CN117360548A

CN117360548A - Vehicle transverse control method, device, equipment and storage medium

Info

Publication number: CN117360548A
Application number: CN202311589373.2A
Authority: CN
Inventors: 郝晨希
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2023-11-24
Filing date: 2023-11-24
Publication date: 2024-01-09

Abstract

The disclosure provides a vehicle transverse control method, device, equipment and storage medium, relates to the technical field of artificial intelligence, and particularly relates to the technical field of automatic driving and intelligent traffic. The specific implementation scheme is as follows: under the condition that the vehicle is identified to be in a high-speed straight road section, determining an original state error of the vehicle according to current state information of the vehicle and track point information of a planned track; wherein the original state error comprises an original transverse error and/or an original course angle error; correcting the original state error to obtain a target state error in response to the original state error being smaller than a state error boundary; and inputting the target state error into a transverse controller to obtain an actual steering wheel control angle of the vehicle so as to transversely control the vehicle. Through the technical scheme, the vehicle can be prevented from frequently shaking.

Description

Vehicle transverse control method, device, equipment and storage medium

Technical Field

The present disclosure relates to the field of artificial intelligence, and more particularly to the field of autopilot and intelligent transportation technology.

Background

The stability and riding quality of the automatic driving vehicle are important indexes for measuring the automatic driving technology, particularly in a high-speed scene, a dynamics model of the vehicle may become more complex in the high-speed scene, a more accurate control algorithm is needed to conduct real-time regulation and control on the vehicle, and the high accuracy of the refined dynamics modeling and the real-time positioning information of the vehicle has great difficulty, and slight shaking can cause tension and discomfort of passengers on the vehicle, so that riding experience is greatly affected, and how to improve the stability of the vehicle is a valuable problem.

Disclosure of Invention

The present disclosure provides a vehicle lateral control method, apparatus, device, and storage medium.

According to an aspect of the present disclosure, there is provided a vehicle lateral control method including:

under the condition that the vehicle is identified to be in a high-speed straight road section, determining an original state error of the vehicle according to current state information of the vehicle and track point information of a planned track; wherein the original state error comprises an original transverse error and/or an original course angle error;

correcting the original state error to obtain a target state error in response to the original state error being smaller than a state error boundary;

And inputting the target state error into a transverse controller to obtain an actual steering wheel control angle of the vehicle so as to transversely control the vehicle.

According to an aspect of the present disclosure, there is provided a vehicle lateral control device including:

the original state error determining module is used for determining the original state error of the vehicle according to the current state information of the vehicle and the track point information of the planned track under the condition that the vehicle is identified to be in a high-speed straight road section; wherein the original state error comprises an original transverse error and/or an original course angle error;

the target state error determining module is used for responding to the original state error being smaller than a state error boundary and correcting the original state error to obtain a target state error;

and the transverse control module is used for inputting the target state error into a transverse controller to obtain the actual steering wheel control angle of the vehicle so as to transversely control the vehicle.

According to another aspect of the present disclosure, there is provided an electronic device including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the vehicle lateral control method of any one of the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the vehicle lateral control method according to any one of the embodiments of the present disclosure.

According to an aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements a vehicle lateral control method according to any embodiment of the present disclosure.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.

Drawings

The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a flow chart of a vehicle lateral control method provided in accordance with an embodiment of the present disclosure;

FIG. 2 is a flow chart of another vehicle lateral control method provided in accordance with an embodiment of the present disclosure;

FIG. 3 is a flow chart of yet another vehicle lateral control method provided in accordance with an embodiment of the present disclosure;

fig. 4 is a schematic structural view of a vehicle lateral control device provided according to an embodiment of the present disclosure;

fig. 5 is a block diagram of an electronic device for implementing a vehicle lateral control method of an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

It should be noted that the terms "first," "second," "target," and the like in the description and claims of the present invention and in the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

In addition, in the technical scheme of the invention, the related processes of collecting, storing, using, processing, transmitting, providing, disclosing and the like of the vehicle state information, the track point information and the like are all in accordance with the regulations of related laws and regulations, and the public welfare is not violated.

