasts
US7948918B2 (en) * 2005-10-11 2011-05-24 Toshiba America Research, Inc. Network discovery utilizing cellular broadcasts/multicasts
JP4735179B2 (en) * 2005-10-12 2011-07-27 株式会社デンソー Vehicle control device
EP1946044B1 (en) * 2005-10-14 2013-03-13 Dash Navigation Inc. System and method for identifying road features
JP5127720B2 (en) * 2005-11-23 2013-01-23 ティーアールダブリュー・オートモーティブ・ユーエス・エルエルシー Electric power steering system
WO2007065725A1 (en) * 2005-12-09 2007-06-14 Technische Universität Darmstadt Digital database system for a navigation device, and system for monitoring a driving corridor of a means of locomotion
US7451045B2 (en) * 2006-01-17 2008-11-11 International Business Machines Corporation Method and system for providing travel direction annotations over a network
US20070179820A1 (en) * 2006-01-27 2007-08-02 Robin Gaster Regional Benchmarking System
DE102006004130B4 (en) * 2006-01-27 2012-02-16 Audi Ag Method for determining a future course of the road by communicating between motor vehicles
JP2007226111A (en) * 2006-02-27 2007-09-06 Pioneer Electronic Corp Map information editing device, map information research device, map information research system, map information research method, map information editing program, and map information research program
DE102006010572A1 (en) * 2006-03-06 2007-09-13 Gerhard Lauche Traffic guidance system for use in vehicle, has data processing unit transmitting processed data to application unit over communication unit, where application unit uses data for computing vehicle travel route
US20080215237A1 (en) * 2006-05-17 2008-09-04 International Business Machines Corporation Design structure for adaptive route planning for gps-based navigation
US20070271034A1 (en) * 2006-05-17 2007-11-22 Perry Patrick E Adaptive route planning for gps-based navigation
US9507778B2 (en) 2006-05-19 2016-11-29 Yahoo! Inc. Summarization of media object collections
US8630768B2 (en) 2006-05-22 2014-01-14 Inthinc Technology Solutions, Inc. System and method for monitoring vehicle parameters and driver behavior
US9067565B2 (en) 2006-05-22 2015-06-30 Inthinc Technology Solutions, Inc. System and method for evaluating driver behavior
EP2034412A4 (en) 2006-06-09 2012-03-28 Aisin Aw Co Data update system, terminal device, server device, and data update method
US7314786B1 (en) * 2006-06-16 2008-01-01 International Business Machines Corporation Metal resistor, resistor material and method
GB0614530D0 (en) * 2006-07-21 2006-08-30 Trw Ltd Determining The Location of a Vehicle on a Map
JP4950590B2 (en) 2006-08-07 2012-06-13 クラリオン株式会社 Traffic information providing apparatus, traffic information providing system, traffic information transmission method, and traffic information request method
CN101154318B (en) 2006-09-05 2010-09-22 株式会社查纳位资讯情报 System and method for collecting and distributing traffic information, center device and vehicle carried terminal device
TWI287621B (en) * 2006-09-15 2007-10-01 Sin Etke Technology Co Ltd Precision positioning system for vehicles
US8417442B2 (en) 2006-09-19 2013-04-09 Intuitive Control Systems, Llc Collection, monitoring, analyzing and reporting of traffic data via vehicle sensor devices placed at multiple remote locations
DE102006061650A1 (en) * 2006-09-20 2008-04-03 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Concept for locating a position on a path
DE112007000069B4 (en) * 2006-10-10 2013-05-16 Mitsubishi Electric Corp. On-board information terminal, map information providing device and map information providing system
US8103448B2 (en) * 2006-10-25 2012-01-24 Denso Corporation Information storage apparatus for storing new road, program for the same, and system for the same
US8594702B2 (en) * 2006-11-06 2013-11-26 Yahoo! Inc. Context server for associating information based on context
US9110903B2 (en) * 2006-11-22 2015-08-18 Yahoo! Inc. Method, system and apparatus for using user profile electronic device data in media delivery
US8402356B2 (en) * 2006-11-22 2013-03-19 Yahoo! Inc. Methods, systems and apparatus for delivery of media
US8073617B2 (en) 2006-12-27 2011-12-06 Aisin Aw Co., Ltd. Map information generating systems, methods, and programs
US8769099B2 (en) * 2006-12-28 2014-07-01 Yahoo! Inc. Methods and systems for pre-caching information on a mobile computing device
DE102007003387A1 (en) * 2007-01-23 2008-07-31 Michael Cloos New route path making method for map system, involves adding new route path with route-away-specific data and vehicle-specific data, and providing new route path to map system on central map system database
US8935086B2 (en) * 2007-02-06 2015-01-13 GM Global Technology Operations LLC Collision avoidance system and method of detecting overpass locations using data fusion
US20080243378A1 (en) * 2007-02-21 2008-10-02 Tele Atlas North America, Inc. System and method for vehicle navigation and piloting including absolute and relative coordinates
CN101275854A (en) * 2007-03-26 2008-10-01 日电(中国)有限公司 Method and equipment for updating map data
JP4437556B2 (en) * 2007-03-30 2010-03-24 アイシン・エィ・ダブリュ株式会社 Feature information collecting apparatus and feature information collecting method
JP4446201B2 (en) * 2007-03-30 2010-04-07 アイシン・エィ・ダブリュ株式会社 Image recognition apparatus and image recognition method
JP4453046B2 (en) * 2007-03-30 2010-04-21 アイシン・エィ・ダブリュ株式会社 Vehicle behavior learning apparatus and vehicle behavior learning program
US8155826B2 (en) 2007-03-30 2012-04-10 Aisin Aw Co., Ltd. Vehicle behavior learning apparatuses, methods, and programs
JP4569837B2 (en) * 2007-03-30 2010-10-27 アイシン・エィ・ダブリュ株式会社 Feature information collecting apparatus and feature information collecting method
US8990003B1 (en) * 2007-04-04 2015-03-24 Harris Technology, Llc Global positioning system with internet capability
US9129460B2 (en) 2007-06-25 2015-09-08 Inthinc Technology Solutions, Inc. System and method for monitoring and improving driver behavior
US9117246B2 (en) 2007-07-17 2015-08-25 Inthinc Technology Solutions, Inc. System and method for providing a user interface for vehicle mentoring system users and insurers
US8818618B2 (en) 2007-07-17 2014-08-26 Inthinc Technology Solutions, Inc. System and method for providing a user interface for vehicle monitoring system users and insurers
US10007675B2 (en) * 2007-07-31 2018-06-26 Robert Bosch Gmbh Method of improving database integrity for driver assistance applications
DE102008012661A1 (en) * 2007-08-25 2009-02-26 Continental Teves Ag & Co. Ohg Update unit and method for updating a digital map
US20110037618A1 (en) * 2009-08-11 2011-02-17 Ginsberg Matthew L Driver Safety System Using Machine Learning
US20110037619A1 (en) * 2009-08-11 2011-02-17 On Time Systems, Inc. Traffic Routing Using Intelligent Traffic Signals, GPS and Mobile Data Devices
WO2009037164A1 (en) * 2007-09-13 2009-03-26 Continental Teves Ag & Co. Ohg Establishing quality parameters of a digital map
JP2009075647A (en) * 2007-09-18 2009-04-09 Aisin Aw Co Ltd Statistical processing server, probe information statistical method, and probe information statistical program
DE102007045082A1 (en) * 2007-09-21 2009-04-02 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Apparatus and method for updating map data
US7594441B2 (en) * 2007-09-27 2009-09-29 Caterpillar Inc. Automated lost load response system
JP4501983B2 (en) 2007-09-28 2010-07-14 アイシン・エィ・ダブリュ株式会社 Parking support system, parking support method, parking support program
US7876205B2 (en) 2007-10-02 2011-01-25 Inthinc Technology Solutions, Inc. System and method for detecting use of a wireless device in a moving vehicle
US8428856B2 (en) * 2007-10-29 2013-04-23 At&T Intellectual Property I, L.P. Methods, systems, devices, and computer program products for implementing condition alert services
US9310210B2 (en) * 2007-11-02 2016-04-12 Continental Teves Ag & Co. Ohg Verification of digital maps
US9103671B1 (en) 2007-11-29 2015-08-11 American Vehicular Sciences, LLC Mapping techniques using probe vehicles
US7418342B1 (en) 2007-12-03 2008-08-26 International Business Machines Corporation Autonomous destination determination
US8069142B2 (en) * 2007-12-06 2011-11-29 Yahoo! Inc. System and method for synchronizing data on a network
US8671154B2 (en) * 2007-12-10 2014-03-11 Yahoo! Inc. System and method for contextual addressing of communications on a network
US8307029B2 (en) * 2007-12-10 2012-11-06 Yahoo! Inc. System and method for conditional delivery of messages
