Vehicle-based anonymization of positioning vehicle data

Abstract

The present disclosure provides vehicle-based anonymization of positioned vehicle data. A method includes defining incremental coordinates indicative of positional relationships between a vehicle and different locations separate from the vehicle; converting the absolute coordinates of the vehicle into fuzzy coordinates having hash coordinates associated with the different positions and the incremental coordinates; retrieving a map tile associated with the fuzzy coordinate from a plurality of map tiles; and outputting a message including anonymous location data as a location of the vehicle and defined by the map tile and the incremental coordinates.

Description

Technical Field

[0001] This disclosure generally relates to the generation and transmission of vehicle data, and more specifically to the generation of anonymous vehicle data for transmission. Background Technology

[0002] The statements in this section are provided only as background information in connection with this disclosure and may not constitute prior art.

[0003] Vehicle connectivity allows vehicle systems (e.g., advanced driver assistance systems (ADAS)) to share data, such as, but not limited to, speed, heading, and / or position. Vehicle data can be used for a variety of applications, such as monitoring vehicle operation and / or updating algorithms / models adopted by vehicle systems. Summary of the Invention

[0004] This section provides a general overview of this disclosure and is not a full disclosure of its entire scope or all its features.

[0005] In one form, this disclosure relates to a method comprising: defining incremental coordinates by a vehicle system indicating a positional relationship between a vehicle and different locations from which the vehicle is separated; converting the absolute coordinates of the vehicle by the vehicle system into fuzzy coordinates having hash coordinates associated with the different locations and the incremental coordinates; retrieving map tiles associated with the fuzzy coordinates from a plurality of map tiles by the vehicle system; and outputting a message by the vehicle system including anonymous location data as the location of the vehicle and defined by the map tiles and the incremental coordinates.

[0006] In one form, this disclosure relates to a system for a vehicle. The system includes one or more computing devices configured to: define incremental coordinates indicating the positional relationship between the vehicle and different locations from which the vehicle is separated; convert the absolute coordinates of the vehicle into fuzzy coordinates having hash coordinates associated with the different locations and the incremental coordinates; retrieve map tiles associated with the fuzzy coordinates from a plurality of map tiles; and output a message including anonymous location data as the location of the vehicle and defined by the map tiles and the incremental coordinates.

[0007] In one form, this disclosure relates to a method comprising: obtaining absolute coordinates of a vehicle by a vehicle system using at least one location signal from a satellite network; identifying different locations separated from the vehicle by the vehicle system using the absolute coordinates; defining incremental coordinates by the vehicle system indicating the positional relationship between the vehicle and the different locations; converting the absolute coordinates of the vehicle into fuzzy coordinates having hash coordinates associated with the different locations and the incremental coordinates by the vehicle system; retrieving map tiles associated with the fuzzy coordinates from a plurality of map tiles by the vehicle system; and outputting a message comprising anonymous location data defined by the map tiles and the incremental coordinates as the location of the vehicle by the vehicle system.

[0008] Further applicability will become apparent from the description provided herein. It should be understood that the descriptions and specific examples are intended for illustrative purposes only and are not intended to limit the scope of this disclosure. Attached Figure Description

[0009] To better understand this disclosure, various forms of the disclosure will now be described by way of example with reference to the accompanying drawings, in which:

[0010] Figure 1 This is an example block diagram of a vehicle with a vehicle location anonymization module and ADAS, wherein the ADAS is configured to communicate with an ADAS server using anonymous data;

[0011] Figure 2 This is an example flowchart of the coordinate anonymization process in the vehicle location anonymization module; and

[0012] Figure 3 The coordinate anonymization of the vehicle's absolute coordinates is shown.

[0013] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of this disclosure. Detailed Implementation

[0014] Detailed embodiments are disclosed herein as requested; however, it should be understood that the disclosed embodiments are merely exemplary, and this disclosure may be embodied in different and alternative forms. The drawings are not necessarily drawn to scale; some features may be enlarged or minimized to show details of specific components. Therefore, the specific structural and functional details disclosed herein should not be construed as limiting, but rather serve only as a representative basis for teaching those skilled in the art to employ the features of this disclosure in different ways.

