Vehicle positioning method, electronic equipment and vehicle

Abstract

The invention relates to the technical field of vehicles, and provides a vehicle positioning method, electronic equipment and a vehicle. The method comprises the following steps: acquiring a driving track of a vehicle, current attitude information, and a navigation map and an attitude map of an environment where the vehicle is located, wherein the attitude map is constructed based on attitude information of the vehicle at multiple positions; determining an intersection area of the vehicle in a navigation map based on the driving track of the vehicle and the navigation map; obtaining attitude information corresponding to a plurality of predicted positions included in the intersection area from an attitude map; and matching the current attitude information of the vehicle with the attitude information corresponding to the plurality of predicted positions, and determining a positioning result of the vehicle from the plurality of predicted positions. According to the method, the problems of positioning deviation and the like caused by too high computing power consumption can be avoided, and the reliability of automatic driving is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, specifically to a vehicle positioning method, electronic equipment, and a vehicle. Background Technology

[0002] With the development of autonomous driving technology, vehicle localization is the foundation for vehicles to achieve autonomous driving in unknown environments. Related technologies typically rely on multi-sensor fusion solutions such as visual sensors and LiDAR. However, this approach requires complex algorithms to process the collected data, leading to excessive computational power consumption during vehicle localization. This, in turn, affects the real-time performance of data processing, causing localization errors and reducing the reliability of autonomous driving. Summary of the Invention

[0003] This application provides a vehicle positioning method, electronic device, and vehicle to solve the technical problem of positioning deviation caused by excessive computing power consumption during vehicle positioning.

[0004] A first aspect of this application provides a vehicle positioning method, the method comprising: acquiring a vehicle's driving trajectory, current posture information, a navigation map of the vehicle's environment, and a posture map, wherein the posture map is constructed based on the vehicle's posture information at multiple locations; determining an intersection area of ​​the vehicle in the navigation map based on the vehicle's driving trajectory and the navigation map; acquiring posture information corresponding to multiple predicted locations included in the intersection area from the posture map; matching the vehicle's current posture information with the posture information corresponding to the multiple predicted locations, and determining the vehicle's positioning result from the multiple predicted locations.

[0005] In this embodiment, the intersection area where the vehicle is located can be roughly filtered out from the navigation map by comparing the vehicle's driving trajectory with the navigation map. By matching the vehicle's current attitude information with the attitude information corresponding to multiple predicted locations included in the intersection area, the vehicle's positioning result can be accurately determined from multiple predicted locations. Furthermore, this embodiment does not rely on visual sensors, LiDAR, or other sensors for vehicle positioning, thus reducing hardware costs and avoiding problems such as positioning errors caused by excessive computing power consumption, thereby improving the reliability of autonomous driving.

[0006] According to an embodiment of this application, determining the intersection area of ​​the vehicle in the navigation map based on the vehicle's driving trajectory and the navigation map includes: determining a first vector based on the vehicle's driving trajectory, and determining multiple second vectors based on multiple navigation points in the navigation map; calculating the similarity between the first vector and the multiple second vectors, and determining the second vector with the highest similarity as the target vector; and determining the intersection area where the navigation point is located based on the navigation point corresponding to the target vector.

[0007] This application embodiment can quickly determine the intersection area of ​​the vehicle in the navigation map by comparing the first vector corresponding to the driving trajectory with the second vector composed of multiple navigation points in the navigation map.

[0008] According to an embodiment of this application, the step of matching the current attitude information of the vehicle with the attitude information corresponding to the plurality of predicted positions, and determining the positioning result of the vehicle from the plurality of predicted positions, includes: determining the attitude deviation value corresponding to each predicted position based on the current attitude information and the attitude information corresponding to each predicted position; and determining the predicted position corresponding to the smallest attitude deviation value as the positioning result.

[0009] This application embodiment uses the vehicle's current attitude information and the attitude information corresponding to each predicted position to quantify the attitude deviation value corresponding to each predicted position, and then uses the attitude deviation value to determine the positioning result, thereby improving the accuracy of the positioning result.

[0010] According to an embodiment of this application, the method further includes: when the distance between the current position of the vehicle and a preset position is less than or equal to a first preset distance, acquiring measured attitude information of the vehicle during driving, wherein the measured attitude information includes at least one of the vehicle's pitch angle, roll angle, and heading angle; and constructing the attitude map based on the measured attitude information.

[0011] In this embodiment of the application, when the distance between the current position of the vehicle and the preset position is less than or equal to a first preset distance, a corresponding attitude map is constructed by measuring the attitude information of the vehicle during driving. This not only decouples the attitude of each dimension, but also controls the scale of the attitude map of each dimension, avoiding the slowdown in optimization speed caused by the excessive amount of data in the attitude map.