FIG. 1 is a flow chart of a vehicle lateral control method provided in accordance with an embodiment of the present disclosure; the method is suitable for the situation of how to improve the stability of the vehicle in an automatic driving scene. The method may be performed by a vehicle lateral control device, which may be implemented in software and/or hardware and may be integrated in an electronic device carrying vehicle lateral control functions, such as a vehicle terminal, in particular an autonomous vehicle terminal. As shown in fig. 1, the vehicle lateral control method of the present embodiment may include:

s101, under the condition that the vehicle is identified to be in a high-speed straight road section, determining an original state error of the vehicle according to current state information of the vehicle and track point information of a planned track.

In the present embodiment, the high-speed flat road section refers to a road section that is relatively flat and allows traveling at a higher speed. The current state information is state information of the vehicle at the current time, and includes a current position, a current heading angle, and the like. The planned trajectory is a planned travel trajectory of the vehicle at a distance in the future. The track point information refers to related information of track points in a planned track, and optionally, the track point information can comprise planned positions, planned course angles and the like of the track points; the planning position refers to the position of a track point planned by the vehicle at the current moment; the planned course angle refers to the course angle planned by the vehicle at the current moment.

The original state error is the error between the current state information of the vehicle and the planned track point information; optionally, an original lateral error and/or an original heading angle error may be included; wherein the original lateral error refers to an error between the current position and the planned position of the vehicle; the raw heading angle error refers to an error between the current heading angle of the vehicle and the planned heading angle.

Specifically, under the condition that the vehicle is identified to be in a high-speed straight road section, the original state error of the vehicle is determined according to the difference data between the current state information of the vehicle and the track point information of the planned track.

S102, in response to the original state error being smaller than the state error boundary, correcting the original state error to obtain a target state error.

In this embodiment, the state error boundary refers to an error boundary whether to attenuate the original state error; optionally, the state error boundaries include lateral error boundaries and/or heading angle error boundaries. Wherein the lateral error boundary is determined according to the lane width and the vehicle width; specifically, the result of subtracting the vehicle width from the lane width can be multiplied by a boundary coefficient to obtain a transverse error boundary; wherein the boundary factor can be set by a person skilled in the art according to the actual situation, for example 0.5. It can be understood that the transverse error boundary is set, so that on one hand, the vehicles can be ensured not to deviate from the lane line, and the safety risk is reduced; on the other hand, the transverse control errors of the automatic driving vehicle are all within the transverse error boundary, so that good control performance can be ensured.

It should be noted that the course angle error boundary may be set by those skilled in the art according to actual scene requirements.

In this embodiment, the target state error refers to a state error after the original state error is corrected; optionally, including a target lateral error and a target heading angle error; the target transverse error refers to the original transverse error corrected transverse error; the target course angle error refers to the course angle error after the original course angle error is corrected.

Alternatively, if the original state error is smaller than the state error boundary, the original state error may be corrected based on a certain correction rule to obtain the target state error, for example, the original state error is reduced according to a certain proportion, and the reduced original state error is used as the target state error. If the original state error is larger than the state error boundary, the original state error is not attenuated, and the original state error is directly input into a transverse controller to obtain an actual steering wheel control angle of the vehicle so as to transversely control the vehicle.

It can be understood that whether the original state error is attenuated is determined by setting a state error boundary, so that the dependence of the steering wheel control angle on the original state error can be effectively reduced when the error is small, and the transverse somatosensory is ensured; when the error is large, the original state error is still normally adopted for transverse control, so that the sense of body is less and good control performance is ensured.

Optionally, if the original lateral error is smaller than the lateral error boundary, the original lateral error may be corrected based on a certain correction rule, so as to obtain the target lateral error. If the original transverse error is larger than the transverse error boundary, the original transverse error is not attenuated, and the original transverse error is directly input into a transverse controller to obtain an actual steering wheel control angle of the vehicle so as to transversely control the vehicle.

It can be understood that whether the original transverse error is attenuated is determined by setting the transverse error boundary, so that the dependence of the steering wheel control angle on the original transverse error can be effectively reduced when the error is small, and the transverse somatosensory is ensured; when the error is large, the original transverse error is still normally adopted for transverse control, so that the sense of body is less and good control performance is ensured.

Optionally, if the original course angle error is smaller than the course angle error boundary, the original course angle error can be corrected based on a certain correction rule to obtain the target course angle error. If the original course angle error is larger than the course angle error boundary, the original course angle error is not attenuated, and the original course angle error is directly input into a transverse controller to obtain an actual steering wheel control angle of the vehicle so as to transversely control the vehicle.

