Driving track adjustment method and device, equipment and storage medium

Abstract

The invention provides a driving track adjusting method and device, equipment and a storage medium, and the method comprises the steps: determining the lateral deviation information of a target vehicle according to a driving position point set from T0 moment to T1 moment, and the T0 moment is earlier than the T1 moment; calculating compensation data of the target vehicle according to the lateral deviation information; and predicting driving track information of the target vehicle according to the compensation data so as to adjust the driving track of the target vehicle after the T1 moment according to the driving track information. According to the method, the position information of the multiple time frames in a period of time before the current moment is taken as a reference, a relatively accurate transverse deviation recognition result can be obtained under the condition that the accuracy of an automatic driving system algorithm is not changed, and then the accuracy of the transverse deviation recognition result is improved in subsequent driving track adjustment. The actual driving track of the target vehicle can be gradually close to the preset target driving track, and the control effect is optimized.

Description

Technical Field

[0001] The present application belongs to the field of data processing technology, and specifically relates to a driving trajectory adjustment method, device, equipment and storage medium. Background Art

[0002] During the driving process of the vehicle, the autonomous driving system plans and adjusts the vehicle's driving trajectory to make the vehicle's driving trajectory as close as possible to the pre-planned ideal trajectory. The autonomous driving system usually determines the real-time positioning of the vehicle in each time frame, calculates the adjustment data for the vehicle's driving trajectory based on the real-time positioning deviation in adjacent time frames, and adjusts the vehicle's actual driving trajectory according to the adjustment data.

[0003] In some implementation scenarios, if the vehicle's driving trajectory deviates laterally, due to the accuracy of the autonomous driving system algorithm, it is difficult to identify the lateral deviation of the driving trajectory based on the trajectory changes at the time frame level, resulting in a lack of strength and timeliness in the lateral adjustment of the vehicle, causing the lateral deviation of the vehicle's driving trajectory to gradually increase, resulting in poor control effect. Summary of the invention

[0004] The present application proposes a driving trajectory adjustment method, device, equipment and storage medium, which can timely adjust the driving trajectory of a vehicle when the driving trajectory of the vehicle is laterally offset.

[0005] The first embodiment of the present application provides a driving trajectory adjustment method, including:

[0006] Determine lateral offset information of the target vehicle according to a set of driving position points from time T0 to time T1, wherein time T0 is earlier than time T1;

[0007] Calculating compensation data of the target vehicle according to the lateral offset information, wherein the compensation data is used to correct the lateral offset of the target vehicle;

[0008] The driving trajectory information of the target vehicle is predicted according to the compensation data, so as to adjust the driving trajectory of the target vehicle after the time T1 according to the driving trajectory information.

[0009] In some embodiments of the present application, the set of driving position points includes:

[0010] The position to which the target vehicle travels in each time frame from the time T0 to the time T1.

[0011] In some embodiments of the present application, the lateral offset information includes at least one of the following:

[0012] The rate at which the target vehicle deviates laterally, and the direction in which the target vehicle deviates laterally.

[0013] In some embodiments of the present application, determining the lateral offset information of the target vehicle according to the set of driving position points from time T0 to time T1 includes:

[0014] Determine the lateral distance between the position of the target vehicle at the time T0 and the preset target trajectory as the first lateral distance, and determine the lateral distance between the position of the target vehicle at the time T1 and the preset target trajectory as the second lateral distance;

[0015] Calculating an average speed of the target vehicle in a lateral direction according to a difference between the second lateral distance and the first lateral distance, the average speed being a rate of lateral displacement of the target vehicle;

[0016] The direction of the position of the target vehicle at the time T1 relative to the preset target trajectory is determined as the offset direction of the lateral offset of the target vehicle.

[0017] In some embodiments of the present application, the calculating the compensation data of the target vehicle according to the lateral offset information includes:

[0018] Calculating the lateral travel distance of the target vehicle in two adjacent time frames according to the lateral displacement rate of the target vehicle;

[0019] A turning rate is calculated according to a rate of lateral deviation of the target vehicle and the lateral travel distance, wherein the turning rate is a rate of traveling in a direction opposite to the deviation direction, and the compensation data includes the turning rate.