US8166168B2 (en) 2007-12-17 2012-04-24 Yahoo! Inc. System and method for disambiguating non-unique identifiers using information obtained from disparate communication channels
WO2009080070A1 (en) * 2007-12-20 2009-07-02 Tomtom International B.V. Improved navigation device and method
JP4831434B2 (en) 2007-12-27 2011-12-07 アイシン・エィ・ダブリュ株式会社 Feature information collection device, feature information collection program, own vehicle position recognition device, and navigation device
US7865308B2 (en) * 2007-12-28 2011-01-04 Yahoo! Inc. User-generated activity maps
US9706345B2 (en) * 2008-01-04 2017-07-11 Excalibur Ip, Llc Interest mapping system
US9626685B2 (en) 2008-01-04 2017-04-18 Excalibur Ip, Llc Systems and methods of mapping attention
US8762285B2 (en) * 2008-01-06 2014-06-24 Yahoo! Inc. System and method for message clustering
US20090177378A1 (en) * 2008-01-07 2009-07-09 Theo Kamalski Navigation device and method
US20090182618A1 (en) 2008-01-16 2009-07-16 Yahoo! Inc. System and Method for Word-of-Mouth Advertising
AU2009211435A1 (en) * 2008-02-04 2009-08-13 Tele Atlas B.V. Method for map matching with sensor detected objects
US8351684B2 (en) * 2008-02-13 2013-01-08 Caterpillar Inc. Terrain map updating system
DE102009008959A1 (en) * 2008-02-15 2009-09-03 Continental Teves Ag & Co. Ohg Vehicle system for navigation and / or driver assistance
US8554623B2 (en) 2008-03-03 2013-10-08 Yahoo! Inc. Method and apparatus for social network marketing with consumer referral
US8560390B2 (en) 2008-03-03 2013-10-15 Yahoo! Inc. Method and apparatus for social network marketing with brand referral
US8538811B2 (en) * 2008-03-03 2013-09-17 Yahoo! Inc. Method and apparatus for social network marketing with advocate referral
CN101533561B (en) * 2008-03-12 2011-11-30 歌乐株式会社 Traffic information management server, navigation terminals and method thereof
US9080887B2 (en) * 2008-03-14 2015-07-14 Tomtom International B.V. Navigation device and method using map data correction files
US8589486B2 (en) 2008-03-28 2013-11-19 Yahoo! Inc. System and method for addressing communications
US8745133B2 (en) 2008-03-28 2014-06-03 Yahoo! Inc. System and method for optimizing the storage of data
US8271506B2 (en) 2008-03-31 2012-09-18 Yahoo! Inc. System and method for modeling relationships between entities
US8180518B2 (en) * 2008-04-15 2012-05-15 Robert Bosch Gmbh System and method for determining microenvironment conditions external to a vehicle
DE102009017731A1 (en) * 2008-04-30 2009-11-05 Continental Teves Ag & Co. Ohg Self-learning map based on environmental sensors
US7519472B1 (en) 2008-05-15 2009-04-14 International Business Machines Corporation Inferring static traffic artifact presence, location, and specifics from aggregated navigation system data
US8762035B2 (en) 2008-05-19 2014-06-24 Waze Mobile Ltd. System and method for realtime community information exchange
US8706406B2 (en) * 2008-06-27 2014-04-22 Yahoo! Inc. System and method for determination and display of personalized distance
US8452855B2 (en) 2008-06-27 2013-05-28 Yahoo! Inc. System and method for presentation of media related to a context
US8813107B2 (en) 2008-06-27 2014-08-19 Yahoo! Inc. System and method for location based media delivery
US8086700B2 (en) 2008-07-29 2011-12-27 Yahoo! Inc. Region and duration uniform resource identifiers (URI) for media objects
US10230803B2 (en) * 2008-07-30 2019-03-12 Excalibur Ip, Llc System and method for improved mapping and routing
US8583668B2 (en) 2008-07-30 2013-11-12 Yahoo! Inc. System and method for context enhanced mapping
US8386506B2 (en) * 2008-08-21 2013-02-26 Yahoo! Inc. System and method for context enhanced messaging
US8612136B2 (en) * 2008-08-27 2013-12-17 Waze Mobile Ltd. System and method for road map creation
US20100063993A1 (en) * 2008-09-08 2010-03-11 Yahoo! Inc. System and method for socially aware identity manager
US8281027B2 (en) * 2008-09-19 2012-10-02 Yahoo! Inc. System and method for distributing media related to a location
US20100076710A1 (en) * 2008-09-19 2010-03-25 Caterpillar Inc. Machine sensor calibration system
US9600484B2 (en) * 2008-09-30 2017-03-21 Excalibur Ip, Llc System and method for reporting and analysis of media consumption data
US8108778B2 (en) * 2008-09-30 2012-01-31 Yahoo! Inc. System and method for context enhanced mapping within a user interface
JP2012505449A (en) * 2008-10-08 2012-03-01 トムトム インターナショナル ベスローテン フエンノートシャップ Improvements for vehicle-mounted navigation devices
KR101025743B1 (en) * 2008-10-13 2011-04-04 한국전자통신연구원 The artificial retina driving apparatus using middle-distance wireless power transfer technology
US8032508B2 (en) * 2008-11-18 2011-10-04 Yahoo! Inc. System and method for URL based query for retrieving data related to a context
US8024317B2 (en) 2008-11-18 2011-09-20 Yahoo! Inc. System and method for deriving income from URL based context queries
US9805123B2 (en) * 2008-11-18 2017-10-31 Excalibur Ip, Llc System and method for data privacy in URL based context queries
US8060492B2 (en) * 2008-11-18 2011-11-15 Yahoo! Inc. System and method for generation of URL based context queries
US20100131194A1 (en) * 2008-11-25 2010-05-27 Jeyhan Karaoguz Map data management using road ghosting characteristics
US9224172B2 (en) 2008-12-02 2015-12-29 Yahoo! Inc. Customizable content for distribution in social networks
US8055675B2 (en) 2008-12-05 2011-11-08 Yahoo! Inc. System and method for context based query augmentation
US8166016B2 (en) * 2008-12-19 2012-04-24 Yahoo! Inc. System and method for automated service recommendations
US20120023057A1 (en) * 2008-12-31 2012-01-26 Mark Winberry Systems and methods for processing information related to a geographic region
US20100185517A1 (en) * 2009-01-21 2010-07-22 Yahoo! Inc. User interface for interest-based targeted marketing
US20100185518A1 (en) * 2009-01-21 2010-07-22 Yahoo! Inc. Interest-based activity marketing
GB0901588D0 (en) 2009-02-02 2009-03-11 Itis Holdings Plc Apparatus and methods for providing journey information
US8963702B2 (en) 2009-02-13 2015-02-24 Inthinc Technology Solutions, Inc. System and method for viewing and correcting data in a street mapping database
US20100228582A1 (en) * 2009-03-06 2010-09-09 Yahoo! Inc. System and method for contextual advertising based on status messages
US8271057B2 (en) * 2009-03-16 2012-09-18 Waze Mobile Ltd. Condition-based activation, shut-down and management of applications of mobile devices
US20100241689A1 (en) * 2009-03-19 2010-09-23 Yahoo! Inc. Method and apparatus for associating advertising with computer enabled maps
US8150967B2 (en) * 2009-03-24 2012-04-03 Yahoo! Inc. System and method for verified presence tracking
DE102009016055A1 (en) * 2009-04-02 2010-10-07 Bayerische Motoren Werke Aktiengesellschaft Method for operating a driver assistance system of a vehicle
DE102010014902B4 (en) * 2009-04-23 2019-02-07 Bomag Gmbh Multipurpose compactor and method of operating the multipurpose compactor
US20100280913A1 (en) * 2009-05-01 2010-11-04 Yahoo! Inc. Gift credit matching engine
US20100280879A1 (en) * 2009-05-01 2010-11-04 Yahoo! Inc. Gift incentive engine
US8432288B2 (en) * 2009-06-15 2013-04-30 Qualcomm Incorporated Sensors in communication devices
US9291463B2 (en) 2009-08-03 2016-03-22 Tomtom North America, Inc. Method of verifying or deriving attribute information of a digital transport network database using interpolation and probe traces
US10223701B2 (en) * 2009-08-06 2019-03-05 Excalibur Ip, Llc System and method for verified monetization of commercial campaigns
US8914342B2 (en) 2009-08-12 2014-12-16 Yahoo! Inc. Personal data platform
US8364611B2 (en) 2009-08-13 2013-01-29 Yahoo! Inc. System and method for precaching information on a mobile device
WO2011023246A1 (en) * 2009-08-25 2011-03-03 Tele Atlas B.V. A vehicle navigation system and method
EP2470863B1 (en) * 2009-08-25 2014-12-24 Tomtom Belgium N.V. Digital map editing process using active contour manipulation
DE102009041586B4 (en) 2009-09-15 2017-06-01 Deutsches Zentrum für Luft- und Raumfahrt e.V. Method for increasing the accuracy of sensor-detected position data
US9140559B2 (en) * 2009-10-01 2015-09-22 Qualcomm Incorporated Routing graphs for buildings using schematics
US8812015B2 (en) 2009-10-01 2014-08-19 Qualcomm Incorporated Mobile device locating in conjunction with localized environments
US8340894B2 (en) * 2009-10-08 2012-12-25 Honda Motor Co., Ltd. Method of dynamic intersection mapping
