WO2022052283A1 - Procédé et dispositif de positionnement de véhicule - Google Patents

Procédé et dispositif de positionnement de véhicule Download PDF

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Publication number
WO2022052283A1
WO2022052283A1 PCT/CN2020/126947 CN2020126947W WO2022052283A1 WO 2022052283 A1 WO2022052283 A1 WO 2022052283A1 CN 2020126947 W CN2020126947 W CN 2020126947W WO 2022052283 A1 WO2022052283 A1 WO 2022052283A1
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map data
semantic element
preset
real
time
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PCT/CN2020/126947
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English (en)
Chinese (zh)
Inventor
肖志光
刘中元
柴文楠
李红军
黄亚
蒋少峰
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广州小鹏自动驾驶科技有限公司
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Publication of WO2022052283A1 publication Critical patent/WO2022052283A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position

Definitions

  • the present invention relates to the technical field of positioning, and in particular, to a method and device for positioning a vehicle.
  • the positioning system of the vehicle can provide the driver with path driving guidance, facilitate the driver to quickly determine the current location, and provide convenient services for public travel.
  • GNSS Global Navigation Satellite System, global navigation satellite system
  • GNSS Global Navigation Satellite System, global navigation satellite system
  • GNSS may be unstable in some cases, resulting in a certain deviation of the positioning information of the vehicle, which cannot be used for driving. to provide reliable positioning information.
  • the positioning accuracy of vehicle positioning only through GNSS is limited, which cannot meet people's requirements for high-precision positioning of vehicles.
  • a method for locating a vehicle comprising:
  • the positioning of the vehicle is updated.
  • the determining the map matching information of the first map data and the second map data includes:
  • the real-time second semantic element matches the preset second semantic element, it is determined that the real-time third semantic element corresponding to the real-time second semantic element and the preset third semantic element corresponding to the preset second semantic element Whether the semantic element matches;
  • map matching information of the first map data and the second map data is determined according to the matching result.
  • a target fourth semantic element is determined; wherein the target fourth semantic element is associated with the real-time first semantic element, the real-time third semantic element, and the preset first semantic element , the preset third semantic element is a semantic element of the same type;
  • map matching information of the first map data and the second map data is determined.
  • determining the map matching information of the first map data and the second map data according to the target fourth semantic element includes:
  • the target second semantic element is the real-time second semantic element
  • determine that the preset third semantic element matches the target fourth semantic element and determine the first map data and the target fourth semantic element according to the matching result. Map matching information of the second map data.
  • determine the map matching information of the first map data and the second map data including:
  • the target second semantic element is the preset second semantic element
  • determine that the real-time third semantic element matches the target fourth semantic element and determine the first map data and the target fourth semantic element according to the matching result. Map matching information of the second map data.
  • the second map data is map data fused by at least two map data, further comprising:
  • clustering is performed according to the positioning information to obtain a semantic element clustering result
  • the at least two map data are fused to obtain second map data.
  • the real-time first semantic element, the real-time third semantic element, the preset first semantic element, and the preset third semantic element are semantic elements for turning points
  • the real-time second semantic element The semantic element, the real-time second semantic element is a semantic element for a road.
  • a vehicle positioning device includes:
  • a first map data acquisition module configured to acquire the first map data collected in real time
  • a first map data matching module for detecting whether a second map data matching the first map data is preset
  • a map matching information determining module configured to determine map matching information of the first map data and the second map data when it is detected that the second map data matching the first map data is preset;
  • a positioning update module configured to update the positioning of the vehicle according to the map matching information.
  • a vehicle includes a processor, a memory, and a computer program stored on the memory and capable of running on the processor, the computer program being executed by the processor to implement the method for locating the vehicle as described above.
  • a computer-readable storage medium stores a computer program on the computer-readable storage medium, and when the computer program is executed by a processor, implements the above-mentioned method for locating a vehicle.
  • the embodiment of the present invention detects whether there is preset second map data matching the first map data by acquiring the first map data collected in real time, and when detecting that the second map data matching the first map data is preset
  • map data is used, the map matching information of the first map data and the second map data is determined, and the vehicle is positioned and updated according to the map matching information, so as to realize the positioning update of the vehicle position.
