Vehicle positioning method and device, vehicle and medium

Abstract

The invention provides a vehicle positioning method and device, a vehicle and a medium, and relates to the technical field of automatic driving, and the method comprises the steps: obtaining first position data, collected by a sensor on the vehicle, of the vehicle under a local coordinate system; the coordinate conversion relation can realize conversion between the local coordinate system and the global coordinate system, and according to the coordinate conversion relation, coordinate conversion is performed on the first position data under the local coordinate system, so that the second position data of the vehicle under the global coordinate system can be obtained. Compared with a mode in the prior art, the sensor used for collecting the first position data is not interfered by factors such as a network, a shielding object and light, and the positioning accuracy can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of autonomous driving technology, and in particular to a vehicle positioning method, device, vehicle and medium. Background Art

[0002] With the continuous development of my country's economy and the improvement of people's living standards, driving has become the preferred way of travel for many people. In order to relieve the fatigue of drivers from long-term driving, autonomous driving technology has been more widely used in vehicles in recent years. The current autonomous driving technology mainly uses satellite positioning for positioning. However, satellite positioning is suitable for open scenes. For scenes with limited satellite signals, this method is difficult to meet the positioning needs. Summary of the invention

[0003] In order to overcome the problems existing in the related art, the present disclosure provides a vehicle positioning method, device, vehicle and medium.

[0004] According to a first aspect of an embodiment of the present disclosure, a vehicle positioning method is provided, the method comprising: acquiring first position data of the vehicle in a local coordinate system collected by a sensor on the vehicle; performing coordinate transformation on the first position data in the local coordinate system according to a coordinate transformation relationship to obtain second position data of the vehicle in a global coordinate system, wherein the coordinate transformation relationship is used for transformation between the local coordinate system and the global coordinate system.

[0005] Optionally, the method further includes: updating the coordinate transformation relationship to obtain an updated coordinate transformation relationship.

[0006] Optionally, updating the coordinate transformation relationship to obtain an updated coordinate transformation relationship includes: acquiring the actual driving trajectory of the vehicle based on the second position data; performing trajectory matching based on the actual driving trajectory and a preset driving trajectory to obtain adjustment parameters for the actual driving trajectory; updating the coordinate transformation relationship based on the adjustment parameters to obtain the updated coordinate transformation relationship.

[0007] Optionally, updating the coordinate transformation relationship to obtain an updated coordinate transformation relationship includes: when the actual driving trajectory satisfies a straight-line driving condition, obtaining an angle between the actual driving trajectory and the preset driving trajectory; and updating the angle transformation relationship in the coordinate transformation relationship according to the angle to obtain the updated coordinate transformation relationship.

[0008] Optionally, updating the coordinate transformation relationship to obtain an updated coordinate transformation relationship includes: when the actual driving trajectory does not satisfy the straight-line driving condition, obtaining the displacement difference between the actual driving trajectory and the preset driving trajectory; updating the displacement transformation relationship in the coordinate transformation relationship according to the displacement difference to obtain the updated coordinate transformation relationship.

[0009] Optionally, the straight-line driving condition includes that the curvature of the driving trajectory is less than a preset curvature.

[0010] Optionally, obtaining the actual driving trajectory of the vehicle includes obtaining first position data collected by the sensor at each of multiple consecutive moments; performing coordinate transformation on the multiple first position data based on the coordinate transformation relationship to obtain second position data corresponding to each of the multiple consecutive moments; and obtaining the actual driving trajectory of the vehicle based on the multiple second position data.

[0011] Optionally, the sensor includes at least one of the following: an inertial measurement unit, a wheel speed meter.

[0012] According to a second aspect of an embodiment of the present disclosure, a vehicle positioning device is provided, the device comprising: an acquisition module, for acquiring first position data of the vehicle in a local coordinate system acquired by a sensor on the vehicle; a conversion module, for performing coordinate conversion on the first position data in the local coordinate system according to a coordinate conversion relationship, to obtain second position data of the vehicle in a global coordinate system, wherein the coordinate conversion relationship is used for conversion between the local coordinate system and the global coordinate system; and a driving module, for controlling the vehicle to drive on a preset driving trajectory in the global coordinate system according to the second position data.

[0013] According to a third aspect of an embodiment of the present disclosure, a vehicle is provided, comprising: a processor; and a memory for storing processor executable instructions; wherein the processor is configured to implement the steps of the method described in the first aspect when executed.