[0015] Vehicle data may contain personally identifiable information, such as, but not limited to, the vehicle's absolute location and / or characteristics of the road or surrounding environment that can be used to identify the vehicle's location. Given, for example, data governance proposals and / or other strategies, the collection and potential dissemination of personally identifiable information can present challenges. This can make it difficult to obtain data to evaluate and / or modify, for example, ADAS features.

[0016] In some applications, personally identifiable information can be slightly modified to protect privacy while providing high-fidelity vehicle data. In a non-limiting example, visual data (such as images with known landmarks) might be blurred to prevent identification of the vehicle's surroundings. However, certain data (such as absolute coordinates) can provide useful information when analyzing the actions of vehicle systems, such as lane position control provided by ADAS.

[0017] This disclosure relates to a system / method for providing anonymized location data for a vehicle, which can be used to monitor vehicle operation, update algorithms / models adopted by vehicle systems, and perform other actions. In a non-limiting example, the system of this disclosure converts the absolute coordinates of the vehicle into fuzzy coordinates having hash coordinates associated with a unique location unrelated to the vehicle and incremental coordinates indicating the positional relationship between the vehicle and the unique location. The system also retrieves map tiles associated with the fuzzy coordinates from a plurality of map tiles and uses the map tiles and incremental coordinates to define anonymized location data, which serves as the vehicle's location. The system / method provides anonymity by converting absolute coordinates into location data that cannot be tracked by the vehicle, while providing general location information for analyzing other vehicle data related to vehicle control (e.g., data related to lane position control or other ADAS features).

[0018] refer to Figure 1In some aspects, vehicle 100 (as part of its vehicle system 101) includes an advanced driver assistance system (ADAS) 102 that provides one or more driver assistance features, such as, but not limited to, a blind spot monitor 104, a driving monitor 106, adaptive cruise control 108, lane driving control 110, and / or driving control 112. The blind spot monitor 104 is configured to detect potential objects in areas with blind spots (e.g., side blind spots) and, if an object is detected, to provide an alert to the driver (e.g., the alert may include sound and / or lighting). The driving monitor 106 is configured to detect whether vehicle 100 is leaving its driving lane and / or objects that may potentially interfere with vehicle 100's path. The adaptive cruise control 108 is configured to monitor the distance between vehicle 100 and a guide vehicle in front of vehicle 100 and adjust vehicle 100's speed to control the distance between vehicle 100 and the guide vehicle. Lane driving control 110 is configured to control the lateral position of vehicle 100, causing vehicle 100 to remain within its driving lane. Driving control 112 is configured to provide partial to fully autonomous control of driving maneuvers to move vehicle 100 to a desired position. In a non-limiting example, when available, driving control 112 is configured to monitor the surrounding environment and perform various driving maneuvers such as controlling speed, changing lanes, turning, and / or following traffic lights. Various driving assistance features can be selected by the driver and operate together or separately.

[0019] ADAS system 102 also includes one or more sensors 114 to receive information about the surrounding environment of vehicle 100. In a non-limiting example, sensor 114 may include one or more of a camera, ultrasonic sensor, radar system, and / or lidar system. Sensor 114 can be used to allow vehicle 100 to image its surrounding environment. For example, a camera may be mounted on the front, rear, and sides of vehicle 100 to capture visual images of the surrounding environment of vehicle 100. The images can be used to detect, for example, the positions of pedestrians, traffic lights / signs, and / or other vehicles.

[0020] Although shown as separate features / controls, the driver assistance features of ADAS 102 can be implemented using one or more controllers configured to perform one or more driver assistance features (e.g., blind spot monitor 104, driver monitoring 106, adaptive cruise control 108, lane control 110, and / or driver control 112). As the automation control of vehicle 100 increases, ADAS 102 can be configured with advanced algorithms and / or artificial intelligence (AI) models to process data from sensor 114 to identify and predict the trajectory of moving objects, and, where applicable, perform driving operations (e.g., adjusting speed, moving to a different lane, adjusting the lateral position of vehicle 100 within the driving lane, and / or stopping the vehicle, among other driving operations).