US8880103B2 (en) 2009-10-12 2014-11-04 Qualcomm Incorporated Method and apparatus for transmitting indoor context information
WO2011047729A1 (en) * 2009-10-22 2011-04-28 Tele Atlas B.V. Incremental map generation, refinement and extension with gps traces
PT104798B (en) * 2009-10-23 2018-12-31 Inst Politecnico De Beja METHOD FOR GENERATING OBSTACLE AIRCRAFT CARDS BASED ON THE MERGER OF INTERFEROMETRY DATA BY SYNTHETIC OPENING RADARS BASED ON SPACE PLATFORMS WITH OTHER DATA CATCHED BY REMOTE SENSORS
US20110098915A1 (en) * 2009-10-28 2011-04-28 Israel Disatnik Device, system, and method of dynamic route guidance
US20110106448A1 (en) * 2009-10-29 2011-05-05 Delphi Technologies, Inc. Database System and Method of Obtaining and Communicating Data
US8504512B2 (en) * 2009-12-02 2013-08-06 Microsoft Corporation Identifying geospatial patterns from device data
US8818641B2 (en) 2009-12-18 2014-08-26 Honda Motor Co., Ltd. Method of intersection estimation for a vehicle safety system
US20110153266A1 (en) * 2009-12-23 2011-06-23 Regents Of The University Of Minnesota Augmented vehicle location system
CN102753939B (en) * 2009-12-23 2016-08-03 通腾北美有限公司 Time that network in numerical map produces and/or the interdependent weight of degree of accuracy
US9689685B2 (en) * 2010-01-21 2017-06-27 Qualcomm Incorporated Methods and apparatuses for use in route navigation involving a mobile station
US9389085B2 (en) * 2010-01-22 2016-07-12 Qualcomm Incorporated Map handling for location based services in conjunction with localized environments
US20110191161A1 (en) * 2010-02-02 2011-08-04 Xia Dai Secured Mobile Transaction Device
JP5066206B2 (en) * 2010-03-11 2012-11-07 日立オートモティブシステムズ株式会社 Link string conversion method, road information providing apparatus, and road information providing system
JP5126263B2 (en) * 2010-03-23 2013-01-23 株式会社デンソー Vehicle navigation device
JP5057183B2 (en) * 2010-03-31 2012-10-24 アイシン・エィ・ダブリュ株式会社 Reference data generation system and position positioning system for landscape matching
US8791996B2 (en) * 2010-03-31 2014-07-29 Aisin Aw Co., Ltd. Image processing system and position measurement system
DE102010028090A1 (en) * 2010-04-22 2011-12-01 Robert Bosch Gmbh Method for navigating e.g. vehicle, involves implementing navigation of vehicle in dependent upon stored navigation data, which comprises confidence levels that indicate confidence of correctness of navigation data that includes objects
US8650193B1 (en) * 2010-07-23 2014-02-11 Google Inc. Road splitting in a map editor
US8823556B2 (en) * 2010-09-02 2014-09-02 Honda Motor Co., Ltd. Method of estimating intersection control
US8612138B2 (en) * 2010-09-15 2013-12-17 The University Of Hong Kong Lane-based road transport information generation
US8618951B2 (en) 2010-09-17 2013-12-31 Honda Motor Co., Ltd. Traffic control database and distribution system
CA2812723C (en) 2010-09-24 2017-02-14 Evolution Robotics, Inc. Systems and methods for vslam optimization
KR20120064276A (en) * 2010-12-09 2012-06-19 한국전자통신연구원 System and method for providing navigation routes for mobile terminal
US9599476B2 (en) * 2010-12-30 2017-03-21 Tomtom Global Content B.V. Seamless network generation
US8618952B2 (en) 2011-01-21 2013-12-31 Honda Motor Co., Ltd. Method of intersection identification for collision warning system
WO2012119087A1 (en) * 2011-03-03 2012-09-07 Telogis, Inc. Vehicle route calculation
JP5353926B2 (en) * 2011-03-09 2013-11-27 株式会社デンソー Navigation device
US20120233102A1 (en) * 2011-03-11 2012-09-13 Toyota Motor Engin. & Manufact. N.A.(TEMA) Apparatus and algorithmic process for an adaptive navigation policy in partially observable environments
DE102011005843A1 (en) * 2011-03-21 2012-09-27 Robert Bosch Gmbh Method for reducing the clamping force exerted by a locking eccentric
GB2492369B (en) 2011-06-29 2014-04-02 Itis Holdings Plc Method and system for collecting traffic data
DE102011106828B4 (en) * 2011-07-07 2013-07-04 Audi Ag Method for providing track data in a motor vehicle, as well as a floor-mounted device
DE102011083378B4 (en) 2011-09-26 2015-07-16 Robert Bosch Gmbh Device and method for checking route data
US8798840B2 (en) * 2011-09-30 2014-08-05 Irobot Corporation Adaptive mapping with spatial summaries of sensor data
DE102011084264A1 (en) 2011-10-11 2013-04-11 Robert Bosch Gmbh Method and device for calibrating an environmental sensor
DE102011084275A1 (en) 2011-10-11 2013-04-11 Robert Bosch Gmbh Method for operating a driver assistance system and method for processing vehicle environment data
DE102011116245B4 (en) * 2011-10-18 2018-10-25 Audi Ag Method for determining current route information of a digital map
DE102011084993A1 (en) * 2011-10-21 2013-04-25 Robert Bosch Gmbh Transfer of data from image data-based map services to an assistance system
DE102011086244A1 (en) * 2011-11-14 2013-05-16 Robert Bosch Gmbh Method for operating a sensor
US9075141B2 (en) * 2011-12-08 2015-07-07 Cambridge Silicon Radio Limited Mini-map-matching for navigation systems
DE102012200192A1 (en) * 2012-01-09 2013-07-11 Robert Bosch Gmbh Method and device for operating a vehicle
DE102012202186A1 (en) 2012-02-14 2013-08-14 Robert Bosch Gmbh Method for providing environmental information
US8494707B1 (en) 2012-02-29 2013-07-23 International Business Machines Corporation Maintaining a dynamic service registry for a self-diagnosing device
DE102012102693A1 (en) * 2012-03-29 2013-10-02 Continental Automotive Gmbh Method for providing traffic information in vehicle, involves receiving transmitted traffic information of secondary vehicle through primary communication device and outputting through optical output unit and acoustic output unit
WO2013185102A1 (en) 2012-06-08 2013-12-12 Irobot Corporation Carpet drift estimation using differential sensors or visual measurements
GB201211636D0 (en) 2012-06-29 2012-08-15 Tomtom Belgium Nv Method and apparatus for detecting deviations from map data
DE102012216788A1 (en) * 2012-09-19 2014-05-28 Bayerische Motoren Werke Aktiengesellschaft Method for obtaining quality data relating to information of switching times/conditions of traffic lights and/or variable message signs, involves comparing actual and expected states of traffic lights and/or variable message signs
FR2997183B1 (en) * 2012-10-24 2017-10-13 Renault Sas ROUND-POINT DETECTING METHOD FOR VEHICLE APPLICATION
DE102012110219A1 (en) 2012-10-25 2014-04-30 Continental Teves Ag & Co. Ohg Method and device for detecting marked danger and / or construction sites in the area of roadways
KR101417432B1 (en) * 2012-11-27 2014-07-08 현대자동차주식회사 Apparatus for generating road information using moving information of vehicle
US9816823B2 (en) * 2013-03-15 2017-11-14 Hewlett Packard Enterprise Development Lp Updating road maps
DE102013207658A1 (en) * 2013-04-26 2014-10-30 Bayerische Motoren Werke Aktiengesellschaft Method for determining a lane course of a traffic lane
US9488483B2 (en) 2013-05-17 2016-11-08 Honda Motor Co., Ltd. Localization using road markings
DE102013107960B4 (en) * 2013-07-25 2020-11-05 Deutsches Zentrum für Luft- und Raumfahrt e.V. Method for updating a database as well as device and computer program
DE102013221187A1 (en) 2013-10-18 2015-04-23 Robert Bosch Gmbh Method for processing data of a digital map
US9384394B2 (en) 2013-10-31 2016-07-05 Toyota Motor Engineering & Manufacturing North America, Inc. Method for generating accurate lane level maps
US9165477B2 (en) 2013-12-06 2015-10-20 Vehicle Data Science Corporation Systems and methods for building road models, driver models, and vehicle models and making predictions therefrom
CA2891051C (en) 2014-01-06 2016-05-10 Geodigital International Inc. Determining portions of a roadway model requiring updating
US9342888B2 (en) 2014-02-08 2016-05-17 Honda Motor Co., Ltd. System and method for mapping, localization and pose correction of a vehicle based on images
DE102014204317A1 (en) * 2014-03-10 2015-09-10 Bayerische Motoren Werke Aktiengesellschaft Method and device for determining crossing parameters
JP6427908B2 (en) * 2014-03-24 2018-11-28 アイシン・エィ・ダブリュ株式会社 Map information generation system, method and program
JP6253467B2 (en) * 2014-03-24 2017-12-27 東芝アルパイン・オートモティブテクノロジー株式会社 Image processing apparatus and image processing program
US10481277B2 (en) 2014-04-09 2019-11-19 Continental Automotive Gmbh Position correction of a vehicle by referencing to objects in the surroundings