[0020] In some embodiments of the present application, the method further includes: obtaining yaw attitude data of the target vehicle at the time T1;

[0021] The step of calculating compensation data of the target vehicle according to the lateral offset information further includes:

[0022] Determine a yaw angle according to the yaw attitude data and the offset direction;

[0023] The posture correction data of the target vehicle is calculated according to the yaw angle, and the compensation data includes the posture correction data.

[0024] In some embodiments of the present application, predicting the driving trajectory information of the target vehicle according to the compensation data includes:

[0025] Predicting the position of the target vehicle in multiple time frames from the time T1 to the time T2 according to the posture correction data and the steering rate, wherein the trajectory formed by the positions of the multiple time frames is the driving trajectory information of the target vehicle;

[0026] The time T2 is later than the time T1.

[0027] In some embodiments of the present application, after predicting the driving trajectory information of the target vehicle according to the compensation data, the method further includes:

[0028] using the compensation data as feedforward data to calculate a steering wheel torque parameter of the target vehicle;

[0029] The steering wheel of the target vehicle is controlled based on the steering wheel torque parameter so that the target vehicle travels according to the driving trajectory information.

[0030] In some embodiments of the present application, the time difference between the time T0 and the time T1 is greater than or equal to a preset duration.

[0031] The embodiment of the second aspect of the present application provides a driving trajectory adjustment device, comprising:

[0032] A determination module, used to determine the lateral offset information of the target vehicle according to a set of driving position points from time T0 to time T1, wherein the time T0 is earlier than the time T1;

[0033] A calculation module, used for calculating compensation data of the target vehicle according to the lateral offset information, wherein the compensation data is used for correcting the lateral offset of the target vehicle;

[0034] A prediction module is used to predict the driving trajectory information of the target vehicle according to the compensation data, so as to adjust the driving trajectory of the target vehicle after the time T1 according to the driving trajectory information.

[0035] An embodiment of the third aspect of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect above.

[0036] An embodiment of the fourth aspect of the present application provides a computer-readable storage medium on which a computer program is stored, and the program is executed by a processor to implement the method described in the first aspect above.

[0037] The technical solution provided in the embodiments of the present application has at least the following technical effects or advantages:

[0038] In an embodiment of the present application, the lateral offset information of the target vehicle is determined by a set of driving position points from time T0 to time T1, wherein the time T0 is earlier than the time T1. Taking time T1 as the current time, that is, by obtaining a set of historical driving positions for a period of time before the current time, the lateral offset of the target vehicle is identified, which is beneficial to improving the accuracy of identifying the lateral deviation of the driving trajectory compared to the traditional identification based on data of adjacent time frames. Furthermore, the compensation data of the target vehicle is calculated based on the lateral offset information, and the compensation data is used to correct the lateral offset of the target vehicle, so that the driving trajectory information of the target vehicle predicted based on the compensation data can correct the lateral offset of the target vehicle to a certain extent, so that the actual driving trajectory of the target vehicle gradually approaches the preset target driving trajectory. It can be seen that by adopting the technical solution of the present application, the position information of two adjacent time frames of the vehicle is no longer used as the identification parameter, but the position information of multiple time frames for a period of time before the current moment is used as a reference. In this way, while the accuracy of the automatic driving system algorithm remains unchanged, a relatively accurate lateral offset identification result can be obtained. Furthermore, in the subsequent driving trajectory adjustment, the actual driving trajectory of the target vehicle can be gradually made close to the preset target driving trajectory, thereby optimizing the control effect.

[0039] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] By reading the detailed description of the preferred embodiment below, various other advantages and benefits will become clear to those of ordinary skill in the art. The accompanying drawings are only used for the purpose of illustrating the preferred embodiment and are not considered to be limitations of the present application. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings.