[0021] In some aspects, ADAS 102 is configured to transmit messages to ADAS support server 115 to share information related to one or more of the driver assistance features. In a non-limiting example, messages may be transmitted in response to ADAS events, which may include, but are not limited to: the state of driver assistance features (e.g., which features are active and which are inactive), activation / deactivation of adaptive cruise control 108, driving actions taken to correct lane position, detection of forward disturbances, and / or driving actions taken to avoid object disturbances. The types of information included in the message as vehicle data may include, but are not limited to: vehicle position, vehicle heading, steering angle, lane position, speed setting for cruise control, data related to detected objects (object classification and object position relative to the vehicle), traffic conditions, entry / exit from predefined geographic areas (e.g., geofence alerts), image data of one or more images of the area surrounding vehicle 100; and / or data related to the type of maneuver taken to avoid disturbances.

[0022] In one embodiment, the ADAS support server 115 is configured to use information from vehicle 100 for various purposes, such as, but not limited to: sharing data with other vehicles or systems (e.g., sharing information about vehicle location to address traffic delays), for driver assistance models for autonomous driving control; and / or training or adjusting algorithms associated with one or more of the driver assistance features. In a non-limiting example, the ADAS support server 115 is provided as a remote server supported by the original manufacturer of vehicle 100.

[0023] In addition to ADAS system 102, vehicle 100 also includes navigation system 116 and communication system 118. In one embodiment, navigation system 116 is configured to monitor the position of vehicle 100 and define a driving route to a desired location that can be input by a user of vehicle 100. In another embodiment, navigation system 116 includes a Global Navigation Satellite System (GNSS) receiver 120, a navigation controller 122, and a map library 124 that stores maps using map tile technology, wherein the map tiles have the same shape, each map tile conveys information related to a selected area, and the group of map tiles defines a continuous map when combined.

[0024] GNSS receiver 120 is configured to use one or more satellite networks (such as Global Positioning System (GPS), GLONASS, Galileo, BeiDou, and / or others) to determine the position or absolute coordinates of vehicle 100. In a non-limiting example, absolute coordinates are provided as latitude and longitude to provide a precise geographic location.

[0025] In one embodiment, navigation controller 122 is configured to monitor the movement of vehicle 100 to provide route guidance and real-time navigation. In a non-limiting example, using a map stored in map library 124, navigation controller 122 tracks the movement of vehicle 100 using absolute coordinates and movement (e.g., heading, speed, etc.) of vehicle 100 that can be provided by ADAS 102. Navigation controller 122 may also receive information from external systems that may affect the driving of vehicle 100, such as, but not limited to, traffic information from local infrastructure and / or driving information of other vehicles traveling within the communication range of vehicle 100.

[0026] Communication system 118 is configured to provide communication interfaces between various systems of vehicle 100 and between vehicle 100 and external devices / systems (e.g., ADAS support server 115). In a non-limiting example, communication system 118 includes gateway controller 130, telematics controller 132 (e.g., telematics control unit (TCU)), and vehicle location anonymization (VLA) module 134.

[0027] Gateway controller 130 can be configured to provide an electrical interface between vehicle communication buses used for communication within vehicle 100. In one example, gateway controller 130 can be configured to route signals from one vehicle bus to another vehicle bus within vehicle 100. Gateway controller 130 can accordingly allow different components of vehicle 100 to communicate, even if said components are connected and connected to different buses in different ways.

[0028] The telematics controller 132 allows vehicle 100 to communicate with remote devices via one or more communication networks. In a non-limiting example, the telematics controller 132 is configured to: track vehicle position; allow remote diagnostics of vehicle 100; exchange messages with other vehicles or devices as part of vehicle-to-the-world (V2X) communication, whereby vehicle 100 shares information related to vehicle 100, such as speed, heading, and anonymous position data; and output signals indicating that assistance may be needed in vehicle 100 due to object interference, for example. In some forms, the telematics controller 132 may include an antenna system supporting one or more communication technologies, a GNSS receiver, a cellular modem, a Bluetooth / Wi-Fi module for short-range communication, a microprocessor and / or memory for storing software applications, and other communication devices.