[0014] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the method provided in the first aspect of the present disclosure are implemented.

[0015] The present invention discloses a vehicle positioning method, device, vehicle and medium, which obtains the first position data of the vehicle in the local coordinate system collected by the sensor on the vehicle; the coordinate transformation relationship can realize the transformation between the local coordinate system and the global coordinate system, and the first position data in the local coordinate system is transformed according to the coordinate transformation relationship to obtain the second position data of the vehicle in the global coordinate system. Compared with the existing technology, the sensor used to collect the first position data is not interfered by factors such as the network, obstructions, and light, which can improve the accuracy of positioning.

[0016] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0018] Figure 1 is a flow chart of a vehicle positioning method shown in an exemplary embodiment of the present disclosure;

[0019] Figure 2 is a flow chart of a vehicle positioning method shown in another exemplary embodiment of the present disclosure;

[0020] Figure 3 It is a schematic diagram of trajectory divergence;

[0021] Figure 4 According to an exemplary embodiment Figure 2 A flowchart of the steps of step S230 in FIG.

[0022] Figure 5 is a flow chart of a vehicle positioning method shown in another exemplary embodiment of the present disclosure;

[0023] Figure 6 is a block diagram of a vehicle positioning device according to an exemplary embodiment;

[0024] Figure 7 The invention is a block diagram of a vehicle used for a vehicle positioning method according to an exemplary embodiment. DETAILED DESCRIPTION

[0025] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0026] With the continuous development of my country's economy and the improvement of people's living standards, driving has become the preferred way of travel for many people. In order to relieve the fatigue of drivers from long-term driving, autonomous driving technology has been more widely used in vehicles in recent years. The current autonomous driving technology mainly uses satellite positioning for positioning. However, satellite positioning is suitable for open scenes. For scenes with limited satellite signals, this method is difficult to meet the positioning needs.

[0027] Current autonomous driving technology can also use visual positioning technology to match the perceived semantic information with a pre-established map to obtain the vehicle's position on the map. In the case of occlusion or interference from external light (such as backlight), the visual positioning method will be greatly disturbed.

[0028] The current autonomous driving technology also uses the laser radar positioning method. However, the laser radar hardware needs to be installed on the car, and the cost of laser radar hardware is relatively high, which naturally increases the hardware cost of the vehicle.

[0029] See also Figure 1 , Figure 1 is a flow chart of a vehicle positioning method shown in an exemplary embodiment of the present disclosure, and the vehicle positioning method can be applied to Figure 6 The vehicle positioning device 100 shown, Figure 7 The vehicle 200 shown, Figure 7 The computing platform 250 and the computer readable storage medium in the embodiment are used in a vehicle as an example. Figure 1 The process shown is described in detail, and the vehicle positioning method can specifically include the following steps:

[0030] Step S110: Acquire first position data of the vehicle in a local coordinate system collected by a sensor on the vehicle.

[0031] The local coordinate system is a coordinate system established relative to a specific reference of the sensor or vehicle, and the first position data is used to describe the relative position relative to the aforementioned specific reference. Optionally, after the vehicle turns on the automatic driving mode, the position of the sensor at the moment the automatic driving mode is turned on is the origin of the local coordinate system. Alternatively, the position of the sensor at the moment the vehicle is started this time is the origin of the local coordinate system. The first position data in the local coordinate system records the distance the sensor moves in the direction of motion. Since the sensor is installed on the vehicle, the first position data can also record the distance the vehicle moves in the direction of motion. For example, the first position data records that the vehicle moves x meters in the first direction and then moves y meters in the second direction of motion, where x and y are both positive numbers.

[0032] When the vehicle does not start the automatic driving mode, the first position data is used to record the mileage or path of the vehicle. When the vehicle starts the automatic driving mode, the first position data can also be used for the automatic driving in the subsequent steps.

[0033] Step S120: performing coordinate transformation on the first position data in the local coordinate system according to a coordinate transformation relationship to obtain second position data of the vehicle in the global coordinate system, wherein the coordinate transformation relationship is used for transformation between the local coordinate system and the global coordinate system.