[0041] In the attached picture:

[0042] Figure 1 A schematic diagram of a scenario in which a driving track is laterally offset provided by an embodiment of the present application is shown;

[0043] Figure 2 A flow chart of a driving trajectory adjustment method provided by an embodiment of the present application is shown;

[0044] Figure 3 A schematic diagram of a scenario of driving trajectory adjustment provided by an embodiment of the present application is shown;

[0045] Figure 4 A schematic diagram of the structure of a driving trajectory adjustment device provided by an embodiment of the present application is shown;

[0046] Figure 5A schematic diagram of the structure of an electronic device provided by an embodiment of the present application is shown;

[0047] Figure 6 A schematic diagram of a storage medium provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0048] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0049] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by technicians in the field to which this application belongs.

[0050] Embodiments of the present application may involve an autonomous driving scenario. In the autonomous driving scenario, the autonomous driving system of the target vehicle may determine the target driving trajectory of the target vehicle based on a pre-input map. During the autonomous driving process, the autonomous driving system obtains the current actual position of the target vehicle in time frames, and locates the driving trend of the target vehicle by comparing it with the actual position of the previous time frame. Afterwards, the driving trajectory of the target vehicle may be predicted based on the relationship between the determined driving trend and the target driving trajectory, and the target vehicle may be controlled to move according to the predicted trajectory.

[0051] It should be pointed out that the target vehicle's driving trajectory may include driving trajectories in a straight direction and a lateral direction (such as a scenario where the vehicle is driving on a curve), and the autonomous driving system may predict the driving trajectory in the straight direction and the driving trajectory in the lateral direction respectively.

[0052] See also Figure 1 , Figure 1 A scenario of lateral deviation of the driving trajectory is shown. Figure 1 Track 1 is the target track, the rectangular box represents the target vehicle, and two adjacent rectangular boxes, for example, represent the position of the target vehicle in two adjacent time frames. Combined with the above description of the localize process, the autonomous driving system determines the position of the target vehicle at time T01, for example, and compares it with the position of the target vehicle at time T00. Since the data acquired by the autonomous driving system itself contains some noise, and the autonomous driving system has a certain precision error, therefore, when the lateral distance between the position at time T01 and the position at time T00 is less than a certain degree, the autonomous driving system may not recognize it as a lateral offset, and the lateral trajectory of the target vehicle will not be adjusted. Figure 1As shown, after a period of time, the lateral deviation of the actual driving trajectory of the target vehicle will become larger and larger, and it will still take a certain amount of time for the automatic driving system to adjust the driving trajectory after the deviation, which will further cause the lateral deviation to expand and result in poor control effect.

[0053] Based on this, the technical solution provided in the embodiment of the present application uses the position information of multiple time frames for a period of time before the current moment as a reference to determine the lateral offset information of the target vehicle, and then compensates the localize of the target vehicle according to the determined lateral offset information to predict the driving trajectory of the target vehicle in the future. A relatively accurate lateral offset identification result can be obtained, and then, in the subsequent driving trajectory adjustment, the actual driving trajectory of the target vehicle can be gradually made close to the preset target driving trajectory, thereby optimizing the control effect.

[0054] The execution subject of this technical solution can be any device that supports driving trajectory adjustment, including vehicles, ships, aircraft or robots. Such devices can support the driving trajectory adjustment of the embodiment of the present application through an automatic driving system. The automatic driving system can be provided with relevant functional mechanisms such as trajectory planning components and motion control components. The automatic driving system can also simulate the target trajectory and target vehicle through a simulation system.

[0055] A driving trajectory adjustment method, device, and storage medium proposed according to an embodiment of the present application are described below in conjunction with the accompanying drawings.

[0056] See also Figure 2 , Figure 2 A flow chart of a driving trajectory adjustment method provided by an embodiment of the present application is shown, and the method specifically comprises the following steps:

[0057] Step S101, determining the lateral offset information of the target vehicle according to the set of driving position points from time T0 to time T1.