[0029] While sharing information with external systems (e.g., ADAS support server 115) is beneficial and sometimes necessary according to various standards (e.g., V2X), VLA module 134 is configured to provide anonymity for vehicle 100, specifically by providing it to the location of vehicle 100 provided in the message. In one form, VLA module 134 is configured to define anonymous location data that provides a defined geographic area (e.g., map tiles) in which vehicle 100 is traveling. That is, instead of the absolute coordinates of vehicle 100, VLA module 134 is configured to relate information to a larger general area associated with the surrounding environment of vehicle 100 in order to provide anonymity without retaining information used to enhance ADAS 102.

[0030] In one form, VLA module 134 includes coordinate anonymization module 140 and location metadata generator 142.

[0031] The coordinate anonymization module 140 is configured to transform or convert the absolute coordinates of vehicle 100 into position information independent of vehicle 100. (Reference) Figure 2 An example coordinate anonymization procedure 200 is provided, executed by the coordinate anonymization module 140. In a non-limiting example, procedure 200 may be executed when ADAS 102 detects an event, when vehicle 100 starts, and / or when a request for information is received from ADAS server 115.

[0032] Process 200 performs different location selection 204 to identify location coordinates 206 associated with different locations separate from vehicle 100. For different location selection 204, coordinate anonymization module 140 is configured to identify or select different locations using absolute coordinates 202. In a non-limiting example, map data from navigation controller 122 is used. Coordinate anonymization module 140 is configured to identify different locations as places of interest or look-up points near vehicle 100 (e.g., at a set distance from the vehicle). For example, referencing... Figure 3 Using the absolute coordinates 302 of vehicle 100, coordinate anonymization module 140 identifies lookup point 304 as a distinct location. Any suitable location can be used as a distinct location and should not be limited to the examples provided herein. For example, coordinate anonymization module 140 is configured to identify distinct locations as predefined longitude and latitude distances from the vehicle.

[0033] Using the position coordinates, the coordinate anonymization module 140 performs vehicle coordinate hashing 208 to obtain fuzzy coordinates 210 with hash coordinates and incremental coordinates. That is, the fuzzy coordinates 210 identify the vehicle's position using the positional relationship between the vehicle 100 and different locations. In a non-limiting example, the coordinate anonymization module 140 defines incremental coordinates reflecting the XY position of the vehicle 100 from different locations (e.g., incremental coordinates = (Δx, Δy)). Alternatively, instead of using the numerical values ​​of the position coordinates, the coordinate anonymization module 140 uses hash coordinates for different locations (e.g., position coordinates (31.657, 31.657) are provided as (#, #)). The fuzzy coordinates 210 of the vehicle are then provided as position hash coordinates + incremental coordinates = ((# + Δx), (# + Δy)).

[0034] Continue to refer to Figure 3 The coordinate anonymization module 140 is configured to update the fuzzy coordinates 210 based on the movement of the vehicle 100. For example, absolute coordinates 302 are associated with a first position of the vehicle 100 having first incremental coordinates (Δx1, Δy1), and coordinates 306 are associated with a second position of the vehicle 100 having second incremental coordinates (Δx2, Δy2), which can be determined based on the movement of the vehicle.

[0035] Return to Figure 2 Using fuzzy coordinates 210, coordinate anonymization module 140 performs map tile selection 212 to obtain associated map tiles 214. In a non-limiting example, when the location of vehicle 100 is requested (e.g., in response to an ADAS event, a message transmission from telematics controller 132, etc.), map tile selection 212 retrieves the map tile associated with fuzzy coordinates 210 from a plurality of map tiles stored by map library 124. For example, in Figure 3In this context, map tile 310 is selected for fuzzy coordinates related to the second location 306 or more broadly to the ADAS event (the location of vehicle 100 at the time of the ADAS event) or to the received message request.