[0012] According to an embodiment of this application, the method further includes: obtaining first posture information of the vehicle when it is at any position in the navigation map, and obtaining second posture information of the vehicle at any position from the posture map; determining the actual position and orientation of the vehicle in the navigation map based on the first posture information and the second posture information; and updating the posture map based on the actual position and orientation.

[0013] This application embodiment can accurately determine the actual position and orientation of the vehicle in the navigation map by using the first and second attitude information when the vehicle is at any position in the navigation map. Based on the actual position and orientation, the attitude map can be accurately updated, thereby improving the accuracy of the attitude map.

[0014] According to an embodiment of this application, determining the actual position and orientation of the vehicle in the navigation map based on the first attitude information and the second attitude information includes: determining calibration parameters based on the first attitude information and the second attitude information, wherein the calibration parameters are used to correct the measurement deviation of the attitude sensor in the vehicle; and determining the actual position and orientation based on the calibration parameters and the second attitude information.

[0015] The embodiments of this application can obtain the optimal calibration parameters through the first attitude information and the second attitude information, and then adjust the second attitude information by obtaining the optimal calibration parameters to obtain the accurate actual pose.

[0016] According to an embodiment of this application, determining the calibration parameters based on the first attitude information and the second attitude information includes: constructing a deviation function based on the first attitude information and the second attitude information; minimizing the deviation function to obtain the calibration parameters.

[0017] In this embodiment of the application, a deviation function can be constructed using the first attitude information and the second attitude information. Then, by minimizing the deviation function, the optimal calibration parameters can be obtained.

[0018] According to an embodiment of this application, the method further includes: updating the attitude map according to any of the following conditions: if the vehicle's travel distance reaches a second preset distance, updating the attitude map; or updating the attitude map according to a preset time interval.

[0019] In this embodiment, the attitude map is updated when the vehicle travels a second preset distance or according to a preset time interval. This can prevent the attitude map from becoming less accurate due to prolonged periods without updates, thus helping to ensure the accuracy of the attitude map.

[0020] A second aspect of this application provides a vehicle positioning device, the device comprising: an acquisition unit, configured to acquire a vehicle's driving trajectory, current posture information, a navigation map of the vehicle's environment, and a posture map, the posture map being constructed based on the vehicle's posture information at multiple locations; a determination unit, configured to determine an intersection area of ​​the vehicle in the navigation map based on the vehicle's driving trajectory and the navigation map; the acquisition unit is further configured to acquire posture information corresponding to multiple predicted locations included in the intersection area from the posture map; the determination unit is further configured to match the vehicle's current posture information with the posture information corresponding to the multiple predicted locations, and determine the vehicle's positioning result from the multiple predicted locations.

[0021] A third aspect of this application provides an electronic device, the electronic device comprising: a memory for storing computer programs; and a processor for executing the computer programs stored in the memory to implement the vehicle positioning method.

[0022] A fourth aspect of this application provides a vehicle equipped with an electronic device for performing the vehicle positioning method.

[0023] A fifth aspect of this application provides a computer-readable storage medium storing a computer program that is executed by a processor in an electronic device to implement the vehicle positioning method. Attached Figure Description

[0024] Figure 1 This is an application scenario diagram of the vehicle positioning method provided in the embodiments of this application.

[0025] Figure 2 This is a flowchart of the vehicle positioning method provided in the embodiments of this application.

[0026] Figure 3 This is a flowchart of a method for constructing an attitude map according to an embodiment of this application.

[0027] Figure 4 This is a schematic diagram of an attitude map and navigation map provided in an embodiment of this application.

[0028] Figure 5 This is a schematic diagram of an attitude map and a navigation map provided in another embodiment of this application.

[0029] Figure 6 This is a flowchart of an embodiment of the attitude map update method provided in this application.

[0030] Figure 7 This is a flowchart illustrating the specific implementation method of step S602 provided in an embodiment of this application.

[0031] Figure 8 This is a flowchart of a vehicle positioning method provided in another embodiment of this application.

[0032] Figure 9 This is a functional block diagram of the vehicle positioning device provided in the embodiments of this application.

[0033] Figure 10 This is a schematic diagram of the structure of an electronic device for implementing a vehicle positioning method according to an embodiment of this application. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this application clearer, the application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0035] It should be noted that in this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and drawings of this application are used to distinguish similar objects, not to describe a specific order or sequence.

[0036] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner. Unless otherwise specified, the following embodiments and features described herein can be combined with each other.

[0037] In autonomous driving fields such as driverless vehicles and autonomous valet parking, vehicle localization is fundamental for achieving autonomous driving in unknown environments. Related technologies typically rely on multi-sensor fusion solutions using visual sensors, LiDAR, and other sensors. However, this approach requires complex algorithms to process the collected data, leading to excessive computational consumption during vehicle localization. This, in turn, affects the real-time performance of data processing, causing localization errors and reducing the reliability of autonomous driving. Furthermore, this method requires a costly hardware platform, resulting in significant expenses for vehicle localization.