[0058] The T0 time is earlier than the T1 time. The driving position point set includes: the position to which the target vehicle drives in each time frame from the T0 time to the T1 time.

[0059] Exemplarily, the T1 moment may be the current moment of the target vehicle, that is, the moment when the automatic driving system determines the current real-time position of the target vehicle. Accordingly, the set of driving position points from T0 to T1 may be realized as a set of driving positions corresponding to each time frame during the actual driving process of the target vehicle from T0 to T1.

[0060] In some implementations, in order to obtain relatively more reference data, the time difference between the time T0 and the time T1 is greater than or equal to a preset duration, so that position points of multiple time frames can be obtained, so that relatively accurate localize data of the target vehicle can be obtained.

[0061] For example, the time difference between the T0 time and the T1 time is greater than or equal to the preset time length of 0.5 seconds (s) (refer to Figure 3 shown).

[0062] The lateral offset information described in the embodiment of the present application may include at least one of the following: the rate of lateral offset of the target vehicle, and the offset direction of lateral offset of the target vehicle.

[0063] It should be understood that the above lateral offset information is an exemplary description of the present application and does not constitute a limitation on the lateral offset information involved in the present application. In some other implementations of the present application, the lateral offset information may also include other information, such as the curvature of the trajectory of the lateral offset of the target vehicle.

[0064] Exemplarily, the automatic driving system of the target vehicle may determine the lateral distance between the position of the target vehicle at time T0 and the preset target trajectory as the first lateral distance, and determine the lateral distance between the position of the target vehicle at time T1 and the preset target trajectory as the second lateral distance, and then calculate the average speed of the target vehicle in the lateral direction according to the difference between the second lateral distance and the first lateral distance, and the average speed is the rate of lateral displacement of the target vehicle. And the direction of the position of the target vehicle at time T1 relative to the preset target trajectory is determined as the displacement direction of the lateral displacement of the target vehicle.

[0065] It should be noted that the autonomous driving system usually controls the target vehicle in the lateral direction by controlling the target vehicle to drive left or right. In view of this, in some implementations, the offset direction may be left or right, for example, Figure 1 The offset direction of the target vehicle is to the left.

[0066] Step S102: calculating compensation data of the target vehicle according to the lateral offset information.

[0067] The compensation data is used to correct the lateral deviation of the target vehicle. In some implementations, the compensation data can be used as feedforward data in the process of calculating vehicle control data.

[0068] In some implementations, the autonomous driving system calculates the lateral travel distance of the target vehicle in two adjacent time frames based on the rate of lateral displacement of the target vehicle; calculates the turning rate based on the rate of lateral displacement of the target vehicle and the lateral travel distance, the turning rate being the rate of driving in the opposite direction to the displacement direction, and the compensation data includes the turning rate.

[0069] It should be understood that if the target vehicle is laterally offset, the target vehicle's position usually also has a certain yaw angle, so see Figure 3 As shown in (a) in the figure, in the driving trajectory after time T1, it is necessary to perform posture rotation at the trajectory point corresponding to each time frame, which is not only relatively cumbersome for the control of the target vehicle, but also not conducive to the calculation of the correction posture parameters of each time frame.

[0070] Based on this, in some other implementations, the autonomous driving system may also obtain the yaw attitude data of the target vehicle at the time T1. In the process of calculating the compensation data of the target vehicle, the autonomous driving system may determine the yaw angle according to the yaw attitude data and the offset direction, and may calculate the attitude correction data of the target vehicle according to the yaw angle. Figure 3 As shown in (b) in FIG. 1 . The compensation data includes the posture correction data. In this way, by performing reverse rotation correction on the posture of the vehicle at time T1, the posture of the target vehicle can be corrected in a timely and relatively accurate manner, without the need to calculate the correction posture parameters of each future time frame, and the control is relatively simple.

[0071] Step S103: predicting the driving trajectory information of the target vehicle according to the compensation data, so as to adjust the driving trajectory of the target vehicle after the time T1 according to the driving trajectory information.