[0034] The global coordinate system and the local coordinate system are a set of relative concepts. The global coordinate system is a fixed reference coordinate, that is, the global coordinate system is a coordinate system that uses the earth as a reference. The two coordinate systems can be transformed through a coordinate transformation relationship. The transformation relationship can be in the form of a transformation matrix. In this step, according to the coordinate transformation relationship, the first position data in the local coordinate system is transformed to obtain the second position data in the global coordinate system. That is, through the coordinate transformation relationship, the first position data is projected into the second position data. The second position data represents the position information in the global coordinate system of the vehicle.

[0035] The vehicle positioning method provided in this embodiment obtains the first position data in the local coordinate system collected by the sensor on the vehicle; the coordinate transformation relationship can realize the transformation between the local coordinate system and the global coordinate system, and the first position data in the local coordinate system is transformed according to the coordinate transformation relationship to obtain the second position data in the global coordinate system. Compared with the existing technology, the sensor used to collect the first position data is not interfered by factors such as the network, obstructions, and light, which can improve the accuracy of positioning.

[0036] Optionally, the user operates on the central control screen of the vehicle to turn on the automatic driving mode. Alternatively, the user operates on a terminal device connected to the vehicle to turn on the automatic driving mode of the vehicle.

[0037] Optionally, the vehicle can also automatically enter the automatic driving mode. Exemplarily, the vehicle collects the driver's biometric information, and uses the biometric information to identify whether the driver is in a state of fatigue. If the driver is in a state of fatigue, the vehicle automatically turns on the automatic driving mode. For example, the camera on the vehicle collects the user's facial image, and uses image recognition technology to recognize the facial image to obtain a recognition result. If the recognition result indicates that the driver is in a state of fatigue, the vehicle automatically turns on the automatic driving mode. On highways, due to long-term driving or the need for high speeds, more energy is consumed, and the driver usually feels tired. If the driver continues to drive in a tired state, there may be safety hazards. After recognizing that the driver is in a state of fatigue, the vehicle automatically turns on the automatic driving mode to assist driving, thereby improving driving safety.

[0038] Automatic driving is an assisted driving function. When the user is detected to be in a non-fatigued state, the vehicle is controlled to exit the automatic driving mode according to the user's operation on the vehicle's central control screen or the terminal device connected to the vehicle. Alternatively, the vehicle automatically exits the automatic driving mode after the user operates the vehicle's steering wheel, gear position, accelerator, etc.

[0039] Optionally, the method further includes: controlling the driving of the vehicle based on the second position data.

[0040] Optionally, based on the second position data, the vehicle is controlled to travel according to a preset driving trajectory in the global coordinate system, and the preset driving trajectory in the global coordinate system is the trajectory that the vehicle is expected to travel. In one embodiment, the preset driving trajectory may be a trajectory planned on the navigation. Exemplarily, the driver navigates on the central control screen in advance, and the vehicle plans a driving path. The vehicle turns on the automatic driving mode during driving, and after the automatic driving mode is turned on, the vehicle uses the remaining path on the driving path as the preset driving trajectory. For example, during navigation, the driving path is planned to be from address A to address C. When driving to address B on this section of the path, the vehicle enters the automatic driving mode and determines the remaining path, i.e., address B to address C, as the preset driving trajectory.

[0041] In another embodiment, the preset driving trajectory may also be determined from a historical path. For example, a path of the vehicle before the automatic driving mode is turned on is obtained, and a path with a high degree of overlap with the historical path is searched from the path as the preset driving trajectory.

[0042] According to the second position data, the vehicle is controlled to travel on a preset driving trajectory. In one embodiment, the driving trajectory of the vehicle is corrected according to the second position data. For example, it is determined whether the second position data is on the preset driving trajectory. If the second position data is outside the preset driving trajectory, such as the shortest distance between the position represented by the second position data and the preset driving trajectory is greater than the preset distance, which may be 5 meters, 10 meters, etc., then the second position data may be considered to be outside the preset driving trajectory. In this case, the trajectory of the vehicle is corrected and the vehicle is controlled to travel along the preset driving trajectory.

[0043] In another embodiment, based on the second position data, it is determined whether the position represented by the second position data is the terminal of the preset trajectory. If the position represented by the second position data is the terminal of the preset trajectory, the driving is terminated.

[0044] Based on the above embodiments, the present disclosure also provides a vehicle positioning method, see Figure 2 , the vehicle positioning method may specifically include the following steps:

[0045] Step S210: Acquire first position data in a local coordinate system collected by a sensor on the vehicle.