It can be understood that whether the original course angle error is attenuated is determined by setting the course angle error boundary, so that the dependence of the steering wheel control angle on the original course angle error can be effectively reduced when the error is small, and the transverse somatosensory is ensured; when the error is large, the original course angle error is still normally adopted for transverse control, so that the sense of body is less and good control performance is ensured.

S103, inputting the target state error into a transverse controller to obtain an actual steering wheel control angle of the vehicle so as to transversely control the vehicle.

In this embodiment, the actual steering wheel control angle refers to the actual steering wheel rotation angle during the running process of the vehicle. By lateral controller is meant a controller for controlling the lateral direction of a vehicle, for example outputting an actual steering wheel control angle of the vehicle.

Specifically, the target state error can be input into a transverse controller, iterative optimization processing is performed through the transverse controller, and the actual steering wheel control angle of the vehicle is output, so that transverse control of the vehicle is realized.

According to the technical scheme provided by the embodiment of the disclosure, under the condition that the vehicle is identified to be in a high-speed straight road section, the original state error of the vehicle is determined according to the current state information of the vehicle and the track point information of the planned track, then the original state error is corrected in response to the original state error being smaller than the state error boundary, the target state error is obtained, and then the target state error is input into a transverse controller to obtain the actual steering wheel control angle of the vehicle so as to transversely control the vehicle. Compared with the prior art, under the high-speed condition, the drift of other factors such as positioning and the like of the vehicle can cause the deviation of the positioning point and the actual position of the vehicle to different degrees, the transverse distance between the positioning point of the vehicle and the planned track is directly taken as the transverse error to be put into the transverse controller for calculating the steering wheel control angle, and the steering wheel of the vehicle continuously shakes left and right under the high-speed straight-road condition, so that the discomfort of riding the object is caused; according to the method and the device, the original state error value is corrected, left and right shaking of the steering wheel can be effectively restrained under the condition that the steering wheel is positioned to drift, and the stability of the vehicle is effectively improved.

On the basis of the above embodiment, as an alternative manner of the present disclosure, determining an original state error of a vehicle according to current state information of the vehicle and track point information of a planned track includes: and determining the original transverse error of the vehicle according to the current position in the current state information of the vehicle and the planning position in the track point information of the planning track.

Specifically, the distance between the current position in the current state information of the vehicle and the planned position in the track point information of the planned track may be used as the original lateral error of the vehicle.

It will be appreciated that the original lateral error of the vehicle can be quickly and reasonably obtained by determining the original lateral error from the distance between the acquired current position and the planned position of the vehicle.

On the basis of the above embodiment, as another alternative of the present disclosure, determining an original state error of the vehicle according to current state information of the vehicle and track point information of the planned track includes: and determining an original course angle error of the vehicle according to the current course angle in the current state information of the vehicle and the planned course angle in the track point information of the planned track.

Specifically, the difference between the current heading angle in the current state information of the vehicle and the planned heading angle in the track point information of the planned track can be used as an original heading angle error of the vehicle.

It can be appreciated that the original course angle error is determined directly by the difference between the current course angle and the planned course angle of the vehicle, and the original course angle error of the vehicle can be obtained quickly and reasonably.

FIG. 2 is a flow chart of another vehicle lateral control method provided in accordance with an embodiment of the present disclosure; this example provides an alternative embodiment based on the above examples by further optimizing the "correct the original state error to obtain the target state error". As shown in fig. 2, the vehicle lateral control method of the present embodiment may include:

s201, in the case that the vehicle is identified to be in a high-speed straight road section, determining an original state error of the vehicle according to current state information of the vehicle and track point information of a planned track.

Wherein the raw state error comprises a raw lateral error and/or a raw heading angle error.

S202, segmenting the original state error to obtain at least one segmented state error in response to the original state error being smaller than the state error boundary.

In this embodiment, the segmentation state error refers to a state error obtained by segmenting the original state error; optionally, the segment status error comprises a lateral segment error and/or a heading angle segment error; the transverse segmentation error refers to a segmentation error obtained by segmenting the original transverse error; the course angle error refers to a segmentation error obtained by segmenting the original course angle error.

Specifically, the original state error may be segmented based on a segmentation rule, to obtain at least one segmented state error. For example, the original state error may be divided into at least one part, and each part is taken as a segment state error, for example, the original state error is 30cm, and the original state error is divided into 3 parts, and each part is 10cm,20cm, and 30cm respectively.

Alternatively, the original lateral error may be segmented based on a segmentation rule, resulting in at least one lateral segmentation error.