  • Matching the first map data and the preset second map data can obtain more accurate positioning information, update the positioning according to the high-precision positioning information, improve the accuracy of the positioning information, and ensure the accuracy of the positioning information.
  • FIG. 1 is a flow chart of steps of a method for locating a vehicle according to an embodiment of the present invention
  • FIG. 3 is a schematic structural diagram of a vehicle positioning device according to an embodiment of the present invention.
  • the positioning system When the vehicle is in the parking lot, the positioning system may be unstable. In this case, the driver cannot determine his own location, or the positioning system will give the driver a wrong direction, so that the driver cannot accurately reach the target position. Therefore, in the parking lot, it is necessary to allow the driver to quickly determine his own position through high-precision positioning.
  • FIG. 1 a flowchart of steps of a method for locating a vehicle provided by an embodiment of the present invention is shown, which may specifically include the following steps:
  • Step 101 acquiring first map data collected in real time
  • the first map data can be obtained by collecting sensor data collected in real time. Because the positioning system is unstable in the parking lot environment, the preliminary positioning information of the current position can be obtained by directly collecting the first map data obtained from the sensor data, and further processing of the first map data can obtain a higher positioning accuracy. location information.
  • the sensory data may include any one or more of the following:
  • the sensing data may also include wheel speed or wheel pulse signals, steering wheel angle signals or IMU angular velocity signals, and coordinates of corner points of the visual parking space, wherein the IMU angular velocity signal includes at least the z-axis angular velocity, and the frequency range can be 10-100 Hz.
  • the transmitted data in the preset container can be processed in real time, and the size of the preset container can be set to a preset fixed mileage that the vehicle travels, for example, The preset fixed mileage can be set to 2km.
  • the preset fixed mileage can be set to 2km.
  • the target map data can be stored on the computer on the vehicle end or uploaded to the cloud server, and the saved target map data can be used to generate a fusion map and update the vehicle positioning.
  • the map data generated in the parking lot can be saved, and the car usually needs to be locked in the parking lot.
  • the map data obtained before locking the car is saved in the map data generated in the preset fixed mileage, and the saved map data is generated based on the parking lot area.
  • the preset GPS accuracy and the preset minimum number of parking spaces can be adjusted as needed.
  • the preset GPS accuracy for the joint is 2 meters, and the preset minimum number of parking spaces is 20.
  • Step 102 detecting whether there is preset second map data matching the first map data
  • the second map data is map data fused by at least two map data, and the semantic elements of the at least two map data are clustered according to positioning information to obtain a semantic element cluster. Class result; according to the semantic element clustering result, the at least two map data are fused to obtain second map data.
  • map data can be generated according to the sensor data collected each time. Therefore, there can be one or more map data for the same area.
  • semantic elements can be extracted for each map data, and the semantic elements can be clustered according to the positioning information to obtain the semantic element clustering result.
  • the clustering result is that the positioning information of the semantic elements is similar, and the Semantic elements representing the same location are clustered into the same class, and then at least two map data can be fused according to the semantic element clustering result, and finally, the semantic elements of the same class can only correspond to one map data.
  • the semantic elements of the same type in the original multiple map data are merged into one semantic element, and for the semantic elements that are not the same or similar in the multiple map data, through fusion,
  • the fused map data can obtain richer semantic elements, which can improve the map data, and the final fused map data is also closer to the actual situation of the target area.
  • semantic elements A1, B, and C in map 1 there are three semantic elements A1, B, and C in map 1, and three semantic elements A2, E, and F in map 2, which are obtained by clustering according to the positioning position, A1 and A2 are clustered into one class, and map 1 and After map 2 is fused, it can be obtained that the fusion map contains 5 semantic elements including A, B1, C1, E1, and F1.
  • A is obtained by merging A1 and A2, and B1, C1, E1, and F1 are composed of B, C, respectively.
  • E and F are adjusted to obtain semantic elements.
  • Step 103 when detecting that the second map data matching the first map data is preset, determine the map matching information of the first map data and the second map data;
  • the map matching information of the first map data and the second map data can be further obtained, and the map matching information can be used for matching the first map data.