[0046] Step S220: performing coordinate transformation on the first position data in the local coordinate system according to a coordinate transformation relationship to obtain second position data in the global coordinate system, wherein the coordinate transformation relationship is used for transformation between the local coordinate system and the global coordinate system.

[0047] The specific description of steps S210 to S220 can refer to steps S110 to S120 and will not be repeated here.

[0048] Step S230: Update the coordinate transformation relationship to obtain an updated coordinate transformation relationship.

[0049] During the driving process of the vehicle, the position collected by the sensor in the local coordinate system may be divergent, which means that the coordinate transformation relationship is not applicable after the divergence. Figure 3 ,During the automatic driving process of the vehicle, a preset driving trajectory is set in advance, and the vehicle is expected to ,drive along the preset driving trajectory, but in fact, the vehicle drives along the actual driving trajectory. ,In the initial stage of driving, e.g. Figure 3At time t1 in the figure, the preset driving trajectory and the actual driving trajectory overlap. As the driving process progresses, at time t2, the two trajectories begin to diverge. At time t3, the two trajectories have completely diverged. At this time, the conversion relationship has become invalid. In this step, the coordinate conversion relationship can be updated. The update of the coordinate conversion relationship can be performed at a preset frequency. For example, the preset frequency is 1HZ, which can be understood as updating the coordinate conversion relationship once per second.

[0050] In one embodiment, see Figure 4 , step S240 may include the following steps:

[0051] Step S231: Acquire the actual driving trajectory of the vehicle according to the second position data.

[0052] As a method, the first position data collected by the sensor at each of the multiple continuous moments is obtained. Then, according to the coordinate transformation relationship, the multiple first position data are coordinate transformed to obtain the second position data corresponding to each of the multiple continuous moments. According to the multiple second position data, the actual driving trajectory of the vehicle is obtained, that is, the second position data of the previous moment is connected with the second position data of the next moment to draw the actual driving trajectory.

[0053] Step S232: performing trajectory matching according to the actual driving trajectory and the preset driving trajectory to obtain adjustment parameters for the actual driving trajectory.

[0054] Matching the actual driving trajectory with the preset driving trajectory aims to process the actual driving trajectory to coincide with the preset driving trajectory through translation, rotation and other processing methods. Then, the adjustment parameters obtained for the actual driving trajectory represent the translation distance and / or rotation angle of the actual driving trajectory.

[0055] Optionally, a Hidden Markov Model (HMM) can be used to match the driving trajectory with the preset driving trajectory, that is, with the current positioning point of the sensor as the center, search for sections within a preset range (e.g., a range of 500 meters) on the parking map as candidate sections, project the vehicle on the candidate sections, and use the Viterbi algorithm to calculate the most likely section to travel. HMM involves modeling the process of a path through many possible states. The output of the HMM model is each section, and the input of the HMM model is the vehicle position measurement value. The HMM model is intended to match each first position data with the corresponding second position data. When the above matching is completed, the projection point of the current positioning point on the corresponding section can be used as the position point of the vehicle on the map.

[0056] Step S233: updating the coordinate transformation relationship according to the adjustment parameter to obtain the updated coordinate transformation relationship.

[0057] After the trajectory diverges, the actual driving trajectory and the preset driving trajectory may not overlap. The coordinate transformation relationship is updated according to the adjustment parameters. The actual driving trajectory and the preset driving trajectory can be overlapped through the updated transformation relationship, which can solve the trajectory divergence problem.

[0058] Optionally, the coordinate transformation relationship includes an angle component and a displacement component, that is, the coordinate transformation relationship includes an angle transformation relationship and a displacement transformation relationship. In the process of converting from a local coordinate system to a global coordinate system, the angle transformation relationship is used to rotate the actual driving trajectory, and optionally, the angle transformation relationship can be in the form of an angle matrix. The displacement transformation relationship is used to translate the actual driving trajectory, and optionally, the displacement transformation relationship can be in the form of a displacement matrix.

[0059] If both the angle transformation relationship and the displacement transformation relationship in the coordinate transformation relationship are updated, and the updated transformation relationship is used to obtain the second position data, and then the driving is controlled based on the second position data, if the path changes too quickly, the driver and passengers in the vehicle will experience bumps, sharp turns, etc., which will reduce the driving and riding experience. Therefore, only one of the angle transformation relationship and the displacement transformation relationship may be updated, as follows.