[0072] In combination with the above description, time T1 is the current time, and the driving trajectory information indicates the driving trajectory of the target vehicle from time T1 to after time T1. Exemplarily, the driving trajectory information may include predicted position points of multiple consecutive time frames.

[0073] It should be pointed out that the predicted driving trajectory information may be a driving trajectory within a period of time, which is helpful to improve the accuracy of the predicted driving trajectory.

[0074] In some implementations, the autonomous driving system may predict the position of the target vehicle in multiple time frames from the time T1 to the time T2 based on the posture correction data and the steering rate (see Figure 3 ), the trajectory formed by the positions of the multiple time frames is the driving trajectory information of the target vehicle.

[0075] See again Figure 4 In this example, the T2 moment is later than the T1 moment.

[0076] In some implementations, after predicting the driving trajectory information of the target vehicle, the autonomous driving system may use the compensation data as feedforward data to calculate the steering wheel torque parameters of the target vehicle, and control the steering wheel of the target vehicle based on the steering wheel torque parameters so that the target vehicle travels according to the driving trajectory information.

[0077] Exemplarily, in combination with the above introduction to the autonomous driving system, the above steps S101 to S103 may be executed by a trajectory planning component in the autonomous driving system. After predicting the driving trajectory information, the trajectory planning component may transmit the driving trajectory information to the motion control component, and the motion control component may control the steering wheel rotation of the target vehicle to control the target vehicle to drive according to the driving trajectory information.

[0078] In an embodiment of the present application, the lateral offset information of the target vehicle is determined by a set of driving position points from time T0 to time T1, wherein the time T0 is earlier than the time T1. Taking the time T1 as the current time, that is, by obtaining a set of historical driving positions for a period of time before the current time, the lateral offset of the target vehicle is identified, which is beneficial to improving the accuracy of identifying the lateral deviation of the driving trajectory compared to the traditional identification based on data of adjacent time frames. Furthermore, the compensation data of the target vehicle is calculated based on the lateral offset information, and the compensation data is used to correct the lateral offset of the target vehicle, so that the driving trajectory information of the target vehicle predicted based on the compensation data can correct the lateral offset of the target vehicle to a certain extent, so that the actual driving trajectory of the target vehicle gradually approaches the preset target driving trajectory. It can be seen that by adopting the technical solution of the present application, the position information of two adjacent time frames of the vehicle is no longer used as the identification parameter, but the position information of multiple time frames for a period of time before the current moment is used as a reference. In this way, while the accuracy of the automatic driving system algorithm remains unchanged, a relatively accurate lateral offset identification result can be obtained. Furthermore, in the subsequent driving trajectory adjustment, the actual driving trajectory of the target vehicle can be gradually made close to the preset target driving trajectory, thereby optimizing the control effect.

[0079] The present application also provides a driving track adjustment device, which is used to execute the driving track adjustment method provided in any of the above embodiments. Figure 4 As shown, the device comprises:

[0080] The determination module 401 is used to determine the lateral offset information of the target vehicle based on the set of driving position points from time T0 to time T1, wherein the time T0 is earlier than the time T1; the calculation module 402 is used to calculate the compensation data of the target vehicle based on the lateral offset information, and the compensation data is used to correct the lateral offset of the target vehicle; the prediction module 403 is used to predict the driving trajectory information of the target vehicle based on the compensation data, so as to adjust the driving trajectory of the target vehicle after the time T1 according to the driving trajectory information.

[0081] Optionally, the driving position point set includes: the position to which the target vehicle drives in each time frame between the time T0 and the time T1.

[0082] Optionally, the lateral offset information includes at least one of the following: a rate of lateral offset of the target vehicle, and a direction of lateral offset of the target vehicle.