  • the positioning information of the current position obtained in the data is further updated to obtain higher-precision and more accurate positioning information.
  • the first map data may be map data generated in real time
  • the second data map may be preset map data.
  • the preset condition may be that the distance between the latitude and longitude coordinates of the semantic element is less than the first preset threshold
  • the current position and direction can be calculated through the turning angle matching relationship in the matching information or the semantic elements matched on the road, and the positioning of the vehicle obtained from the first map data can be further updated to obtain higher positioning accuracy.
  • Step 104 according to the map matching information, update the location of the vehicle.
  • each positioning information in the real-time first map data can be updated according to the map matching information to obtain more accurate and reliable positioning information.
  • the embodiment of the present invention detects whether there is preset second map data matching the first map data by acquiring the first map data collected in real time, and when detecting that the second map data matching the first map data is preset
  • map data is used, the map matching information of the first map data and the second map data is determined, and the vehicle is positioned and updated according to the map matching information, so as to realize the positioning update of the vehicle position.
  • Matching the first map data and the preset second map data can obtain more accurate positioning information, update the positioning according to the high-precision positioning information, improve the accuracy of the positioning information, and ensure the accuracy of the positioning information.
  • FIG. 2 a flowchart of steps of another vehicle positioning method provided by an embodiment of the present invention is shown, which may specifically include the following steps:
  • Step 201 acquiring first map data collected in real time
  • Step 202 detecting whether there is preset second map data matching the first map data
  • Step 203 for the real-time first semantic element in the first map data, determine the matching preset first semantic element in the second map data;
  • the first map data includes at least a real-time first semantic element, a real-time second semantic element and a real-time third semantic element;
  • the second map data at least includes a preset first semantic element, a preset second semantic element, and a preset first semantic element.
  • the real-time first semantic element, the real-time third semantic element, the preset first semantic element, and the preset third semantic element are semantic elements for turning points, so
  • the real-time second semantic element, and the real-time second semantic element is a semantic element for a road.
  • the matching preset first semantic element in the map data is determined. Since the semantic element in the map data is the location information for a certain target area, two map data with matching semantic elements can be preliminarily judged as matching. Map data, i.e. the area where the map is overlaid.
  • the map matching information can be converted through the matching relationship of semantic elements between the second map data and the first map data, so as to obtain more accurate positioning information.
  • Step 204 for the real-time second semantic element corresponding to the real-time first semantic element, determine the preset second semantic element corresponding to the preset first semantic element;
  • the real-time first semantic element can have its corresponding real-time second semantic element
  • the preset first semantic element can have its corresponding preset second semantic element Semantic element, for the real-time first semantic element, one or more real-time second semantic elements corresponding to it are determined by searching the first map data.
  • searching in the second map data The search determines one or more preset second semantic elements corresponding thereto, and further, for each real-time second semantic element, a matching preset second semantic element may be determined among all the preset second semantic elements.
  • the first map data can be traversed by breadth first search based on the real-time first semantic element in the first map data, to obtain the real-time first map data in the first map data.
  • a semantic element of the same semantic element type wherein the first real-time semantic element may be the semantic element of the turning point, and the semantic element obtained by traversal may also be the semantic element of the turning point. Then, the semantic elements obtained by traversal can be further matched to obtain all matching results that can be matched.
  • Step 205 when the real-time second semantic element matches the preset second semantic element, determine the real-time third semantic element corresponding to the real-time second semantic element and the preset second semantic element corresponding to the preset second semantic element. Set whether the third semantic element matches;
  • the real-time second semantic element can be matched with the preset second semantic element.
  • the preset second semantic element may have a corresponding preset third semantic element, and for each real-time third semantic element, it may be further determined whether it matches the preset third semantic element. , it is determined that the real-time third semantic element matches the preset third semantic element.
  • Step 206 after determining that the real-time third semantic element matches the preset third semantic element, according to the matching result, determine the map matching information of the first map data and the second map data;
  • map matching information of the first map data and the second map data may be determined according to the matching result, and the map matching information may be used for relocation.