[0036] Additionally, the coordinate anonymization module 140 is configured to perform hash coordinate generalization 216 to define anonymous vehicle coordinates 218. In a non-restrictive example, the anonymous vehicle coordinates 218 are represented by incremental coordinates with the hash coordinates removed (e.g., ((#+Δx),(#+Δy))→(Δx,Δy)).

[0037] The coordinate anonymization module 140 performs vehicle position representation 220 to generate anonymous location data 222 using associated map tiles 214 and anonymous vehicle coordinates 218. Specifically, instead of absolute coordinates, map tiles and incremental coordinates are used to identify the location of vehicle 100, thereby providing anonymity for vehicle 100 and its user. In one form, the VLA module 134 provides the anonymous location data 222 to a telematics controller 132, which then incorporates the data 222 as part of a message to be transmitted. In some variations, the coordinate anonymization module 140 is configured to change the rotation of the coordinate plane by, for example, switching the position of (x, y) coordinates in the anonymous vehicle coordinates (e.g., incremental coordinates (Δx, Δy) are provided as (Δy, Δx)).

[0038] In some respects, VLA module 134 can provide metadata related to the surrounding environment of vehicle 100, which can be detected by sensor 114 or even represented in map tiles. Third parties can use the metadata to detect the actual location of the vehicle, and to prevent such detection, location metadata generator 142 is configured to modify location characteristics that can be used as metadata so that these characteristics are not used to track the location of vehicle 100.

[0039] In one form, location features are associated with a region having absolute coordinates. For example, location features can include, but are not limited to: landmarks (e.g., statues, lakes, mountains, buildings); the curvature of a road over which vehicles are traveling; or road markings. Location features can be represented from various sources, such as, but not limited to: images from cameras and map tiles.

[0040] Location metadata generator 142 is configured to modify information related to the location characteristics of a region to generate fuzzy characteristics that cannot be identified by the absolute coordinates of the region or, more specifically, vehicle 100. In a non-limiting example, location characteristics can be modified by: altering the physical properties of landmarks (e.g., blurring the design of a statue, adding additional landmarks, changing the size of a landmark); changing the curvature of a road (e.g., shortening curves along a road); or editing identification information (e.g., editing signs, road names, businesses). VLA module 134 is configured to provide fuzzy characteristics as part of the anonymized location data.

[0041] While a specific type of metadata is provided, other suitable information related to location characteristics can be used. For example, location characteristics can provide a spatial extent associated with the actual location of vehicle 100, where the spatial extent is provided as a two-dimensional extent (e.g., 1x1 mile, 2x2 mile), with fuzzy characteristics replacing the distance from a specific point.

[0042] In operation, VLA module 134 is configured to provide anonymous location data for messages based on requests initiated from a vehicle system (e.g., ADAS 102) or an external system (e.g., ADAS server 115). In a non-limiting example, when ADAS 102 detects an ADAS event to be reported to ADAS server 115, ADAS 102 requests a message with defined fields to be output, one of which includes the vehicle's location at the time the ADAS event occurred. VLA module 134 defines anonymous location data for the vehicle location field. In some aspects, in addition to anonymous location data, the message also includes vehicle data associated with the ADAS event provided by ADAS 102.

[0043] In some respects, vehicle data related to ADAS events can be stored in vehicle database 150. Regarding the location of vehicle 100, vehicle database 150 can store the absolute coordinates of vehicle 100, which can be encrypted. Therefore, the absolute coordinates remain available and accessible to authorized personnel to, for example, verify software updates and / or provide additional accuracy when analyzing the operation of driver assistance features related to ADAS events. In addition to absolute coordinates, vehicle database 150 can also store anonymous location data 222 associated with the absolute coordinates.

[0044] In another example, as a supplement to or alternative to waiting for ADAS events, ADAS server 115 or other external systems may request status updates regarding vehicle 100. Upon receiving the request, vehicle 100 generates and outputs a message that includes selected vehicle data (such as anonymous location data).