GB201407643D0 (en) 2014-04-30 2014-06-11 Tomtom Global Content Bv Improved positioning relatie to a digital map for assisted and automated driving operations
US9576478B2 (en) 2014-07-29 2017-02-21 Here Global B.V. Apparatus and associated methods for designating a traffic lane
DE102014217847A1 (en) * 2014-09-08 2016-03-10 Conti Temic Microelectronic Gmbh Driver assistance system, traffic telematics system and method for updating a digital map
DE102014015073B4 (en) * 2014-10-11 2021-02-25 Audi Ag Method for updating and / or expanding a map data set in a limited environment
DE102014220687A1 (en) * 2014-10-13 2016-04-14 Continental Automotive Gmbh Communication device for a vehicle and method for communicating
US9417076B2 (en) * 2014-12-29 2016-08-16 Here Global B.V. Total route score to measure quality of map content
CA2976344A1 (en) 2015-02-10 2016-08-18 Mobileye Vision Technologies Ltd. Sparse map for autonomous vehicle navigation
JP6658088B2 (en) * 2015-03-23 2020-03-04 株式会社豊田中央研究所 Information processing apparatus, program, and map data updating system
DE102015004067A1 (en) * 2015-03-30 2016-10-06 Technisat Digital Gmbh Providing additional map data for an off-road route with a navigation device
DE102015206605A1 (en) * 2015-04-14 2016-10-20 Continental Teves Ag & Co. Ohg Calibration and monitoring of environmental sensors with the aid of highly accurate maps
DE102015005987B4 (en) * 2015-05-08 2017-02-02 Audi Ag Method for operating a radar sensor in a motor vehicle, radar sensor and motor vehicle
DE102015210015A1 (en) 2015-06-01 2016-12-01 Robert Bosch Gmbh Method and device for determining the position of a vehicle
EP3332219B1 (en) 2015-08-03 2021-11-03 TomTom Global Content B.V. Methods and systems for generating and using localisation reference data
DE102015218809A1 (en) 2015-09-29 2017-03-30 Continental Teves Ag & Co. Ohg Method for updating an electronic map of a vehicle
DE102016200759B4 (en) 2015-11-12 2023-03-30 Volkswagen Aktiengesellschaft Method, device and processing device for controlling functions in a vehicle
US10642813B1 (en) * 2015-12-14 2020-05-05 Amazon Technologies, Inc. Techniques and systems for storage and processing of operational data
US20170186317A1 (en) 2015-12-29 2017-06-29 Tannery Creek Systems Inc. System and Method for Determining Parking Infraction
US10386480B1 (en) * 2016-02-02 2019-08-20 Waymo Llc Radar based mapping and localization for autonomous vehicles
US10223380B2 (en) * 2016-03-23 2019-03-05 Here Global B.V. Map updates from a connected vehicle fleet
DE102016204805A1 (en) * 2016-03-23 2017-09-28 Bayerische Motoren Werke Aktiengesellschaft Method and devices for providing data for a driver assistance system of a motor vehicle
US10317519B2 (en) * 2016-04-15 2019-06-11 Huawei Technologies Co., Ltd. Systems and methods for environment sensing using radar
DE102016207984B3 (en) 2016-05-10 2017-07-06 Continental Automotive Gmbh Method and device for transmitting track data collected by a moving vehicle to a central database with improved privacy
US10764713B2 (en) 2016-05-11 2020-09-01 Here Global B.V. Map based feedback loop for vehicle observation
US10184800B2 (en) 2016-05-17 2019-01-22 Here Global B.V. Sharing safety driving metrics for navigable segments
US11092446B2 (en) 2016-06-14 2021-08-17 Motional Ad Llc Route planning for an autonomous vehicle
US10309792B2 (en) 2016-06-14 2019-06-04 nuTonomy Inc. Route planning for an autonomous vehicle
DE102016210495A1 (en) * 2016-06-14 2017-12-14 Robert Bosch Gmbh Method and apparatus for creating an optimized location map and method for creating a location map for a vehicle
US10126136B2 (en) 2016-06-14 2018-11-13 nuTonomy Inc. Route planning for an autonomous vehicle
US10502577B2 (en) 2016-06-30 2019-12-10 Here Global B.V. Iterative map learning based on vehicle on-board sensor data
DE102016214868A1 (en) * 2016-08-10 2018-02-15 Volkswagen Aktiengesellschaft Method and device for creating or supplementing a map for a motor vehicle
DE102016217079A1 (en) * 2016-09-08 2018-03-08 Robert Bosch Gmbh Method and device for operating a first vehicle
FR3058515A1 (en) * 2016-10-13 2018-05-11 Valeo Schalter Und Sensoren Gmbh DEVICE AND METHOD FOR LOCATING A VEHICLE
US10473470B2 (en) 2016-10-20 2019-11-12 nuTonomy Inc. Identifying a stopping place for an autonomous vehicle
US10857994B2 (en) 2016-10-20 2020-12-08 Motional Ad Llc Identifying a stopping place for an autonomous vehicle
US10681513B2 (en) 2016-10-20 2020-06-09 nuTonomy Inc. Identifying a stopping place for an autonomous vehicle
US10331129B2 (en) 2016-10-20 2019-06-25 nuTonomy Inc. Identifying a stopping place for an autonomous vehicle
US11892311B2 (en) 2016-11-26 2024-02-06 Thinkware Corporation Image processing apparatus, image processing method, computer program and computer readable recording medium
CN108121764B (en) * 2016-11-26 2022-03-11 星克跃尔株式会社 Image processing device, image processing method, computer program, and computer-readable recording medium
DE102016224351A1 (en) * 2016-12-07 2018-06-07 Robert Bosch Gmbh Concept for testing a sensor system for detecting an occupancy state of a parking space for errors
US10317240B1 (en) * 2017-03-30 2019-06-11 Zoox, Inc. Travel data collection and publication
DE102017205939A1 (en) * 2017-04-06 2018-10-11 Knorr-Bremse Systeme für Schienenfahrzeuge GmbH Automatic generation of infrastructure data for a route network
US10761541B2 (en) 2017-04-21 2020-09-01 X Development Llc Localization with negative mapping
JP7062892B2 (en) * 2017-07-13 2022-05-09 トヨタ自動車株式会社 Dynamic map updater, dynamic map update method, dynamic map update program
US10089894B1 (en) * 2017-08-30 2018-10-02 Honeywell International Inc. Apparatus and method of implementing an augmented reality processed terrain and obstacle threat scouting service
DE102017122440A1 (en) 2017-09-27 2019-03-28 Valeo Schalter Und Sensoren Gmbh A method for locating and further developing a digital map by a motor vehicle; localization device
DE102017217299A1 (en) * 2017-09-28 2019-03-28 Continental Automotive Gmbh Method and device
DE102017223632A1 (en) * 2017-12-21 2019-06-27 Continental Automotive Gmbh System for calculating an error probability of vehicle sensor data
DE102018203237A1 (en) * 2018-03-05 2019-09-05 Bayerische Motoren Werke Aktiengesellschaft A method for providing map data of a cross-section of a vehicle, computer readable medium, system, and vehicle comprising the system
DE102018205322A1 (en) 2018-04-10 2019-10-10 Audi Ag Method and control device for detecting a malfunction of at least one environmental sensor of a motor vehicle
US11561317B2 (en) * 2018-04-11 2023-01-24 SeeScan, Inc. Geographic map updating methods and systems
US11293769B2 (en) * 2018-05-14 2022-04-05 Qualcomm Incorporated Techniques for route selection
US10943152B2 (en) 2018-05-23 2021-03-09 Here Global B.V. Method, apparatus, and system for detecting a physical divider on a road segment
US10546200B2 (en) 2018-05-23 2020-01-28 Here Global B.V. Method, apparatus, and system for detecting a physical divider on a road segment
WO2019241061A1 (en) * 2018-06-11 2019-12-19 Apex.AI, Inc. Management of data and software for autonomous vehicles
JP6680319B2 (en) * 2018-08-24 2020-04-15 アイシン・エィ・ダブリュ株式会社 Map information generation system, method and program
DE102018214971A1 (en) * 2018-09-04 2020-03-05 Robert Bosch Gmbh Method for creating a map of the surroundings of a vehicle
DE102018007658A1 (en) 2018-09-27 2019-03-07 Daimler Ag Method for providing extended environment models for at least partially autonomous vehicles, control unit for carrying out such a method, and vehicle having such a control unit
DE102018007960A1 (en) 2018-10-09 2019-03-28 Daimler Ag Method for matching map material with a detected environment of a vehicle, control device configured to carry out such a method, and vehicle having such a control device
CN109448373A (en) * 2018-11-09 2019-03-08 百度在线网络技术(北京)有限公司 Method and apparatus for generating information
US10896334B2 (en) 2018-11-28 2021-01-19 Here Global B.V. Method and system of a machine learning model for detection of physical dividers
CN111366164B (en) 2018-12-26 2023-12-29 华为技术有限公司 Positioning method and electronic equipment
DE102019207215A1 (en) * 2019-05-17 2020-11-19 Robert Bosch Gmbh Method for using a feature-based localization map for a vehicle