[0060] In another embodiment, when the actual driving trajectory satisfies the straight driving condition, the actual driving trajectory is considered to be a straight line, and the angle between the actual driving trajectory and the preset driving trajectory is obtained, for example, the angle may be 30 degrees, 20 degrees, etc. Optionally, the angle may be calculated using an iterative closest point (ICP) algorithm. The angle conversion relationship in the coordinate conversion relationship is updated according to the angle to obtain the updated coordinate conversion relationship.

[0061] Optionally, if the coordinate transformation relationship is updated in one step, the above-mentioned bumps, sharp turns, etc. may occur. The update of the coordinate transformation relationship can be performed in multiple update cycles, that is, in the first update cycle, the updated coordinate transformation relationship is obtained, and the angle between the path obtained by the updated coordinate transformation relationship and the actual driving trajectory is smaller than the angle before the update, which can be understood as a small-scale adjustment of the angle. After the update in the first update cycle, the update continues in the next update cycle, and through multiple update cycles, the ideal coordinate transformation relationship is gradually obtained.

[0062] Optionally, the straight-line driving condition includes that the curvature of the driving trajectory is less than a preset curvature.

[0063] In another embodiment, when the actual driving trajectory does not meet the straight driving condition, it is considered that the actual driving trajectory is not a straight line, that is, the actual driving trajectory is a curve, a turn, an uphill, a downhill, etc. trajectory, and the displacement difference between the actual driving trajectory and the preset driving trajectory is obtained. The displacement transformation relationship in the coordinate transformation relationship is updated according to the displacement difference to obtain the updated coordinate transformation relationship.

[0064] It should be noted that, in this embodiment, the updated coordinate transformation relationship obtained replaces the coordinate transformation relationship for coordinate updating.

[0065] Optionally, in this embodiment, the update of the coordinate transformation relationship can be real-time, which can effectively avoid the problem of trajectory divergence, thereby avoiding the invalidation of the coordinate transformation relationship caused by the accumulated error. The coordinate transformation relationship can also be updated according to a preset period. Within the preset transformation relationship, the deviation between the actual driving trajectory and the preset driving trajectory is less than the preset deviation, and the preset deviation is not enough to cause the problem of trajectory divergence. Therefore, updating the coordinate transformation relationship according to the preset period can also effectively avoid the problem of trajectory divergence, thereby avoiding the invalidation of the coordinate transformation relationship caused by the accumulated error.

[0066] In this embodiment, the coordinate transformation relationship is updated to prevent cumulative errors from causing the coordinate transformation relationship to become invalid, thereby ensuring the accuracy of positioning.

[0067] Optionally, the sensor includes at least one of the following: an inertial measurement unit (IMU) and an odograph (ODO). Compared with a laser radar, the IMU and ODO of this embodiment have the advantage of low cost. The use of IMU and ODO can reduce the manufacturing cost of the vehicle. In addition, in traditional vehicles, an inertial measurement unit and a wheel speed meter are usually installed, and a laser radar is generally not installed. If a traditional vehicle is to be modified for autonomous driving, the inertial measurement unit and the wheel speed meter can be directly reused without adding a laser radar, thereby reducing the modification cost.

[0068] In conjunction with the automatic parking scenario, the present disclosure provides a vehicle automatic positioning method, please refer to Figure 5, the method includes: obtaining a coordinate transformation relationship. During the movement of the vehicle, the position is updated, that is, the position collected by the sensor on the vehicle changes, which can be understood as the sensor on the vehicle collecting the first position data, and the first position data is the data in the local coordinate system. The second position data is obtained by converting the trajectory to the global coordinate system, that is, converting the first position data to the global coordinate system through the trajectory. HMM trajectory matching. Then the coordinate transformation relationship is updated, and the updated coordinate transformation relationship can transform the newly collected position data. In this embodiment, the updated coordinate transformation relationship is used for coordinate transformation, and the coordinate transformation result is used to control automatic parking.

[0069] To implement the above method embodiment, this embodiment proposes a vehicle positioning device, see Figure 6 , Figure 6 is a block diagram of a vehicle positioning device according to an exemplary embodiment, wherein the vehicle positioning device 100 includes: a collection module 110 and a conversion module 120;

[0070] The acquisition module 110 is used to acquire first position data of the vehicle in a local coordinate system acquired by a sensor on the vehicle;

[0071] The conversion module 120 is used to perform coordinate conversion on the first position data in the local coordinate system according to a coordinate conversion relationship to obtain second position data of the vehicle in the global coordinate system, wherein the coordinate conversion relationship is used for conversion between the local coordinate system and the global coordinate system.