[0045] Although VLA module 134 is described as being associated with location data that transmits messages related to ADAS 102, the VLA module 134 of this disclosure can be integrated with other suitable systems of vehicle 100.

[0046] Unless otherwise expressly indicated herein, all numerical values ​​indicating mechanical / thermal properties, percentage of composition, dimensions and / or tolerances or other characteristics should be understood as being modified by the words “about” or “approximately” when describing the scope of this disclosure. Such modification is desired for a variety of reasons, including: industrial practice; material, manufacturing and assembly tolerances; and testing capabilities.

[0047] In this application, the terms “module” and / or “computing device” may refer to, be part of, or include the following: application-specific integrated circuit (ASIC); digital, analog, or mixed-signal analog / digital discrete circuit; digital, analog, or mixed-signal analog / digital integrated circuit; composable logic circuit; field-programmable gate array (FPGA); processor circuitry (shared, dedicated, or grouped) that executes code; memory circuitry (shared, dedicated, or grouped) that stores code executed by the processor circuitry; other suitable hardware components that provide the described functionality; or combinations of some or all of the foregoing, such as in a system-on-a-chip.

[0048] The term memory is a subset of the term computer-readable medium. As used herein, the term computer-readable medium does not cover transient electrical or electromagnetic signals propagated through a medium (such as on a carrier wave); therefore, the term computer-readable medium can be considered tangible and non-transient. Non-limiting examples of non-transient tangible computer-readable media include non-volatile memory circuits (such as flash memory circuits, erasable programmable read-only memory circuits, or mask read-only circuits), volatile memory circuits (such as static random access memory circuits or dynamic random access memory circuits), magnetic storage media (such as analog magnetic tape or digital magnetic tape or hard disk drives), and optical storage media (such as USB, CD, DVD, or Blu-ray discs).

[0049] The apparatus and methods described in this application can be implemented, in part or in whole, by a dedicated computer created by configuring a general-purpose computer (e.g., a computing device) to perform one or more specific functions embodied in a computer program. Function blocks, flowchart components, and other elements described above serve as software specifications that can be translated into computer programs through the routine work of a technician or programmer.

[0050] The description in this disclosure is merely exemplary in nature, and therefore, variations without departing from the spirit and scope of this disclosure are intended to be made within its scope. Such variations should not be considered as departing from the spirit and scope of this disclosure.

[0051] According to the present invention, a method includes: defining incremental coordinates by a vehicle system indicating the positional relationship between a vehicle and different locations from which the vehicle is separated; converting the absolute coordinates of the vehicle by the vehicle system into fuzzy coordinates having hash coordinates associated with the different locations and the incremental coordinates; retrieving map tiles associated with the fuzzy coordinates from a plurality of map tiles by the vehicle system; and outputting a message by the vehicle system including anonymous location data as the location of the vehicle and defined by the map tiles and the incremental coordinates.

[0052] In one aspect of the invention, the method includes the vehicle system using the absolute coordinates to identify the different locations separated from the vehicle.

[0053] In one aspect of the invention, the method includes: identifying location characteristics of a region having the absolute coordinates by the vehicle system; and modifying information related to the location characteristics of the region by the vehicle system to generate fuzzy characteristics that the region cannot be identified, wherein the anonymous location data is further defined using the fuzzy characteristics.

[0054] In one aspect of the invention, the location characteristic includes at least one of the following: a landmark associated with the map tile, the curvature of the road on which the vehicle is traveling, or the road markings.

[0055] In one aspect of the invention, information for changing the location characteristics includes at least one of the following: modifying the physical properties of the landmark, changing the curvature of the road, or editing the road markings.

[0056] In one aspect of the invention, the method includes updating the incremental coordinates by the vehicle system based on the movement of the vehicle.