[0038] To address the aforementioned issues, this application provides a vehicle positioning method that eliminates the need for visual sensors, lidar, or other sensors for vehicle positioning. This reduces hardware costs and avoids problems such as positioning errors caused by excessive computing power consumption, thereby improving the reliability of autonomous driving.

[0039] like Figure 1 The diagram shown is an application scenario diagram of a vehicle positioning method provided in an embodiment of this application.

[0040] In this embodiment, the vehicle positioning method can be applied to electronic device 100. Electronic device 100 can be installed in vehicle 200; for example, electronic device 100 can be an in-vehicle terminal in vehicle 200.

[0041] Vehicle 200 may also include an attitude sensor 101, which may include, but is not limited to, an inertial measurement unit (IMU). The IMU in attitude sensor 101 can obtain the vehicle's attitude information, including but not limited to, the vehicle's pitch angle, roll angle, and yaw angle. In practical applications, vehicle 200 may include more or fewer components, and this application does not impose specific limitations in this regard. For example, vehicle 200 may also include a microphone.

[0042] In another embodiment, the electronic device 100 may also be an electronic product that communicates with the vehicle 200. For example, the electronic device 100 may be a personal computer, tablet computer, smartphone, personal digital assistant (PDA), game console, interactive network television (Internet Protocol Television, IPTV), smart wearable device, etc.

[0043] Electronic device 100 may include network devices and / or user devices. Among them, network devices include, but are not limited to, a single network electronic device, a group of electronic devices consisting of multiple network electronic devices, or a cloud based on cloud computing consisting of a large number of hosts or network electronic devices.

[0044] The network where electronic device 100 is located may include, but is not limited to: the Internet, wide area network, metropolitan area network, local area network, and virtual private network (VPN).

[0045] like Figure 2 The diagram shown is a flowchart of a vehicle positioning method provided in one embodiment of this application. The order of the steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements.

[0046] S201, acquire the vehicle's driving trajectory, current attitude information, navigation map and attitude map of the vehicle's environment.

[0047] In at least one embodiment of this application, during vehicle operation, the electronic device can acquire the vehicle's corresponding driving trajectory on a navigation map. The electronic device can also acquire the vehicle's current attitude information from the vehicle's attitude sensors. The vehicle's current attitude information may include, but is not limited to, the vehicle's pitch angle, roll angle, and yaw angle at the current moment.

[0048] In at least one embodiment of this application, the electronic device can obtain a navigation map of the vehicle's environment from a global navigation satellite system. The electronic device can also obtain an attitude map of the vehicle's environment from a pre-built attitude map. The attitude map can be constructed based on the vehicle's attitude information at multiple locations; the method for constructing the attitude map can be referred to... Figure 3 The flowchart shown is for reference only. Attitude maps may include, but are not limited to: slope field maps, roll field maps, and heading field maps. Attitude maps and navigation maps have a positional correspondence. For example, the slope field map can carry the pitch angle corresponding to any position of the vehicle in the navigation map, the roll field map can carry the roll angle corresponding to any position of the vehicle in the navigation map, and the heading field map can carry the heading angle corresponding to any position of the vehicle in the navigation map.

[0049] Please see Figure 4 As shown, Figure 4 This is a schematic diagram of an attitude map and navigation map provided in one embodiment of this application. For example... Figure 4 As shown, the navigation map includes position A, the slope field map can carry the pitch angle corresponding to the vehicle being at position A, the roll field map can carry the roll angle corresponding to the vehicle being at position A, and the heading field map can carry the heading angle corresponding to the vehicle being at position A.

[0050] S202, based on the vehicle's driving trajectory and the navigation map, determines the intersection area of ​​the vehicle in the navigation map.

[0051] In at least one embodiment of this application, an electronic device determines the intersection area of ​​a vehicle in a navigation map based on the vehicle's driving trajectory and the navigation map, including: determining a first vector based on the vehicle's driving trajectory, and determining multiple second vectors based on multiple navigation points in the navigation map; calculating the similarity between the first vector and the multiple second vectors, and determining the second vector with the highest similarity as the target vector; and determining the intersection area where the navigation point is located based on the navigation point corresponding to the target vector.

[0052] In this embodiment, the electronic device can determine a first vector based on any trajectory point in the driving trajectory and the current trajectory point. For example, any trajectory point in the driving trajectory includes trajectory point A, and the current trajectory point is trajectory point B. The electronic device can determine the first vector based on the coordinates of any trajectory point and the coordinates of the current trajectory point. For example, assuming the coordinates of trajectory point A are (0, 0) and the coordinates of trajectory point B are (3, 4), the first vector AB formed by trajectory point A and trajectory point B can be determined.