DE102019207212A1 (en) * 2019-05-17 2020-11-19 Robert Bosch Gmbh Method and device for processing sensor data
CN112579614A (en) * 2019-09-27 2021-03-30 北京百度网讯科技有限公司 Map data acquisition method and device, electronic equipment and medium
US11521398B2 (en) * 2019-11-26 2022-12-06 GM Global Technology Operations LLC Method and apparatus for traffic light positioning and mapping using crowd-sensed data
US20230145649A1 (en) * 2020-02-20 2023-05-11 Tomtom Global Content B.V. Using Map Change Data
CN112683284B (en) * 2020-12-01 2024-01-02 北京罗克维尔斯科技有限公司 Method and device for updating high-precision map
USD959552S1 (en) 2021-07-21 2022-08-02 Speedfind, Inc Display sign
CN113911123B (en) * 2021-12-15 2022-02-18 深圳佑驾创新科技有限公司 Road model updating method and device

Citations (54)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4891761A (en) * 1988-03-31 1990-01-02 Mets, Inc. Method for accurately updating positional information provided on a digital map
US4894662A (en) * 1982-03-01 1990-01-16 Western Atlas International, Inc. Method and system for determining position on a moving platform, such as a ship, using signals from GPS satellites
US4982332A (en) * 1988-06-27 1991-01-01 Pioneer Electronic Corporation Road data generating method for use in an on-board navigation system
US4989151A (en) * 1988-02-23 1991-01-29 Kabushiki Kaisha Toshiba Navigation apparatus and matching method for navigation
US4994971A (en) * 1985-12-06 1991-02-19 Poelstra Theo J System for setting up and keeping up-to-date datafiles for road traffic
US5146219A (en) * 1987-01-10 1992-09-08 Robert Bosch Gmbh Device for the output of safety-related road information in locating and navigating systems of land vehicles
US5164904A (en) * 1990-07-26 1992-11-17 Farradyne Systems, Inc. In-vehicle traffic congestion information system
US5243528A (en) * 1990-09-12 1993-09-07 Motorola, Inc. Land vehicle navigation apparatus with visual display
US5315295A (en) * 1991-01-18 1994-05-24 Mazda Motor Corporation Vehicle speed control system
US5332180A (en) * 1992-12-28 1994-07-26 Union Switch & Signal Inc. Traffic control system utilizing on-board vehicle information measurement apparatus
US5374933A (en) * 1993-01-05 1994-12-20 Zexel Corporation Position correction method for vehicle navigation system
US5412738A (en) * 1992-08-11 1995-05-02 Istituto Trentino Di Cultura Recognition system, particularly for recognising people
US5440484A (en) * 1992-05-15 1995-08-08 Zexel Corporation Calibration method for a relative heading sensor
US5483453A (en) * 1992-04-20 1996-01-09 Mazda Motor Corporation Navigation control system with adaptive characteristics
US5485161A (en) * 1994-11-21 1996-01-16 Trimble Navigation Limited Vehicle speed control based on GPS/MAP matching of posted speeds
US5488559A (en) * 1993-08-02 1996-01-30 Motorola, Inc. Map-matching with competing sensory positions
US5517419A (en) * 1993-07-22 1996-05-14 Synectics Corporation Advanced terrain mapping system
US5543789A (en) * 1994-06-24 1996-08-06 Shields Enterprises, Inc. Computerized navigation system
US5550924A (en) * 1993-07-07 1996-08-27 Picturetel Corporation Reduction of background noise for speech enhancement
US5566072A (en) * 1993-08-10 1996-10-15 Mitsubishi Jidosha Kogyo Kabushiki Kaisha Method and apparatus for estimating a road traffic condition and method and apparatus for controlling a vehicle running characteristic
US5596494A (en) * 1994-11-14 1997-01-21 Kuo; Shihjong Method and apparatus for acquiring digital maps
US5614895A (en) * 1993-11-19 1997-03-25 Honda Giken Kogyo Kabushiki Kaisha Map information regenerating device
US5625818A (en) * 1994-09-30 1997-04-29 Apple Computer, Inc. System for managing local database updates published to different online information services in different formats from a central platform
US5636245A (en) * 1994-08-10 1997-06-03 The Mitre Corporation Location based selective distribution of generally broadcast information
US5689252A (en) * 1994-11-04 1997-11-18 Lucent Technologies Inc. Navigation system for an automotive vehicle
US5699056A (en) * 1994-12-28 1997-12-16 Omron Corporation Traffic information system
US5731978A (en) * 1995-06-07 1998-03-24 Zexel Corporation Method and apparatus for enhancing vehicle navigation through recognition of geographical region types
US5731997A (en) * 1996-03-19 1998-03-24 Trimble Navigation Limited Method and apparatus for collecting recording and displaying data pertaining to an artifact
US5774824A (en) * 1995-08-24 1998-06-30 The Penn State Research Foundation Map-matching navigation system
US5812069A (en) * 1995-07-07 1998-09-22 Mannesmann Aktiengesellschaft Method and system for forecasting traffic flows
US5828585A (en) * 1997-01-17 1998-10-27 Delco Electronics Corporation Vehicle speed signal calibration
US5835087A (en) * 1994-11-29 1998-11-10 Herz; Frederick S. M. System for generation of object profiles for a system for customized electronic identification of desirable objects
US5844505A (en) * 1997-04-01 1998-12-01 Sony Corporation Automobile navigation system
US5848373A (en) * 1994-06-24 1998-12-08 Delorme Publishing Company Computer aided map location system
US5922036A (en) * 1996-05-28 1999-07-13 Matsushita Electric Industrial Co., Ltd. Lane detection sensor and navigation system employing the same
US5933100A (en) * 1995-12-27 1999-08-03 Mitsubishi Electric Information Technology Center America, Inc. Automobile navigation system with dynamic traffic data
US5948042A (en) * 1995-07-03 1999-09-07 Mannesmann Aktiengesellschaft Method and system for updating digital road maps
US5951620A (en) * 1996-01-26 1999-09-14 Navigation Technologies Corporation System and method for distributing information for storage media
US5961571A (en) * 1994-12-27 1999-10-05 Siemens Corporated Research, Inc Method and apparatus for automatically tracking the location of vehicles
US5968109A (en) * 1996-10-25 1999-10-19 Navigation Technologies Corporation System and method for use and storage of geographic data on physical media
US5999878A (en) * 1997-04-11 1999-12-07 Navigation Technologies Corp. System and method for acquiring geographic data for forming a digital database of road geometry in a geographic region
US6006161A (en) * 1996-08-02 1999-12-21 Aisin Aw Co., Ltd. Land vehicle navigation system with multi-screen mode selectivity
US6047234A (en) * 1997-10-16 2000-04-04 Navigation Technologies Corporation System and method for updating, enhancing or refining a geographic database using feedback
US6061625A (en) * 1996-02-08 2000-05-09 Mannesmann Ag Process for obtaining traffic data
US6067500A (en) * 1995-08-14 2000-05-23 Aisin Aw Co., Ltd. Navigation system
US6072396A (en) * 1994-12-30 2000-06-06 Advanced Business Sciences Apparatus and method for continuous electronic monitoring and tracking of individuals
US6144916A (en) * 1992-05-15 2000-11-07 Micron Communications, Inc. Itinerary monitoring system for storing a plurality of itinerary data points
US6154152A (en) * 1997-10-16 2000-11-28 Toyota Jidosha Kabushiki Kaisha Road data maintenance system and on-vehicle terminal apparatus compatible therewith
US6169515B1 (en) * 1994-09-01 2001-01-02 British Telecommunications Public Limited Company Navigation information system
US6173231B1 (en) * 2000-01-31 2001-01-09 Navigation Technologies Corp. Method and system for collecting data concerning thermal properties of roads for a geographic database and use thereof in a vehicle safety system
US6178374B1 (en) * 1996-10-10 2001-01-23 Mannesmann Ag Method and device for transmitting data on traffic assessment
US6199045B1 (en) * 1996-08-15 2001-03-06 Spatial Adventures, Inc. Method and apparatus for providing position-related information to mobile recipients
US6199013B1 (en) * 1997-07-15 2001-03-06 Navigation Technologies Corp. Maneuver generation program and method
US6480783B1 (en) * 2000-03-17 2002-11-12 Makor Issues And Rights Ltd. Real time vehicle guidance and forecasting system under traffic jam conditions

Family Cites Families (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2696169B2 (en) * 1987-12-11 1998-01-14 マツダ株式会社 Navigation device
JPH07119617B2 (en) * 1988-07-05 1995-12-20 マツダ株式会社 Vehicle navigation system
JPH02122214A (en) * 1988-10-31 1990-05-09 Nippon Telegr & Teleph Corp <Ntt> Sensor correcting system for moving body navigation device
ES2049400T3 (en) * 1989-01-06 1994-04-16 Teleatlas International B V PROCEDURE TO ORGANIZE AND UPDATE FILE FOR ROAD TRAFFIC.