[0072] Optionally, the vehicle positioning device 100 further includes: an updating module;

[0073] The updating module is used to update the coordinate transformation relationship to obtain an updated coordinate transformation relationship.

[0074] Optionally, the updating module includes: a trajectory acquisition module and a transformation relationship updating module;

[0075] A trajectory acquisition module, used to acquire the actual driving trajectory of the vehicle according to the second position data;

[0076] A matching module, used for performing trajectory matching according to the actual driving trajectory and the preset driving trajectory to obtain adjustment parameters for the actual driving trajectory;

[0077] The transformation relationship updating module is used to update the coordinate transformation relationship according to the adjustment parameter to obtain the updated coordinate transformation relationship.

[0078] Optionally, the conversion relationship updating module includes a first conversion relationship updating module;

[0079] An angle acquisition module, used for acquiring an angle between the actual driving trajectory and the preset driving trajectory when the actual driving trajectory meets the straight driving condition;

[0080] The transformation relationship updating module is used to update the angle transformation relationship in the coordinate transformation relationship according to the included angle to obtain the updated coordinate transformation relationship.

[0081] Optionally, the conversion relationship updating module includes a second conversion relationship updating module;

[0082] A displacement difference acquisition module, used for acquiring a displacement difference between the actual driving trajectory and the preset driving trajectory when the actual driving trajectory does not meet the straight-line driving condition;

[0083] The second transformation relationship updating module is used to update the displacement transformation relationship in the coordinate transformation relationship according to the displacement difference to obtain the updated coordinate transformation relationship.

[0084] Optionally, the straight-line driving condition includes that the curvature of the driving trajectory is less than a preset curvature.

[0085] Optionally, the trajectory acquisition module includes: a first position data acquisition module, a second position data acquisition module and an actual driving trajectory acquisition module;

[0086] A first position data acquisition module, used to acquire first position data collected by the sensor at each moment in a plurality of consecutive moments;

[0087] A second position data acquisition module, configured to perform coordinate transformation on the plurality of first position data according to the coordinate transformation relationship, so as to obtain second position data corresponding to each moment in the plurality of continuous moments;

[0088] The actual driving trajectory acquisition module is used to obtain the actual driving trajectory of the vehicle based on a plurality of second position data.

[0089] Optionally, the sensor includes at least one of the following: an inertial measurement unit, a wheel speed meter.

[0090] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0091] The present disclosure also provides a computer-readable storage medium on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the above method provided by the present disclosure are implemented.

[0092] Figure 72 is a block diagram of a vehicle for a vehicle positioning method according to an exemplary embodiment. For example, vehicle 200 may be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles. Vehicle 200 may be an autonomous vehicle or a semi-autonomous vehicle.

[0093] Reference Figure 7 , the vehicle 200 may include various subsystems, such as an infotainment system 210, a perception system 220, a decision control system 230, a drive system 240, and a computing platform 250. The vehicle 200 may also include more or fewer subsystems, and each subsystem may include multiple components. In addition, each subsystem and each component of the vehicle 200 may be interconnected by wire or wireless means.

[0094] In some embodiments, the infotainment system 210 may include a communication system, an entertainment system, and a navigation system, among others.

[0095] The perception system 220 may include several sensors for sensing information about the environment around the vehicle 200. For example, the perception system 220 may include a global positioning system (the global positioning system may be a GPS system, a Beidou system, or other positioning systems) and an inertial measurement unit (IMU).

[0096] The decision control system 230 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0097] The drive system 240 may include components that provide power movement for the vehicle 200. In one embodiment, the drive system 240 may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of an internal combustion engine, an electric motor, and an air compression engine. The engine can convert energy provided by the energy source into mechanical energy.

[0098] Some or all functions of the vehicle 200 are controlled by a computing platform 250. The computing platform 250 may include at least one processor 251 and a memory 252, and the processor 251 may execute instructions 253 stored in the memory 252.

[0099] The processor 251 may be any conventional processor, such as a commercially available CPU. The processor may also include a graphics processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable Gate Array, FPGA), a system on chip (System on Chip, SOC), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC) or a combination thereof.