[0053] In this embodiment, the electronic device can randomly select multiple navigation points from the navigation map, or it can select locations with specified markers from the navigation map as multiple navigation points. For example, the electronic device can use a turning point as a navigation point. The electronic device can determine multiple second vectors based on the coordinates of the multiple navigation points.

[0054] In this embodiment, during the process of determining the intersection area of ​​a vehicle in a navigation map, the electronic device can calculate the similarity between a first vector and multiple second vectors, and determine the second vector with the highest similarity as the target vector. The electronic device then determines the area where the navigation point corresponding to the target vector is located as the intersection area.

[0055] This application embodiment can quickly determine the intersection area where the vehicle is located in the navigation map by comparing the first vector corresponding to the driving trajectory with the second vector composed of multiple navigation points in the navigation map.

[0056] S203: Obtain attitude information corresponding to multiple predicted locations in the intersection area from the attitude map.

[0057] In at least one embodiment of this application, the electronic device can obtain attitude information corresponding to multiple predicted positions from the attitude map based on the positional correspondence between the navigation map and the attitude map.

[0058] S204, match the vehicle's current attitude information with the attitude information corresponding to multiple predicted positions, and determine the vehicle's positioning result from the multiple predicted positions.

[0059] In at least one embodiment of this application, the electronic device matches the current attitude information of the vehicle with the attitude information corresponding to multiple predicted positions, and determines the positioning result of the vehicle from the multiple predicted positions, including: determining the attitude deviation value corresponding to each predicted position based on the current attitude information and the attitude information corresponding to each predicted position; and determining the predicted position corresponding to the smallest attitude deviation value as the positioning result.

[0060] In this embodiment, the attitude deviation value corresponding to each predicted position can be expressed as: ,in, It can represent the first The attitude deviation value corresponding to each predicted position. It can represent the heading angle in the current attitude information. It can represent the first The heading angle in the attitude information corresponding to each predicted position. It can represent the weight corresponding to the heading angle. It can represent the roll angle in the current attitude information. It can represent the first The roll angle in the attitude information corresponding to each predicted position. It can represent the weight corresponding to the roll angle. It can represent the pitch angle in the current attitude information. It can represent the first The pitch angle in the attitude information corresponding to each predicted position. The weights corresponding to pitch angles can be represented. The weights corresponding to yaw angle, roll angle, and pitch angle can be set and adjusted according to actual needs, and this application does not impose any restrictions on this.

[0061] This application embodiment uses the vehicle's current attitude information and the attitude information corresponding to each predicted position to quantify the attitude deviation value corresponding to each predicted position, and then uses the attitude deviation value to determine the positioning result, thereby improving the accuracy of the positioning result.

[0062] In other embodiments of this application, the electronic device can determine the vehicle's position on a navigation map based on the vehicle's current attitude information. The vehicle's position on the navigation map may include: a first position determined based on a slope field map, a second position determined based on a roll field map, and a third position determined based on a heading field map.

[0063] Please see Figure 5 As shown, electronic devices can determine the vehicle's initial position on a navigation map based on the vehicle's current pitch angle, for example... Figure 5 Position b1 is shown. Electronic devices can determine a second position of the vehicle on the navigation map based on the vehicle's current roll angle, for example... Figure 5 The location shown is c1. Electronic devices can also determine the vehicle's third position on the navigation map based on the vehicle's current heading angle, for example... Figure 5 The position shown is d1.

[0064] In some embodiments of this application, if the first position, the second position, and the third position are all the same, the first position, the second position, or the third position can be determined as the vehicle's positioning result. Continuing with the above example, if the actual position b1, the actual position c1, and the actual position d1 are all the same, the actual position b1, the actual position c1, or the actual position d1 can be determined as the vehicle's positioning result.

[0065] In several embodiments of this application, the intersection area where the vehicle is located can be roughly filtered out from the navigation map by using the vehicle's driving trajectory and the navigation map. By matching the vehicle's current attitude information with the attitude information corresponding to multiple predicted positions included in the intersection area, the vehicle's positioning result can be accurately determined from multiple predicted positions. In addition, the embodiments of this application do not rely on sensors such as visual sensors and LiDAR for vehicle positioning. Therefore, hardware costs are reduced, and problems such as positioning errors caused by excessive computing power consumption are avoided, thus improving the reliability of autonomous driving.

[0066] like Figure 3 The diagram shown is a flowchart of a method for constructing an attitude map according to an embodiment of this application. The order of the steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements.

[0067] S301, when the distance between the vehicle's current position and the preset position is less than or equal to a first preset distance, acquire the vehicle's measured attitude information during driving.