JPH03237482A (en) * 1990-02-15 1991-10-23 Daihatsu Motor Co Ltd Navigation device
US5272638A (en) * 1991-05-31 1993-12-21 Texas Instruments Incorporated Systems and methods for planning the scheduling travel routes
JP2778374B2 (en) * 1992-09-07 1998-07-23 日産自動車株式会社 Vehicle navigation system
JPH06180235A (en) * 1992-12-14 1994-06-28 Pioneer Electron Corp Navigation apparatus
JP3269156B2 (en) * 1993-01-14 2002-03-25 住友電気工業株式会社 Road map data collection device
US5504482A (en) * 1993-06-11 1996-04-02 Rockwell International Corporation Automobile navigation guidance, control and safety system
JPH07294274A (en) * 1994-04-28 1995-11-10 Nec Home Electron Ltd Navigation system
JPH08101039A (en) * 1994-09-30 1996-04-16 Oki Electric Ind Co Ltd Navigation device
ES2126210T3 (en) * 1994-11-28 1999-03-16 Mannesmann Ag PROCEDURE FOR THE REDUCTION OF A QUANTITY OF DATA TO BE TRANSMITTED FROM VEHICLES FROM A FLEET OF RANDOM SAMPLING VEHICLES.
JP3472896B2 (en) * 1994-12-28 2003-12-02 オムロン株式会社 Traffic information system
JPH08247775A (en) * 1995-03-15 1996-09-27 Toshiba Corp Device and method for identification of self position of moving body
JPH0933267A (en) * 1995-07-18 1997-02-07 Matsushita Electric Ind Co Ltd Traveling-position indicator
US5699255A (en) * 1995-10-18 1997-12-16 Trimble Navigation Limited Map transmission for in-vehicle navigation system with dynamic scale/detail adjustment
JP3413318B2 (en) * 1995-12-25 2003-06-03 トヨタ自動車株式会社 Route information providing method and route information providing system
JP3008839B2 (en) * 1996-01-08 2000-02-14 ソニー株式会社 Navigation device
JP3557776B2 (en) * 1996-03-08 2004-08-25 日産自動車株式会社 Route guidance device for vehicles
JP2707237B2 (en) * 1996-04-15 1998-01-28 マツダ株式会社 Vehicle navigation system
JP3760958B2 (en) * 1996-04-24 2006-03-29 アイシン・エィ・ダブリュ株式会社 Navigation device
WO1998054682A1 (en) 1997-05-30 1998-12-03 Booth David S Generation and delivery of travel-related, location-sensitive information
US6671615B1 (en) * 2000-05-02 2003-12-30 Navigation Technologies Corp. Navigation system with sign assistance

Patent Citations (56)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4894662A (en) * 1982-03-01 1990-01-16 Western Atlas International, Inc. Method and system for determining position on a moving platform, such as a ship, using signals from GPS satellites
US4994971A (en) * 1985-12-06 1991-02-19 Poelstra Theo J System for setting up and keeping up-to-date datafiles for road traffic
US5146219A (en) * 1987-01-10 1992-09-08 Robert Bosch Gmbh Device for the output of safety-related road information in locating and navigating systems of land vehicles
US4989151A (en) * 1988-02-23 1991-01-29 Kabushiki Kaisha Toshiba Navigation apparatus and matching method for navigation
US4891761A (en) * 1988-03-31 1990-01-02 Mets, Inc. Method for accurately updating positional information provided on a digital map
US4982332A (en) * 1988-06-27 1991-01-01 Pioneer Electronic Corporation Road data generating method for use in an on-board navigation system
US5164904A (en) * 1990-07-26 1992-11-17 Farradyne Systems, Inc. In-vehicle traffic congestion information system
US5243528A (en) * 1990-09-12 1993-09-07 Motorola, Inc. Land vehicle navigation apparatus with visual display
US5315295A (en) * 1991-01-18 1994-05-24 Mazda Motor Corporation Vehicle speed control system
US5483453A (en) * 1992-04-20 1996-01-09 Mazda Motor Corporation Navigation control system with adaptive characteristics
US5440484A (en) * 1992-05-15 1995-08-08 Zexel Corporation Calibration method for a relative heading sensor
US6144916A (en) * 1992-05-15 2000-11-07 Micron Communications, Inc. Itinerary monitoring system for storing a plurality of itinerary data points
US5412738A (en) * 1992-08-11 1995-05-02 Istituto Trentino Di Cultura Recognition system, particularly for recognising people
US5332180A (en) * 1992-12-28 1994-07-26 Union Switch & Signal Inc. Traffic control system utilizing on-board vehicle information measurement apparatus
US5374933A (en) * 1993-01-05 1994-12-20 Zexel Corporation Position correction method for vehicle navigation system
US5550924A (en) * 1993-07-07 1996-08-27 Picturetel Corporation Reduction of background noise for speech enhancement
US5517419A (en) * 1993-07-22 1996-05-14 Synectics Corporation Advanced terrain mapping system
US5488559A (en) * 1993-08-02 1996-01-30 Motorola, Inc. Map-matching with competing sensory positions
US5566072A (en) * 1993-08-10 1996-10-15 Mitsubishi Jidosha Kogyo Kabushiki Kaisha Method and apparatus for estimating a road traffic condition and method and apparatus for controlling a vehicle running characteristic
US5614895A (en) * 1993-11-19 1997-03-25 Honda Giken Kogyo Kabushiki Kaisha Map information regenerating device
US5543789A (en) * 1994-06-24 1996-08-06 Shields Enterprises, Inc. Computerized navigation system
US5848373A (en) * 1994-06-24 1998-12-08 Delorme Publishing Company Computer aided map location system
US5636245A (en) * 1994-08-10 1997-06-03 The Mitre Corporation Location based selective distribution of generally broadcast information
US6169515B1 (en) * 1994-09-01 2001-01-02 British Telecommunications Public Limited Company Navigation information system
US5625818A (en) * 1994-09-30 1997-04-29 Apple Computer, Inc. System for managing local database updates published to different online information services in different formats from a central platform
US5689252A (en) * 1994-11-04 1997-11-18 Lucent Technologies Inc. Navigation system for an automotive vehicle
US5596494A (en) * 1994-11-14 1997-01-21 Kuo; Shihjong Method and apparatus for acquiring digital maps
US5485161A (en) * 1994-11-21 1996-01-16 Trimble Navigation Limited Vehicle speed control based on GPS/MAP matching of posted speeds
US5835087A (en) * 1994-11-29 1998-11-10 Herz; Frederick S. M. System for generation of object profiles for a system for customized electronic identification of desirable objects
US5961571A (en) * 1994-12-27 1999-10-05 Siemens Corporated Research, Inc Method and apparatus for automatically tracking the location of vehicles
US5699056A (en) * 1994-12-28 1997-12-16 Omron Corporation Traffic information system
US6072396A (en) * 1994-12-30 2000-06-06 Advanced Business Sciences Apparatus and method for continuous electronic monitoring and tracking of individuals
US5731978A (en) * 1995-06-07 1998-03-24 Zexel Corporation Method and apparatus for enhancing vehicle navigation through recognition of geographical region types
US5948042A (en) * 1995-07-03 1999-09-07 Mannesmann Aktiengesellschaft Method and system for updating digital road maps
US5812069A (en) * 1995-07-07 1998-09-22 Mannesmann Aktiengesellschaft Method and system for forecasting traffic flows
US6067500A (en) * 1995-08-14 2000-05-23 Aisin Aw Co., Ltd. Navigation system
US5774824A (en) * 1995-08-24 1998-06-30 The Penn State Research Foundation Map-matching navigation system
US5933100A (en) * 1995-12-27 1999-08-03 Mitsubishi Electric Information Technology Center America, Inc. Automobile navigation system with dynamic traffic data
US5951620A (en) * 1996-01-26 1999-09-14 Navigation Technologies Corporation System and method for distributing information for storage media
US6061625A (en) * 1996-02-08 2000-05-09 Mannesmann Ag Process for obtaining traffic data
US5731997A (en) * 1996-03-19 1998-03-24 Trimble Navigation Limited Method and apparatus for collecting recording and displaying data pertaining to an artifact
US5922036A (en) * 1996-05-28 1999-07-13 Matsushita Electric Industrial Co., Ltd. Lane detection sensor and navigation system employing the same
US6006161A (en) * 1996-08-02 1999-12-21 Aisin Aw Co., Ltd. Land vehicle navigation system with multi-screen mode selectivity
US6199045B1 (en) * 1996-08-15 2001-03-06 Spatial Adventures, Inc. Method and apparatus for providing position-related information to mobile recipients
US6178374B1 (en) * 1996-10-10 2001-01-23 Mannesmann Ag Method and device for transmitting data on traffic assessment
US5968109A (en) * 1996-10-25 1999-10-19 Navigation Technologies Corporation System and method for use and storage of geographic data on physical media
US5828585A (en) * 1997-01-17 1998-10-27 Delco Electronics Corporation Vehicle speed signal calibration
US5844505A (en) * 1997-04-01 1998-12-01 Sony Corporation Automobile navigation system