[0083] Optionally, the determination module 401 is also used to determine the lateral distance between the position of the target vehicle at the time T0 and the preset target trajectory as the first lateral distance, and to determine the lateral distance between the position of the target vehicle at the time T1 and the preset target trajectory as the second lateral distance; calculate the average speed of the target vehicle in the lateral direction according to the difference between the second lateral distance and the first lateral distance, and the average speed is the rate of lateral deviation of the target vehicle; and determine the direction of the position of the target vehicle at the time T1 relative to the preset target trajectory as the offset direction of the lateral deviation of the target vehicle.

[0084] Optionally, the calculation module 402 is also used to calculate the lateral travel distance of the target vehicle in two adjacent time frames according to the rate of lateral displacement of the target vehicle; calculate the turning rate according to the rate of lateral displacement of the target vehicle and the lateral travel distance, the turning rate is the rate of driving in the opposite direction to the displacement direction, and the compensation data includes the turning rate.

[0085] Optionally, the driving trajectory adjustment device further includes an acquisition module for acquiring the yaw attitude data of the target vehicle at the time T1. The calculation module 402 is further used to determine the yaw angle according to the yaw attitude data and the offset direction; and calculate the attitude correction data of the target vehicle according to the yaw angle, and the compensation data includes the attitude correction data.

[0086] Optionally, the prediction module 403 is also used to predict the position of the target vehicle in multiple time frames from the moment T1 to the moment T2 based on the posture correction data and the steering rate, and the trajectory formed by the positions of the multiple time frames is the driving trajectory information of the target vehicle; the moment T2 is later than the moment T1.

[0087] Optionally, the driving trajectory adjustment device further includes a control module. The calculation module 402 is further used to use the compensation data as feedforward data to calculate the steering wheel torque parameter of the target vehicle; the control module is used to control the steering wheel of the target vehicle based on the steering wheel torque parameter so that the target vehicle travels according to the driving trajectory information.

[0088] The driving trajectory adjustment device provided in the embodiment of the present application and the driving trajectory adjustment method provided in the embodiment of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented therein.

[0089] The present application also provides an electronic device to perform the above-mentioned driving trajectory adjustment method. Figure 5 It shows a schematic diagram of an electronic device provided by some embodiments of the present application. Figure 5 As shown, the electronic device 5 includes: a processor 500, a memory 501, a bus 502 and a communication interface 503, wherein the processor 500, the communication interface 503 and the memory 501 are connected via the bus 502; the memory 501 stores a computer program that can be run on the processor 500, and when the processor 500 runs the computer program, the driving trajectory adjustment method provided in any of the aforementioned embodiments of the present application is executed.

[0090] The memory 501 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The communication connection between the device network element and at least one other network element is realized through at least one communication interface 503 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0091] The bus 502 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory 501 is used to store a program, and the processor 500 executes the program after receiving an execution instruction. The driving trajectory adjustment method disclosed in any implementation of the embodiment of the present application may be applied to the processor 500, or implemented by the processor 500.

[0092] The processor 500 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 500. The above processor 500 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor to be executed, or the hardware and software modules in the decoding processor can be executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 501, and the processor 500 reads the information in the memory 501 and completes the steps of the above method in combination with its hardware.

[0093] The electronic device provided in the embodiment of the present application and the driving trajectory adjustment method provided in the embodiment of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented therein.

[0094] The present application also provides a computer-readable storage medium corresponding to the driving trajectory adjustment method provided in the above embodiment. Figure 6 The computer-readable storage medium shown is a CD 30 on which a computer program (ie, a program product) is stored. When the computer program is run by a processor, the driving trajectory adjustment method provided by any of the aforementioned embodiments will be executed.

[0095] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0096] The computer-readable storage medium provided in the above-mentioned embodiments of the present application and the driving trajectory adjustment method provided in the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.

[0097] It should be noted that:

[0098] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known structures and technologies are not shown in detail so as not to obscure the understanding of this description.

[0099] Similarly, it should be understood that in order to streamline the present application and help understand one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present application, the various features of the present application are sometimes grouped together into a single embodiment, figure, or description thereof. However, the disclosed method should not be interpreted as reflecting the following schematic diagram: the claimed application requires more features than the features clearly stated in each claim. More specifically, as reflected in the claims below, the inventive aspects are less than all the features of the single embodiment disclosed above. Therefore, the claims following the specific embodiment are hereby expressly incorporated into the specific embodiment, wherein each claim itself serves as a separate embodiment of the present application.