[0068] In at least one embodiment of this application, the vehicle's current position can be determined in real time during its operation, and a preset position can also be set. The preset position can be an intersection, but this application does not impose specific limitations on the preset position. The electronic device can set a preset path based on the path between the vehicle's current position and the preset position. For example, the path between the vehicle's current position in a parking lot and the parking lot's exit can be used as the preset path. To enable the vehicle to drive autonomously along the preset path, a map of the environment corresponding to the preset path can be constructed.

[0069] In at least one embodiment of this application, in order to map the environment corresponding to the preset path, the electronic device can also set a first preset distance, which can be set and adjusted according to actual needs. When the distance between the vehicle's current position and the preset position is less than or equal to the first preset distance, the electronic device can acquire the vehicle's measured attitude information during driving based on the vehicle's attitude sensor. The measured attitude information includes, but is not limited to, the vehicle's pitch angle, roll angle, and yaw angle.

[0070] S302, constructs an attitude map based on measured attitude information.

[0071] In at least one embodiment of this application, the attitude map may include, but is not limited to, a slope field map, a roll field map, and a heading field map. The electronic device can construct a slope field map based on the vehicle's pitch angle during driving. The electronic device can construct a roll field map based on the vehicle's roll angle during driving. The electronic device can construct a heading field map based on the vehicle's heading angle during driving.

[0072] Please see Figure 4 As shown, Figure 4 This is a schematic diagram of an attitude map and navigation map provided in an embodiment of this application. The slope field map can carry the pitch angle corresponding to the vehicle being at any position in the navigation map, for example... Figure 4 As shown, the navigation map includes location A. The slope field map can carry the pitch angle corresponding to the vehicle being at location A. The roll field map can carry the roll angle corresponding to the vehicle being at any location on the navigation map, for example... Figure 4 As shown, the roll field map can display the roll angle corresponding to the vehicle being at position A. The heading field map can display the heading angle corresponding to the vehicle being at any position on the navigation map, for example... Figure 4 As shown, the heading field map can carry the heading angle corresponding to the vehicle's position A. This embodiment improves positioning robustness by associating the navigation map, slope field map, roll field map, and heading field map.

[0073] In other embodiments of this application, the electronic device can acquire measured attitude information of the vehicle during driving, including attitude information of the vehicle at multiple moments. The electronic device can also determine the vehicle's position at multiple moments based on a navigation map. Based on the attitude information and position at multiple moments, the electronic device can establish a correlation between the attitude map and the navigation map by performing time alignment between the attitude map and the navigation map.

[0074] In this embodiment of the application, when the distance between the vehicle's current position and the preset position is less than or equal to a first preset distance, a corresponding attitude map is constructed by measuring the vehicle's attitude information during driving. This not only decouples the attitude of each dimension but also controls the scale of the attitude map in each dimension, avoiding a decrease in optimization speed due to excessive data volume of the attitude map.

[0075] like Figure 6 The diagram shown is a flowchart of an attitude map update method according to an embodiment of this application. The order of steps in the flowchart can be changed, and some steps can be omitted, depending on different requirements.

[0076] S601, obtain the first attitude information of the vehicle when it is at any position in the navigation map, and obtain the second attitude information of the vehicle at any position from the attitude map.

[0077] In at least one embodiment of this application, the electronic device can determine any location from the navigation map at configured intervals. For example, the configured interval can be set and adjusted according to actual needs; for instance, the configured interval can be set to 0.2 meters. The electronic device can also randomly determine any location from the navigation map.

[0078] In at least one embodiment of this application, when the vehicle is at any location on the navigation map, the electronic device can obtain attitude angles from the vehicle's attitude sensors as first attitude information. The first attitude information is used to indicate the vehicle's attitude information at a first moment.

[0079] In at least one embodiment of this application, the attitude map stores the vehicle's attitude information at a second moment, which is prior to the first moment. An electronic device can obtain the second attitude information of the vehicle at any given location from the attitude map.

[0080] S602 determines the actual position and orientation of the vehicle in the navigation map based on the first attitude information and the second attitude information.

[0081] In at least one embodiment of this application, the electronic device determines the actual pose of the vehicle in the navigation map by referring to... Figure 7 The process shown is as follows: Figure 7 The process shown may include steps S6021-S6022: S6021, Based on the first attitude information and the second attitude information, determine the calibration parameters.

[0082] In some embodiments of this application, calibration parameters are used to correct measurement biases of attitude sensors in a vehicle.

[0083] In some embodiments of this application, the electronic device determines calibration parameters based on first attitude information and second attitude information, including: constructing a deviation function based on the first attitude information and second attitude information; minimizing the deviation function to obtain calibration parameters.