US5999878A (en) * 1997-04-11 1999-12-07 Navigation Technologies Corp. System and method for acquiring geographic data for forming a digital database of road geometry in a geographic region
US6199013B1 (en) * 1997-07-15 2001-03-06 Navigation Technologies Corp. Maneuver generation program and method
US6154152A (en) * 1997-10-16 2000-11-28 Toyota Jidosha Kabushiki Kaisha Road data maintenance system and on-vehicle terminal apparatus compatible therewith
US6047234A (en) * 1997-10-16 2000-04-04 Navigation Technologies Corporation System and method for updating, enhancing or refining a geographic database using feedback
US6516267B1 (en) * 1997-10-16 2003-02-04 Navigation Technologies Corporation System and method for updating, enhancing or refining a geographic database using feedback
US6853913B2 (en) * 1997-10-16 2005-02-08 Navteq North America, Llc System and method for updating, enhancing, or refining a geographic database using feedback
US6173231B1 (en) * 2000-01-31 2001-01-09 Navigation Technologies Corp. Method and system for collecting data concerning thermal properties of roads for a geographic database and use thereof in a vehicle safety system
US6480783B1 (en) * 2000-03-17 2002-11-12 Makor Issues And Rights Ltd. Real time vehicle guidance and forecasting system under traffic jam conditions

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
A sonar-based mapping and navigation system; Elfes, A.; Robotics and Automation. Proceedings. 1986 IEEE International Conference on; Volume: 3; Digital Object Identifier: 10.1109/ROBOT.1986.1087534; Publication Year: 1986 , Page(s): 1151 - 1156 *
Integrating geographic analysis with image databases; Pullar, D.; Sun, S.; Reeves, R.; TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications., Proceedings of IEEE; Volume: 1; Digital Object Identifier: 10.1109/TENCON.1997.647323; Publication Year: 1997 , Page(s): 327 - 331 vol.1 *
Real-time routing in mobile networks using GPS and GIS techniques; Karimi, H.A.; Krishnamurthy, P.; System Sciences, 2001. Proceedings of the 34th Annual Hawaii International Conference on; Jan 3-6 2001 Page(s):11+ *
Use of map data information in an on-board intersection violation detection system; Pierowicz, J.A.; Digital Avionics Systems Conference, 1998. Proceedings., 17th DASC. The AIAA/IEEE/SAE; Volume: 2; Digital Object Identifier: 10.1109/DASC.1998.739873; Publication Year: 1998 , Page(s): I25/1 - I25/6 vol.2 *

Cited By (105)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8407065B2 (en) * 2002-05-07 2013-03-26 Polyremedy, Inc. Wound care treatment service using automatic wound dressing fabricator
US20090204423A1 (en) * 2002-05-07 2009-08-13 Polyremedy, Inc. Wound Care Treatment Service Using Automatic Wound Dressing Fabricator
US20040015115A1 (en) * 2002-05-07 2004-01-22 Dmitriy Sinyagin Method for treating wound, dressing for use therewith and apparatus and system for fabricating dressing
US7910789B2 (en) 2002-05-07 2011-03-22 Polyremedy, Inc. Method for treating wound, dressing for use therewith and apparatus and system for fabricating dressing
US20040088110A1 (en) * 2002-08-26 2004-05-06 Keizo Suzuki Method and apparatus for displaying navigation information
US7239963B2 (en) * 2002-08-26 2007-07-03 Alpine Electronics, Inc. Method and apparatus for displaying navigation information
US20090020554A1 (en) * 2004-07-16 2009-01-22 Polyremedy Inc. Wound dressing and apparatus for forming same
US8234842B2 (en) 2004-07-16 2012-08-07 Polyremedy, Inc. Wound dressing and apparatus for forming same
US20070035563A1 (en) * 2005-08-12 2007-02-15 The Board Of Trustees Of Michigan State University Augmented reality spatial interaction and navigational system
WO2007037986A3 (en) * 2005-09-21 2007-11-01 Boeing Co Creation of optimized terrain databases
US20070124064A1 (en) * 2005-11-30 2007-05-31 Fujitsu Limited Map information updating system, central apparatus, map information updating method and recording medium
US10878646B2 (en) 2005-12-08 2020-12-29 Smartdrive Systems, Inc. Vehicle event recorder systems
US9226004B1 (en) 2005-12-08 2015-12-29 Smartdrive Systems, Inc. Memory management in event recording systems
US9633318B2 (en) 2005-12-08 2017-04-25 Smartdrive Systems, Inc. Vehicle event recorder systems
US8521425B2 (en) * 2006-03-14 2013-08-27 Pioneer Corporation Position registering apparatus, route retrieving apparatus, position registering method, position registering program, and recording medium
US20090030607A1 (en) * 2006-03-14 2009-01-29 Pioneer Corporation Position registering apparatus, route retrieving apparatus, position registering method, position registering program, and recording medium
US9566910B2 (en) 2006-03-16 2017-02-14 Smartdrive Systems, Inc. Vehicle event recorder systems and networks having integrated cellular wireless communications systems
US9208129B2 (en) 2006-03-16 2015-12-08 Smartdrive Systems, Inc. Vehicle event recorder systems and networks having integrated cellular wireless communications systems
US9691195B2 (en) 2006-03-16 2017-06-27 Smartdrive Systems, Inc. Vehicle event recorder systems and networks having integrated cellular wireless communications systems
US9545881B2 (en) 2006-03-16 2017-01-17 Smartdrive Systems, Inc. Vehicle event recorder systems and networks having integrated cellular wireless communications systems
US9201842B2 (en) 2006-03-16 2015-12-01 Smartdrive Systems, Inc. Vehicle event recorder systems and networks having integrated cellular wireless communications systems
US9942526B2 (en) 2006-03-16 2018-04-10 Smartdrive Systems, Inc. Vehicle event recorders with integrated web server
US9472029B2 (en) 2006-03-16 2016-10-18 Smartdrive Systems, Inc. Vehicle event recorder systems and networks having integrated cellular wireless communications systems
US9402060B2 (en) 2006-03-16 2016-07-26 Smartdrive Systems, Inc. Vehicle event recorders with integrated web server
US10404951B2 (en) 2006-03-16 2019-09-03 Smartdrive Systems, Inc. Vehicle event recorders with integrated web server
US20080004761A1 (en) * 2006-06-30 2008-01-03 Denso Corporation Control information storage apparatus and program for same
US7899589B2 (en) 2006-06-30 2011-03-01 Denso Corporation Control information storage apparatus and program for same
US20080018497A1 (en) * 2006-07-18 2008-01-24 John Edward Farnham Integrated data logging unit
US20080082254A1 (en) * 2006-10-02 2008-04-03 Yka Huhtala Route-assisted GPS location sensing via mobile device
US10053032B2 (en) 2006-11-07 2018-08-21 Smartdrive Systems, Inc. Power management systems for automotive video event recorders
US9761067B2 (en) 2006-11-07 2017-09-12 Smartdrive Systems, Inc. Vehicle operator performance history recording, scoring and reporting systems
US9554080B2 (en) 2006-11-07 2017-01-24 Smartdrive Systems, Inc. Power management systems for automotive video event recorders
US10682969B2 (en) 2006-11-07 2020-06-16 Smartdrive Systems, Inc. Power management systems for automotive video event recorders
US10339732B2 (en) 2006-11-07 2019-07-02 Smartdrive Systems, Inc. Vehicle operator performance history recording, scoring and reporting systems
US9738156B2 (en) 2006-11-09 2017-08-22 Smartdrive Systems, Inc. Vehicle exception event management systems
US11623517B2 (en) 2006-11-09 2023-04-11 SmartDriven Systems, Inc. Vehicle exception event management systems
US10471828B2 (en) 2006-11-09 2019-11-12 Smartdrive Systems, Inc. Vehicle exception event management systems
US20080147305A1 (en) * 2006-12-07 2008-06-19 Hitachi, Ltd. Car Information System, Map Server And On-Board System
US8180569B2 (en) * 2006-12-07 2012-05-15 Hitachi Ltd. Car information system, map server and on-board system
US20080167594A1 (en) * 2007-01-10 2008-07-10 Oleg Siniaguine Wound dressing with controllable permeability
US8237007B2 (en) 2007-01-10 2012-08-07 Polyremedy, Inc. Wound dressing with controllable permeability
US20080177738A1 (en) * 2007-01-22 2008-07-24 Fujitsu Limited. Map data processing method and apparatus
US20100088021A1 (en) * 2007-04-26 2010-04-08 Marcus Rishi Leonard Viner Collection methods and devices
US20100026804A1 (en) * 2007-04-27 2010-02-04 Aisin Aw Co., Ltd. Route guidance systems, methods, and programs
US9183679B2 (en) 2007-05-08 2015-11-10 Smartdrive Systems, Inc. Distributed vehicle event recorder systems having a portable memory data transfer system