[0057] In one aspect of the invention, the method includes: in response to an Advanced Driver Assistance System (ADAS) event, storing data indicating the absolute coordinates of the vehicle at the time of the ADAS event by the vehicle system; and generating vehicle data associated with the ADAS event by the vehicle system, wherein the message further includes the vehicle data, wherein the anonymous location data includes the map tiles and the incremental coordinates associated with the ADAS event.

[0058] In one aspect of the invention, the method includes: receiving a vehicle data request from a remote server, wherein: the message is output to the remote server in response to the vehicle data request and includes at least one vehicle data and the incremental coordinates at the time of the vehicle data request.

[0059] According to the present invention, a system for a vehicle is provided, the system comprising: one or more computing devices configured to: define incremental coordinates indicating the positional relationship between the vehicle and different locations from which the vehicle is separated; convert the absolute coordinates of the vehicle into fuzzy coordinates having hash coordinates associated with the different locations and the incremental coordinates; retrieve map tiles associated with the fuzzy coordinates from a plurality of map tiles; and output a message including anonymous location data as the location of the vehicle and defined by the map tiles and the incremental coordinates.

[0060] According to one embodiment, the one or more computing devices are further configured to: obtain the absolute coordinates using at least one location signal from a satellite network, and use the absolute coordinates to identify the different locations separated from the vehicle.

[0061] According to one embodiment, the one or more computing devices are further configured to: identify the location characteristics of a region having the absolute coordinates, and modify information related to the location characteristics of the region to generate fuzzy characteristics that the region cannot be identified, wherein the anonymous location data is further defined using the fuzzy characteristics.

[0062] According to one embodiment, the location characteristics include at least one of the following: a landmark associated with the map tile, the curvature of the road on which the vehicle is traveling, or the road markings.

[0063] According to one embodiment, in order to change the location characteristics information, the one or more computing devices are further configured to perform at least one of the following: modifying the physical characteristics of the landmark, changing the curvature of the road, or editing the road signage.

[0064] According to one embodiment, the one or more computing devices are further configured to update the incremental coordinates based on the vehicle movement.

[0065] According to one embodiment, the one or more computing devices are further configured to respond to an Advanced Driver Assistance System (ADAS) event: store data indicating the absolute position of the vehicle at the time of the ADAS event, and generate vehicle data associated with the ADAS event, wherein the message further includes the vehicle data, and wherein the anonymous location data includes the map tiles and incremental coordinates associated with the ADAS event.

[0066] According to one embodiment, the message is output to the remote server in response to receiving a vehicle data request from the remote server and includes at least one vehicle data and the incremental coordinates at the time of the vehicle data request.

[0067] According to the present invention, a method includes: obtaining absolute coordinates of a vehicle by a vehicle system using at least one location signal from a satellite network; identifying different locations separated from the vehicle by the vehicle system using the absolute coordinates; defining incremental coordinates by the vehicle system indicating the positional relationship between the vehicle and the different locations; converting the absolute coordinates of the vehicle into fuzzy coordinates having hash coordinates associated with the different locations and the incremental coordinates by the vehicle system; retrieving map tiles associated with the fuzzy coordinates from a plurality of map tiles by the vehicle system; and outputting a message including anonymous location data defined by the map tiles and the incremental coordinates as the location of the vehicle by the vehicle system.

[0068] In one aspect of the invention, the method includes: identifying location characteristics of a region having the absolute coordinates by the vehicle system; and modifying information related to the location characteristics of the region by the vehicle system to generate fuzzy characteristics that the region cannot be identified, wherein the anonymous location data is further defined using the fuzzy characteristics.

[0069] In one aspect of the invention, the location characteristic includes at least one of the following: a landmark associated with the map tile, the curvature of the road on which the vehicle is traveling, or the road identification, and information for changing the location characteristic includes at least one of the following: modifying the physical properties of the landmark, changing the curvature of the road, or editing the road identification.

[0070] In one aspect of the invention, the method includes: in response to an Advanced Driver Assistance System (ADAS) event, generating vehicle data associated with the ADAS event by the vehicle system, wherein the message further includes the vehicle data; and storing by the vehicle system at least one of the vehicle data and data indicating the absolute position of the vehicle at the time of the ADAS event, wherein the anonymous position data includes the map tiles and the incremental coordinates associated with the ADAS event.