[0084] In this embodiment, the deviation function can be expressed as: Where l_yaw can represent the yaw angle in the first attitude information, l_roll can represent the roll angle in the first attitude information, l_pitch can represent the pitch angle in the first attitude information, m_yaw can represent the yaw angle in the second attitude information, m_roll can represent the roll angle in the second attitude information, m_pitch can represent the pitch angle in the second attitude information, and Tlm can represent the calibration parameter.

[0085] In the embodiments of this application, the electronic device can minimize the deviation function to obtain the optimal calibration parameter Tlm.

[0086] In this embodiment, a deviation function can be constructed using the first attitude information and the second attitude information. Then, by minimizing the deviation function, the optimal calibration parameters can be obtained.

[0087] S6022 determines the actual pose based on calibration parameters and second attitude information.

[0088] In some embodiments of this application, the electronic device can determine its actual pose based on calibration parameters and second pose information. The actual pose can be represented as... ,in, It can represent the actual pose. It can represent second attitude information. It can represent calibration parameters.

[0089] This embodiment can obtain the optimal calibration parameters through the first attitude information and the second attitude information, and then adjust the second attitude information by obtaining the optimal calibration parameters to obtain the accurate actual pose.

[0090] S603 updates the attitude map based on the actual pose.

[0091] In at least one embodiment of this application, a second preset distance can be set, which can be set and adjusted according to actual needs. The second preset distance can be used to determine the timing for attitude map optimization.

[0092] In at least one embodiment of this application, the attitude map is updated if the vehicle's travel distance reaches a second preset distance. This embodiment updates the attitude map when the vehicle's travel distance reaches the second preset distance, thus ensuring the accuracy of the attitude map.

[0093] In other embodiments of this application, the attitude map is updated according to a preset time interval. The preset time interval can be set and adjusted according to actual needs. This embodiment updates the attitude map according to a preset time interval, which can avoid the decrease in the accuracy of the attitude map caused by a long period of no update, thereby helping to ensure the accuracy of the attitude map.

[0094] In at least one embodiment of this application, the electronic device can adjust the second attitude information of the vehicle in the attitude map to the actual pose. This embodiment updates the attitude map using the actual pose, enabling continuous optimization of the attitude map and improving its accuracy.

[0095] In several embodiments of this application, the actual position and orientation of the vehicle in the navigation map can be accurately determined by using the first and second orientation information of the vehicle when it is at any position in the navigation map. Based on the actual position and orientation, the orientation map can be accurately updated, thereby improving the accuracy of the orientation map.

[0096] like Figure 8 The diagram shown is a flowchart of a vehicle positioning method according to another embodiment of this application. The order of the steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements.

[0097] S801 constructs an attitude map based on the vehicle's measured attitude information during driving.

[0098] In at least one embodiment of this application, during vehicle operation, if the distance between the vehicle's current position and a preset position is less than or equal to a first preset distance, the electronic device can acquire the vehicle's attitude measurement information during operation. The attitude measurement information includes at least one of the vehicle's pitch angle, roll angle, and yaw angle.

[0099] In at least one embodiment of this application, the electronic device constructs an attitude map based on measured attitude information. The method by which the electronic device constructs the attitude map can be referred to... Figure 3 The relevant content of step S302.

[0100] S802, locally associates the attitude map with the navigation map.

[0101] In at least one embodiment of this application, taking an intersection as an example, the electronic device can obtain map information between the current location and the preset location, as well as map information between the preset location and the destination, from a navigation map. Based on the map information between the current location and the preset location, and the map information between the preset location and the destination, the electronic device constructs an intersection scene map. Please refer to [link to relevant documentation]. Figure 4 The navigation map shown.

[0102] In at least one embodiment of this application, the electronic device can realize the relationship between the attitude map and the intersection field map by locally associating the attitude map with the navigation map. See also... Figure 4 As shown, the attitude map carries attitude information for any location in the intersection site map.

[0103] S803 determines whether the vehicle's travel distance has reached a preset threshold.

[0104] In at least one embodiment of this application, the electronic device determines whether the vehicle's travel distance has reached a preset threshold (also referred to as a "second preset distance"). If the vehicle's travel distance reaches the preset threshold, step S804 is executed; if the vehicle's travel distance does not reach the preset threshold, step S801 is executed.

[0105] S804, update the attitude map until the vehicle reaches its destination.

[0106] In at least one embodiment of this application, the electronic device updates the attitude map in a manner that can be referred to Figure 6The details of steps S601-S603 will not be repeated here. A destination can be set, for example, a parking lot exit can be set as the destination. Before the vehicle reaches the destination, the electronic device repeats steps S801-S804.

[0107] S805 stores the updated attitude map.

[0108] In at least one embodiment of this application, in order for the vehicle to drive autonomously, the electronic device can store an updated attitude map.