US9679424B2 (en) 2007-05-08 2017-06-13 Smartdrive Systems, Inc. Distributed vehicle event recorder systems having a portable memory data transfer system
US8442791B2 (en) * 2007-08-29 2013-05-14 Continental Teves Ag & Co. Ohg Correction of a vehicle position by means of landmarks
US20110161032A1 (en) * 2007-08-29 2011-06-30 Continental Teves Ag & Co.Ohg Correction of a vehicle position by means of landmarks
US9043138B2 (en) 2007-09-07 2015-05-26 Green Driver, Inc. System and method for automated updating of map information
US10311724B2 (en) 2007-09-07 2019-06-04 Connected Signals, Inc. Network security system with application for driver safety system
US20130131980A1 (en) * 2007-09-07 2013-05-23 On Time Systems, Inc. Resolving gps ambiguity in electronic maps
US10083607B2 (en) 2007-09-07 2018-09-25 Green Driver, Inc. Driver safety enhancement using intelligent traffic signals and GPS
US20090138497A1 (en) * 2007-11-06 2009-05-28 Walter Bruno Zavoli Method and system for the use of probe data from multiple vehicles to detect real world changes for use in updating a map
US20090216442A1 (en) * 2008-02-26 2009-08-27 Nokia Corporation Method, apparatus and computer program product for map feature detection
WO2009106678A1 (en) * 2008-02-26 2009-09-03 Nokia Corporation Method, apparatus and computer program product for map feature detection
US20100241447A1 (en) * 2008-04-25 2010-09-23 Polyremedy, Inc. Customization of wound dressing using rule-based algorithm
US8237009B2 (en) 2008-06-30 2012-08-07 Polyremedy, Inc. Custom patterned wound dressings having patterned fluid flow barriers and methods of manufacturing and using same
US20090326429A1 (en) * 2008-06-30 2009-12-31 Oleg Siniaguine Custom Patterned Wound Dressings Having Patterned Fluid Flow Barriers and Methods of Manufacturing and Using Same
US8247634B2 (en) 2008-08-22 2012-08-21 Polyremedy, Inc. Expansion units for attachment to custom patterned wound dressings and custom patterned wound dressings adapted to interface with same
US20100049148A1 (en) * 2008-08-22 2010-02-25 Oleg Siniaguine Expansion Units for Attachment to Custom Patterned Wound Dressings and Custom Patterned Wound Dressings Adapted to Interface With Same
US8949020B2 (en) * 2009-03-31 2015-02-03 Thinkwaresystems Corp. Map-matching apparatus using planar data of road, and method for same
US20120101718A1 (en) * 2009-03-31 2012-04-26 Thinkwaresystems Corp Map-matching apparatus using planar data of road, and method for same
US10198942B2 (en) 2009-08-11 2019-02-05 Connected Signals, Inc. Traffic routing display system with multiple signal lookahead
CN105117396A (en) * 2009-09-15 2015-12-02 美国结构数据有限公司 Processes and systems for collaborative manipulation of data
US10678825B2 (en) 2009-09-15 2020-06-09 Factual Inc. Processes and systems for collaborative manipulation of data
WO2011155929A1 (en) * 2010-06-09 2011-12-15 Tele Atlas North America Inc. Systems and methods for processing information related to a geographic region
US20120050489A1 (en) * 2010-08-30 2012-03-01 Honda Motor Co., Ltd. Road departure warning system
US9077958B2 (en) * 2010-08-30 2015-07-07 Honda Motor Co., Ltd. Road departure warning system
US10678776B1 (en) * 2010-10-06 2020-06-09 Google Llc Automated identification of anomalous map data
US8676506B1 (en) 2011-11-15 2014-03-18 Google Inc. Systems and methods for identifying missing signage
US9240080B2 (en) * 2012-04-17 2016-01-19 Lytx, Inc. Server request for downloaded information from a vehicle-based monitor
US20140236382A1 (en) * 2012-04-17 2014-08-21 Lytx, Inc. Server request for downloaded information from a vehicle-based monitor
US9240079B2 (en) 2012-04-17 2016-01-19 Lytx, Inc. Triggering a specialized data collection mode
US9728228B2 (en) 2012-08-10 2017-08-08 Smartdrive Systems, Inc. Vehicle event playback apparatus and methods
US9501878B2 (en) 2013-10-16 2016-11-22 Smartdrive Systems, Inc. Vehicle event playback apparatus and methods
US10019858B2 (en) 2013-10-16 2018-07-10 Smartdrive Systems, Inc. Vehicle event playback apparatus and methods
US10818112B2 (en) 2013-10-16 2020-10-27 Smartdrive Systems, Inc. Vehicle event playback apparatus and methods
US11260878B2 (en) 2013-11-11 2022-03-01 Smartdrive Systems, Inc. Vehicle fuel consumption monitor and feedback systems
US9610955B2 (en) 2013-11-11 2017-04-04 Smartdrive Systems, Inc. Vehicle fuel consumption monitor and feedback systems
US11884255B2 (en) 2013-11-11 2024-01-30 Smartdrive Systems, Inc. Vehicle fuel consumption monitor and feedback systems
US10497187B2 (en) 2014-02-21 2019-12-03 Smartdrive Systems, Inc. System and method to detect execution of driving maneuvers
US10249105B2 (en) 2014-02-21 2019-04-02 Smartdrive Systems, Inc. System and method to detect execution of driving maneuvers
US9594371B1 (en) 2014-02-21 2017-03-14 Smartdrive Systems, Inc. System and method to detect execution of driving maneuvers
US11734964B2 (en) 2014-02-21 2023-08-22 Smartdrive Systems, Inc. System and method to detect execution of driving maneuvers
US11250649B2 (en) 2014-02-21 2022-02-15 Smartdrive Systems, Inc. System and method to detect execution of driving maneuvers
US9780960B2 (en) * 2014-09-25 2017-10-03 Dell Products, L.P. Event notifications in a shared infrastructure environment
US20160094359A1 (en) * 2014-09-25 2016-03-31 Dell Products, L.P. Event notifications in a shared infrastructure environment
US9663127B2 (en) 2014-10-28 2017-05-30 Smartdrive Systems, Inc. Rail vehicle event detection and recording system
US11069257B2 (en) 2014-11-13 2021-07-20 Smartdrive Systems, Inc. System and method for detecting a vehicle event and generating review criteria
US10930093B2 (en) 2015-04-01 2021-02-23 Smartdrive Systems, Inc. Vehicle event recording system and method
US20180357839A1 (en) * 2015-06-30 2018-12-13 Robert Bosch Gmbh Method and device for uploading data of a motor vehicle
US10872477B2 (en) * 2015-06-30 2020-12-22 Robert Bosch Gmbh Method and device for uploading data of a motor vehicle
US20180239032A1 (en) * 2015-08-11 2018-08-23 Continental Automotive Gmbh System and method for precision vehicle positioning
US10970317B2 (en) 2015-08-11 2021-04-06 Continental Automotive Gmbh System and method of a two-step object data processing by a vehicle and a server database for generating, updating and delivering a precision road property database
US11085774B2 (en) 2015-08-11 2021-08-10 Continental Automotive Gmbh System and method of matching of road data objects for generating and updating a precision road database
CN107851125A (en) * 2015-08-11 2018-03-27 大陆汽车有限责任公司 The processing of two step object datas is carried out by vehicle and server database to generate, update and transmit the system and method in accurate road characteristic data storehouse
US20180246907A1 (en) * 2015-08-11 2018-08-30 Continental Automotive Gmbh System and method of a two-step object data processing by a vehicle and a server database for generating, updating and delivering a precision road property database
CN106568453A (en) * 2015-11-13 2017-04-19 深圳市步科电气有限公司 AGV automatic path exploring system, and method thereof
EP3236212B1 (en) * 2016-04-22 2023-01-25 Volvo Car Corporation Method for generating navigation data and a navigation device for performing the method
US11248925B2 (en) * 2016-07-28 2022-02-15 Toyota Motor Engineering & Manufacturing North America, Inc. Augmented road line detection and display system
US20180031384A1 (en) * 2016-07-28 2018-02-01 Toyota Motor Engineering & Manufacturing North America, Inc. Augmented road line detection and display system
DE102018221740A1 (en) * 2018-12-14 2020-06-18 Volkswagen Aktiengesellschaft Method, device and computer program for a vehicle
WO2020120696A1 (en) 2018-12-14 2020-06-18 Volkswagen Aktiengesellschaft Method, device, and computer program for a vehicle
CN109766405A (en) * 2019-03-06 2019-05-17 路特迩科技(杭州)有限公司 Traffic and travel information service system and method based on electronic map
DE102020210515A1 (en) 2020-08-19 2022-03-24 Volkswagen Aktiengesellschaft Method for checking detected changes for an environment model of a digital environment map

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US6047234A (en) 2000-04-04
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