  • the real-time third semantic element when it is determined that the real-time third semantic element does not match the preset third semantic element, from the determining a target second semantic element from the real-time second semantic element and the preset second semantic element; for the target second semantic element, determining a target fourth semantic element;
  • the target fourth semantic element is the same type of semantic element as the real-time first semantic element, the real-time third semantic element, the preset first semantic element, and the preset third semantic element; According to the target fourth semantic element, map matching information of the first map data and the second map data is determined.
  • the target second semantic element may be determined from the real-time second semantic element and the preset second semantic element, and the target second semantic element may be the real-time second semantic element
  • the semantic element can also be a preset second semantic element, and the target fourth semantic element is determined according to the target second semantic element, and the target fourth semantic element is the corresponding semantic element re-determined by the target second semantic element, and the target fourth semantic element is The semantic element can be matched with the real-time third semantic element or the preset third semantic element.
  • the first map data and the second map are determined according to the target fourth semantic element
  • the map matching information of the data includes: when the target second semantic element is the real-time second semantic element, determining that the preset third semantic element matches the target fourth semantic element, and according to the matching result, Map matching information of the first map data and the second map data is determined.
  • the target second semantic element is the real-time second semantic element
  • the corresponding semantic element that can be re-determined for the real-time second semantic element is the target fourth semantic element
  • the target fourth semantic element can be the same as the preset third semantic element.
  • the semantic elements are matched, so that map matching information of the first map data and the second map data is determined according to the matching result.
  • the first map data and the second map are determined according to the target fourth semantic element
  • the map matching information of the data includes: when the target second semantic element is the preset second semantic element, determining that the real-time third semantic element matches the target fourth semantic element, and according to the matching result, Map matching information of the first map data and the second map data is determined.
  • the corresponding semantic element that can be re-determined for the preset second semantic element can be the target fourth semantic element, and the target fourth semantic element can be the same as the real-time first semantic element.
  • Three semantic elements are matched, so that map matching information of the first map data and the second map data is determined according to the matching result.
  • mapping is performed step by step for the semantic elements that are successfully matched at first, until the matching of all semantic elements of the first map data is completed, so that the map matching information of the first map data and the second map data can be obtained.
  • the matching information can improve the accuracy of the positioning information and ensure the accuracy of the positioning information.
  • steps 203 to 206 there may be the following examples:
  • the first map data may be a real-time topological map map1 obtained according to sensor data in a preset container
  • the second map data may be a fusion map map2 fused according to at least two map data.
  • Step 207 according to the map matching information, update the location of the vehicle.
  • the embodiment of the present invention detects whether there is preset second map data matching the first map data by acquiring the first map data collected in real time, and when detecting that the second map data matching the first map data is preset
  • map data is used, the map matching information of the first map data and the second map data is determined, and the vehicle is positioned and updated according to the map matching information, so as to realize the positioning update of the vehicle position.
  • Matching the first map data and the preset second map data can obtain more accurate positioning information, update the positioning according to the high-precision positioning information, improve the accuracy of the positioning information, and ensure the accuracy of the positioning information.
  • FIG. 3 a schematic structural diagram of a vehicle positioning device provided by an embodiment of the present invention is shown, which may specifically include the following modules:
  • the first map data acquisition module 301 is used to acquire the first map data collected in real time;
  • a first map data matching module 302 configured to detect whether a second map data matching the first map data is preset
  • a map matching information determination module 303 configured to determine map matching information of the first map data and the second map data when it is detected that the second map data matching the first map data is preset;
  • the positioning update module 304 is configured to update the positioning of the vehicle according to the map matching information.
  • the map matching information determination module 303 includes:
  • a preset first semantic element determination submodule configured to determine a matching preset first semantic element in the second map data for the real-time first semantic element in the first map data
  • a preset second semantic element determination submodule configured to determine, for the real-time second semantic element corresponding to the real-time first semantic element, the preset second semantic element corresponding to the preset first semantic element;
  • the first sub-module for determining the map matching information is used to determine that the real-time third semantic element matches the preset third semantic element, and determine the relationship between the first map data and the second map data according to the matching result. Map matching information.