[0109] like Figure 9 The diagram shown is a functional block diagram of a vehicle positioning device according to an embodiment of this application. The vehicle positioning device 91 includes an acquisition unit 910, a determination unit 911, a construction unit 912, and an update unit 913. The module / unit referred to in this application refers to a module / unit that can be processed by a processor (e.g., ...). Figure 10 A series of computer program segments acquired by the processor 1101 shown, and capable of performing a fixed function, which are stored in memory (e.g., memory). Figure 10 In the memory 1102 shown.

[0110] In one embodiment, the acquisition unit 910 is used to acquire the vehicle's driving trajectory, current attitude information, navigation map of the vehicle's environment, and attitude map, wherein the attitude map is constructed based on the vehicle's attitude information at multiple locations; the determination unit 911 is used to determine the intersection area of ​​the vehicle in the navigation map based on the vehicle's driving trajectory and the navigation map; the acquisition unit 910 is also used to acquire attitude information corresponding to multiple predicted locations included in the intersection area from the attitude map; the determination unit 911 is also used to match the vehicle's current attitude information with the attitude information corresponding to the multiple predicted locations to determine the vehicle's positioning result from the multiple predicted locations.

[0111] In one embodiment, the determining unit 911 is specifically used for: determining a first vector based on the vehicle's driving trajectory, and determining multiple second vectors based on multiple navigation points in the navigation map; calculating the similarity between the first vector and the multiple second vectors, and determining the second vector with the highest similarity as the target vector; and determining the intersection area where the navigation point is located based on the navigation point corresponding to the target vector.

[0112] In one embodiment, the determining unit 911 is further configured to: determine the attitude deviation value corresponding to each predicted position based on the current attitude information and the attitude information corresponding to each predicted position; and determine the predicted position corresponding to the smallest attitude deviation value as the positioning result.

[0113] In one embodiment, the acquisition unit 910 is further configured to acquire the vehicle's measured attitude information during driving when the distance between the vehicle's current position and the preset position is less than or equal to a first preset distance. The measured attitude information includes at least one of the vehicle's pitch angle, roll angle, and yaw angle. The construction unit 912 is configured to construct an attitude map based on the measured attitude information.

[0114] In one embodiment, the acquisition unit 910 is further configured to acquire first posture information of the vehicle when it is at any position in the navigation map, and acquire second posture information of the vehicle at any position from the posture map; the determination unit 911 is further configured to determine the actual posture of the vehicle in the navigation map based on the first posture information and the second posture information; and the update unit 913 is configured to update the posture map based on the actual posture.

[0115] In one embodiment, the determining unit 911 is further specifically configured to: determine calibration parameters based on the first attitude information and the second attitude information, wherein the calibration parameters are used to correct the measurement deviation of the attitude sensor in the vehicle; and determine the actual pose based on the calibration parameters and the second attitude information.

[0116] In one embodiment, the determining unit 911 is further specifically used to: construct a deviation function based on the first attitude information and the second attitude information; and minimize the deviation function to obtain calibration parameters.

[0117] In one embodiment, the updating unit 913 is further configured to update the attitude map according to any of the following conditions: if the vehicle's travel distance reaches a second preset distance, update the attitude map; or update the attitude map according to a preset time interval.

[0118] In several embodiments of this application, the intersection area where the vehicle is located can be roughly filtered out from the navigation map by using the vehicle's driving trajectory and the navigation map. By matching the vehicle's current attitude information with the attitude information corresponding to multiple predicted positions included in the intersection area, the vehicle's positioning result can be accurately determined from multiple predicted positions. In addition, the embodiments of this application do not rely on sensors such as visual sensors and LiDAR for vehicle positioning. Therefore, hardware costs are reduced, and problems such as positioning errors caused by excessive computing power consumption are avoided, thus improving the reliability of autonomous driving.

[0119] like Figure 10 The diagram shown is a schematic diagram of the structure of an electronic device that implements the vehicle positioning method of this application.

[0120] In one embodiment of this application, the electronic device 100 includes, but is not limited to, a memory 1102, a processor 1101, and a computer program, such as a vehicle location program, stored in the memory 1102 and executable on the processor 1101.

[0121] Those skilled in the art will understand that the schematic diagram is merely an example of the electronic device 100 and does not constitute a limitation on the electronic device 100. It may include more or fewer components than shown, or combine certain components, or different components. For example, the electronic device 100 may also include input / output devices, network access devices, buses, etc.

[0122] Processor 1101 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. Processor 1101 is the computing core and control center of electronic device 100, connecting various parts of electronic device 100 through various interfaces and lines, and acquiring the operating system of electronic device 100 and various installed application programs and program code.

[0123] Processor 1101 acquires the operating system and various installed applications of electronic device 100. Processor 1101 acquires these applications to implement the steps in the various vehicle positioning method embodiments described above, for example... Figures 2 to 4 , Figure 6 , Figure 8 The steps are shown.