[0100] In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present application and form different embodiments. For example, in the claims below, any one of the claimed embodiments may be used in any combination.

[0101] The above is only a preferred specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A driving trajectory adjustment method, characterized in that: include: Determine lateral offset information of the target vehicle according to a set of driving position points from time T0 to time T1, wherein time T0 is earlier than time T1; Calculating compensation data of the target vehicle according to the lateral offset information, wherein the compensation data is used to correct the lateral offset of the target vehicle; The driving trajectory information of the target vehicle is predicted according to the compensation data, so as to adjust the driving trajectory of the target vehicle after the time T1 according to the driving trajectory information.

2. The method according to claim 1, characterized in that The driving position point set includes: The position to which the target vehicle travels in each time frame between the time T0 and the time T1; The lateral offset information includes at least one of the following: The rate at which the target vehicle deviates laterally, and the direction in which the target vehicle deviates laterally.

3. The method according to claim 2, characterized in that The step of determining the lateral offset information of the target vehicle according to the set of driving position points from time T0 to time T1 includes: Determine the lateral distance between the position of the target vehicle at the time T0 and the preset target trajectory as the first lateral distance, and determine the lateral distance between the position of the target vehicle at the time T1 and the preset target trajectory as the second lateral distance; Calculating an average speed of the target vehicle in a lateral direction according to a difference between the second lateral distance and the first lateral distance, the average speed being a rate of lateral displacement of the target vehicle; The direction of the position of the target vehicle at the time T1 relative to the preset target trajectory is determined as the offset direction of the lateral offset of the target vehicle.

4. The method according to claim 1 or 2, characterized in that: The calculating the compensation data of the target vehicle according to the lateral offset information comprises: Calculating the lateral travel distance of the target vehicle in two adjacent time frames according to the lateral displacement rate of the target vehicle; A turning rate is calculated according to a rate of lateral deviation of the target vehicle and the lateral travel distance, wherein the turning rate is a rate of traveling in a direction opposite to the deviation direction, and the compensation data includes the turning rate.

5. The method according to claim 4, characterized in that Also includes: Acquire the yaw attitude data of the target vehicle at the time T1; The step of calculating the compensation data of the target vehicle according to the lateral offset information further includes: Determine a yaw angle according to the yaw attitude data and the offset direction; The posture correction data of the target vehicle is calculated according to the yaw angle, and the compensation data includes the posture correction data.

6. The method according to claim 5, characterized in that The predicting the driving trajectory information of the target vehicle according to the compensation data includes: Predicting the position of the target vehicle in multiple time frames from the time T1 to the time T2 according to the posture correction data and the steering rate, wherein the trajectory formed by the positions of the multiple time frames is the driving trajectory information of the target vehicle; The time T2 is later than the time T1.

7. The method according to claim 1, characterized in that After predicting the driving trajectory information of the target vehicle according to the compensation data, the method further includes: using the compensation data as feedforward data to calculate a steering wheel torque parameter of the target vehicle; The steering wheel of the target vehicle is controlled based on the steering wheel torque parameter so that the target vehicle travels according to the driving trajectory information.

8. A driving track adjustment device, characterized in that: include: A determination module, used to determine the lateral offset information of the target vehicle according to a set of driving position points from time T0 to time T1, wherein the time T0 is earlier than the time T1; A calculation module, used for calculating compensation data of the target vehicle according to the lateral offset information, wherein the compensation data is used for correcting the lateral offset of the target vehicle; A prediction module is used to predict the driving trajectory information of the target vehicle according to the compensation data, so as to adjust the driving trajectory of the target vehicle after the time T1 according to the driving trajectory information.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: The processor runs the computer program to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method according to any one of claims 1 to 7.

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