[0100] The memory 252 may be implemented by any type of volatile or nonvolatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0101] In addition to instructions 253 , memory 252 may also store data, such as road maps, route information, and data such as the location, direction, and speed of the vehicle. The data stored in memory 252 may be used by computing platform 250 .

[0102] In the embodiment of the present disclosure, the processor 251 may execute the instruction 253 to complete all or part of the steps of the above-mentioned vehicle positioning method.

[0103] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program executable by a programmable device. The computer program has a code portion for executing the above-mentioned vehicle positioning method when executed by the programmable device.

[0104] In summary, the vehicle positioning method, device, vehicle and medium provided by the present disclosure obtain the first position data of the vehicle in the local coordinate system collected by the sensor on the vehicle; the coordinate transformation relationship can realize the transformation between the local coordinate system and the global coordinate system, and according to the coordinate transformation relationship, the first position data in the local coordinate system is transformed to obtain the second position data of the vehicle in the global coordinate system. Compared with the existing technology, the sensor used to collect the first position data is not interfered by factors such as the network, obstructions, and light, which can improve the accuracy of positioning.

[0105] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the present disclosure. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0106] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A vehicle positioning method, characterized in that: The method comprises: Acquire first position data of the vehicle in a local coordinate system collected by a sensor on the vehicle; The first position data in the local coordinate system is subjected to coordinate transformation according to a coordinate transformation relationship to obtain second position data of the vehicle in a global coordinate system, wherein the coordinate transformation relationship is used for transformation between the local coordinate system and the global coordinate system.

2. The method according to claim 1, characterized in that Also includes: The coordinate transformation relationship is updated to obtain an updated coordinate transformation relationship.

3. The method according to claim 2, characterized in that The updating of the coordinate transformation relationship to obtain an updated coordinate transformation relationship includes: Acquiring an actual driving track of the vehicle according to the second position data; Performing trajectory matching according to the actual driving trajectory and the preset driving trajectory to obtain adjustment parameters for the actual driving trajectory; The coordinate transformation relationship is updated according to the adjustment parameter to obtain the updated coordinate transformation relationship.

4. The method according to claim 3, characterized in that The updating of the coordinate transformation relationship to obtain an updated coordinate transformation relationship includes: When the actual driving trajectory satisfies a straight-line driving condition, obtaining an angle between the actual driving trajectory and the preset driving trajectory; The angle transformation relationship in the coordinate transformation relationship is updated according to the included angle to obtain the updated coordinate transformation relationship.

5. The method according to claim 4, characterized in that The updating of the coordinate transformation relationship to obtain an updated coordinate transformation relationship includes: When the actual driving trajectory does not meet the straight-line driving condition, obtaining a displacement difference between the actual driving trajectory and the preset driving trajectory; The displacement transformation relationship in the coordinate transformation relationship is updated according to the displacement difference to obtain the updated coordinate transformation relationship.

6. The method according to claim 4 or 5, characterized in that: The straight-line driving condition includes that the curvature of the driving trajectory is less than a preset curvature.

7. The method according to claim 3, characterized in that The obtaining of the actual driving trajectory of the vehicle comprises: Acquire first position data collected by the sensor at each moment in a plurality of consecutive moments; According to the coordinate transformation relationship, coordinate transformation is performed on the plurality of first position data to obtain second position data corresponding to each moment in the plurality of consecutive moments; The actual driving trajectory of the vehicle is obtained according to the plurality of second position data.

8. The method according to any one of claims 1 to 5, characterized in that: The sensor includes at least one of the following: an inertial measurement unit, a wheel speed meter.

9. A vehicle positioning device, characterized in that: The device comprises: An acquisition module, used for acquiring first position data of the vehicle in a local coordinate system acquired by a sensor on the vehicle; A conversion module is used to perform coordinate conversion on the first position data in the local coordinate system according to a coordinate conversion relationship to obtain second position data of the vehicle in the global coordinate system, wherein the coordinate conversion relationship is used for conversion between the local coordinate system and the global coordinate system.

10. A vehicle, characterized in that: The vehicle comprises: processor; a memory for storing processor-executable instructions; The processor is configured to implement the steps of any one of the methods of claims 1 to 8 when executing.

11. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, the steps of the method described in any one of claims 1 to 8 are implemented.

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