[0124] The memory 1102 can be used to store computer programs and / or modules. The processor 1101 implements various functions of the electronic device 100 by running or retrieving the computer programs and / or modules stored in the memory 1102, and by calling the data stored in the memory 1102. The memory 1102 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 1102 may include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0125] The memory 1102 can be the external memory and / or internal memory of the electronic device 100. Furthermore, the memory 1102 can be a memory in physical form, such as a memory stick, a TF card (Trans-flash Card), etc.

[0126] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent workpieces, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above.

[0127] Computer programs include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), and random access memory (RAM).

[0128] For example, a computer program may be divided into one or more modules / units, one or more of which are stored in memory 1102 and executed by processor 1101 to complete this application. One or more modules / units may be a series of computer program segments capable of performing specific functions, which describe the execution process of the computer program in electronic device 100. For example, the computer program may be divided into an acquisition unit 910, a determination unit 911, a construction unit 912, and an update unit 913.

[0129] For detailed information on the functions of each module / unit, please refer to the above text. Figure 2 , Figure 3 , Figures 6 to 8 The detailed description will not be repeated here.

[0130] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0131] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0132] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0133] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of this application is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within this application. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0134] Furthermore, it is clear that the word "including" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices can also be implemented by a single unit or device through software or hardware. Terms such as "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0135] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application.

Claims

1. A vehicle positioning method characterized by comprising: The method comprises: obtaining a driving track of a vehicle, current attitude information, a navigation map of an environment where the vehicle is located, and an attitude map, the attitude map being constructed based on attitude information of the vehicle at multiple positions; determining a junction area of the vehicle in the navigation map based on the driving track of the vehicle and the navigation map; obtaining attitude information corresponding to multiple predicted positions included in the junction area from the attitude map; matching the current attitude information of the vehicle with the attitude information corresponding to the multiple predicted positions, and determining a positioning result of the vehicle from the multiple predicted positions.

2. The vehicle positioning method according to claim 1, characterized by, The determination of the junction area of the vehicle in the navigation map based on the driving track of the vehicle and the navigation map comprises: determining a first vector based on the driving track of the vehicle, and determining multiple second vectors based on multiple navigation points in the navigation map; calculating the similarity of the first vector and the multiple second vectors, and determining a target vector with the maximum similarity as the second vector; determining a junction area where the navigation point corresponding to the target vector is located according to the navigation point.

3. The vehicle positioning method according to claim 1, characterized by, The matching of the current attitude information of the vehicle with the attitude information corresponding to the multiple predicted positions, and the determination of the positioning result of the vehicle from the multiple predicted positions comprise: determining an attitude deviation value corresponding to each predicted position according to the current attitude information and the attitude information corresponding to each predicted position; determining a predicted position corresponding to the minimum attitude deviation value as the positioning result.

4. The vehicle positioning method according to claim 1, characterized by, The method further comprises: when the distance between the current position of the vehicle and a preset position is less than or equal to a first preset distance, obtaining measurement attitude information of the vehicle during driving, the measurement attitude information comprising at least one of a pitch angle, a roll angle, and a heading angle of the vehicle; constructing the attitude map based on the measurement attitude information.

5. The vehicle positioning method according to any one of claims 1 to 4, characterized by, The method further comprises: obtaining first attitude information when the vehicle is at any position in the navigation map, and obtaining second attitude information corresponding to the vehicle at the any position from the attitude map; determining an actual pose of the vehicle in the navigation map based on the first attitude information and the second attitude information; updating the attitude map based on the actual pose.

6. The vehicle positioning method according to claim 5, characterized by, The determination of the actual pose of the vehicle in the navigation map based on the first attitude information and the second attitude information comprises: determining a calibration parameter based on the first attitude information and the second attitude information, the calibration parameter being used to correct measurement deviation of an attitude sensor in the vehicle; determining the actual pose based on the calibration parameter and the second attitude information.

7. The vehicle positioning method according to claim 6, characterized by, The determination of the calibration parameter based on the first attitude information and the second attitude information comprises: constructing a deviation function based on the first attitude information and the second attitude information; minimizing the deviation function to obtain the calibration parameter.

8. The vehicle positioning method according to any one of claims 1 to 7, characterized by, The method further comprises: updating the attitude map according to any one of the following conditions: if the driving distance of the vehicle reaches a second preset distance, updating the attitude map; or According to a preset time interval, the pose map is updated.

9. An electronic device, comprising: Comprise: A memory storing a computer program, and a processor, wherein the processor implements the vehicle positioning method according to any one of claims 1 to 8 when executing the computer program.

10. A vehicle characterized by comprising: The electronic device is configured in the vehicle according to claim 9.

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