  • the real-time first semantic element, the real-time third semantic element, the preset first semantic element, and the preset third semantic element are semantic elements for turning points, so
  • the real-time second semantic element, and the real-time second semantic element is a semantic element for a road.
  • the map matching information determining module 303 further includes:
  • the target second semantic element determination sub-module is configured to, when determining that the real-time third semantic element does not match the preset third semantic element, select from the real-time second semantic element and the preset second semantic element determining the target second semantic element;
  • a target fourth semantic element determination submodule configured to determine the target fourth semantic element for the target second semantic element
  • the target fourth semantic element is the same type of semantic element as the real-time first semantic element, the real-time third semantic element, the preset first semantic element, and the preset third semantic element;
  • the second sub-module for determining map matching information determines map matching information of the first map data and the second map data according to the target fourth semantic element.
  • the second submodule for determining the map matching information includes:
  • the map matching information determines a first sub-unit for determining that the preset second semantic element matches the target fourth semantic element when the target second semantic element is the real-time second semantic element, and according to As a result of the matching, map matching information of the first map data and the second map data is determined.
  • the second submodule for determining the map matching information includes:
  • the map matching information determines a second sub-unit for determining that the real-time second semantic element matches the target fourth semantic element when the target second semantic element is the preset second semantic element, and according to As a result of the matching, map matching information of the first map data and the second map data is determined.
  • the vehicle further includes:
  • a clustering module configured to cluster the semantic elements of the at least two map data according to the positioning information to obtain a semantic element clustering result
  • the second map data determination module is configured to fuse the at least two map data according to the semantic element clustering result to obtain second map data.
  • the embodiment of the present invention detects whether there is preset second map data matching the first map data by acquiring the first map data collected in real time, and when detecting that the second map data matching the first map data is preset
  • map data is used, the map matching information of the first map data and the second map data is determined, and the vehicle is positioned and updated according to the map matching information, so as to realize the positioning update of the vehicle position.
  • Matching the first map data and the preset second map data can obtain more accurate positioning information, update the positioning according to the high-precision positioning information, improve the accuracy of the positioning information, and ensure the accuracy of the positioning information.
  • An embodiment of the present invention also provides a vehicle, which may include a processor, a memory, and a computer program stored in the memory and capable of running on the processor.
  • the computer program is executed by the processor to implement the above method for locating a vehicle.
  • An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the above method for locating a vehicle is implemented.
  • embodiments of the present invention may be provided as a method, an apparatus, or a computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • computer-usable storage media including, but not limited to, disk storage, CD-ROM, optical storage, etc.
  • Embodiments of the present invention are described with reference to flowcharts and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the present invention. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions.
  • These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing terminal equipment to produce a machine that causes the instructions to be executed by the processor of the computer or other programmable data processing terminal equipment Means are created for implementing the functions specified in a flow or flows of the flowcharts and/or a block or blocks of the block diagrams.
  • These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing terminal equipment to operate in a particular manner, such that the instructions stored in the computer readable memory result in an article of manufacture comprising instruction means, the The instruction means implement the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
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Abstract

Sont décrits ici un procédé de positionnement de véhicule et un véhicule. Le procédé de positionnement comprend les étapes consistant à : obtenir des premières données de carte acquises en temps réel (101) ; détecter si des secondes données de carte prédéfinies correspondant aux premières données de carte sont présentes ou non (102) ; lors de la détection des secondes données de carte prédéfinies correspondant aux premières données de carte, déterminer des informations de mise en correspondance de carte des premières données de carte et des secondes données de carte (103) ; et effectuer une mise à jour de positionnement de véhicule en fonction des informations de mise en correspondance de carte (104). L'invention permet de mettre à jour la position d'un véhicule. Des premières données de carte acquises en temps réel sont mises en correspondance avec des secondes données de carte prédéfinies, de telle sorte que des informations de positionnement de haute précision peuvent être obtenues, et une mise à jour de positionnement est effectuée en fonction des informations de positionnement de haute précision, ce qui permet d'améliorer la précision des informations de positionnement et d'assurer la précision de celles-ci.
PCT/CN2020/126947 2020-09-08 2020-11-06 Procédé et dispositif de positionnement de véhicule WO2022052283A1 (fr)

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