Claims

1. A method comprising: Incremental coordinates, defined by the vehicle system, indicate the positional relationship between the vehicle and different locations where the vehicle is separated from it. The vehicle system converts the absolute coordinates of the vehicle into fuzzy coordinates with hash coordinates associated with the different locations and the incremental coordinates; The vehicle system retrieves map tiles associated with the fuzzy coordinates from multiple map tiles; as well as The vehicle system outputs a message including anonymous location data, which is the location of the vehicle and is defined by the map tiles and the incremental coordinates.

2. The method of claim 1, further comprising using the absolute coordinates by the vehicle system to identify the distinct locations separated from the vehicle.

3. The method of claim 1, further comprising: The location characteristics of the region with the absolute coordinates identified by the vehicle system; as well as The vehicle system modifies information related to the location characteristics of the area to generate fuzzy characteristics that the area cannot be identified, and the anonymous location data is further defined using these fuzzy characteristics.

4. The method of claim 3, wherein the location characteristic includes at least one of the following: a landmark associated with the map tile, the curvature of the road on which the vehicle is traveling, or the road markings.

5. The method of claim 4, wherein the information for changing the location characteristics includes at least one of the following: modifying the physical characteristics of the landmark, changing the curvature of the road, or editing the road signage.

6. The method of claim 1, further comprising updating the incremental coordinates by the vehicle system based on the movement of the vehicle.

7. The method of claim 6, further comprising responding to an advanced driver assistance system (ADAS) event. The vehicle system stores data indicating the absolute coordinates of the vehicle at the time of the ADAS event; and The vehicle system generates vehicle data associated with the ADAS event, wherein the message also includes the vehicle data. The anonymous location data includes the map tiles and incremental coordinates associated with the ADAS event.

8. The method of claim 6, further comprising: Receive vehicle data requests from a remote server, including: The message is output to the remote server in response to the vehicle data request and includes at least one vehicle data and the incremental coordinates at the time of the vehicle data request.

9. A system for a vehicle, comprising: One or more computing devices, the one or more computing devices being configured to: Define incremental coordinates that indicate the positional relationship between the vehicle and different locations where the vehicle is separated. The absolute coordinates of the vehicle are converted into fuzzy coordinates with hash coordinates associated with the different locations and the incremental coordinates. Retrieve map tiles associated with the fuzzy coordinates from multiple map tiles, and The output includes a message containing anonymous location data, which is the location of the vehicle and is defined by the map tiles and the incremental coordinates.

10. The system of claim 9, wherein the one or more computing devices are further configured to: The absolute coordinates are obtained using at least one position signal from a satellite network, and The absolute coordinates are used to identify the different locations that are separated from the vehicle.

11. The system of claim 9, wherein the one or more computing devices are further configured to: The location characteristics of the region having the absolute coordinates, and Information related to the location characteristics of the region is modified to generate fuzzy characteristics that the region cannot identify, and the anonymous location data is further defined using these fuzzy characteristics.

12. The system of claim 11, wherein the location characteristic includes at least one of the following: a landmark associated with the map tile, the curvature of the road on which the vehicle is traveling, or the road markings.

13. The system of claim 12, wherein, in order to change the information of the location characteristics, the one or more computing devices are further configured to perform at least one of the following: modifying the physical characteristics of the landmark, changing the curvature of the road, or editing the signage of the road.

14. The system of claim 9, wherein the one or more computing devices are further configured to update the incremental coordinates based on the vehicle movement.

15. The system of claim 14, wherein the one or more computing devices are further configured to respond to an advanced driver assistance system (ADAS) event: Store data indicating the absolute position of the vehicle at the time of the ADAS event, and Generate vehicle data associated with the ADAS event, wherein the message also includes the vehicle data. The anonymous location data includes the map tiles and incremental coordinates associated with the ADAS event.

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