Alternatively, the original heading angle error may be segmented based on a segmentation rule to obtain at least one heading angle segmentation error.

S203, configuring corresponding segment attenuation coefficients for at least one segment state error.

In this embodiment, the segment attenuation coefficient refers to the attenuation coefficient corresponding to the segment state error, and is used for reducing the state error; the segment attenuation coefficient is greater than 0 and less than or equal to 1. The larger the segmentation state error is, the larger the segmentation attenuation coefficient corresponding to the segmentation state error is; optionally, the piecewise attenuation coefficient includes a lateral piecewise attenuation coefficient and/or a heading angle piecewise attenuation coefficient. It can be understood that the dependence of the steering wheel control angle on the transverse error can be effectively reduced when the error is smaller, and the transverse body feeling is ensured; and when the error is larger, the dependence of the steering wheel control angle on the transverse error can be properly increased, so that the transverse error can be conveniently and rapidly converged, and the vehicle cannot be greatly deviated. By doing so, the error and the body feeling can be considered, so that the error and the body feeling are balanced, and the comprehensive control performance is improved.

Specifically, the corresponding segment attenuation coefficients may be configured for the at least one segment state error according to the magnitude of the at least one segment state error.

Alternatively, the corresponding transversal segment attenuation coefficients may be configured for the at least one transversal segment error according to the magnitude of the at least one transversal segment error, respectively.

Alternatively, corresponding heading angle section attenuation coefficients can be respectively configured for the at least one heading angle section error according to the magnitude of the at least one heading angle section error.

S204, determining a target attenuation coefficient from at least one segment attenuation coefficient.

In this embodiment, the target attenuation coefficient refers to the attenuation coefficient of the finally determined original state error; optionally, the target attenuation coefficient includes a target lateral attenuation coefficient and/or a target heading angle attenuation coefficient.

Alternatively, the target attenuation coefficient may be randomly determined from at least one of the segmented attenuation coefficients. Alternatively, the target transverse attenuation coefficient may be randomly determined from at least one transverse segment attenuation coefficient. Alternatively, the target heading angle attenuation coefficient may be randomly determined from at least one heading angle segment attenuation coefficient.

S205, determining a target state error according to the original state error and the target attenuation coefficient.

In the present embodiment, the target state error refers to a state error that is finally used for the vehicle lateral control; optionally, the target state error includes a target lateral error and/or a target heading angle error; wherein the target lateral error refers to a lateral error that is ultimately used for lateral control of the vehicle; the target heading angle error refers to a heading angle error that is ultimately used for lateral control of the vehicle.

Specifically, the original state error and the target attenuation coefficient may be multiplied, and the product may be used as the target state error. Alternatively, the original lateral error and the target lateral attenuation coefficient may be multiplied to obtain the target lateral error. Alternatively, the original course angle error and the target course angle attenuation coefficient may be multiplied to obtain the target course angle error.

S206, inputting the target state error into a transverse controller to obtain an actual steering wheel control angle of the vehicle so as to transversely control the vehicle.

According to the technical scheme provided by the embodiment of the disclosure, under the condition that the vehicle is identified to be in a high-speed straight road section, an original state error of the vehicle is determined according to current state information of the vehicle and track point information of a planned track, then the original state error is segmented in response to the original state error being smaller than a state error boundary, at least one segmented state error is obtained, corresponding segmented attenuation coefficients are respectively configured for the at least one segmented state error, a target attenuation coefficient is determined from the at least one segmented attenuation coefficient, and then the target state error is determined according to the original state error and the target attenuation coefficient, and finally the target state error is input into a transverse controller to obtain an actual steering wheel control angle of the vehicle so as to transversely control the vehicle. According to the technical scheme, through introducing the attenuation coefficient, the original state error is properly reduced, the dependence of the steering wheel control angle on the transverse error can be effectively reduced, and the transverse somatosensory is ensured.

On the basis of the above embodiment, as an alternative manner of the present disclosure, determining the target attenuation coefficient from the at least one piecewise attenuation coefficient includes: and interpolating at least one segment attenuation coefficient according to the original state error to obtain a target attenuation coefficient.

Specifically, at least one segment attenuation coefficient is interpolated according to the original state error, and the segment attenuation coefficient obtained by interpolation is used as a target attenuation coefficient; taking the original state error as an original transverse error as an example, if the corresponding segment transverse attenuation coefficients of at least one segment transverse error (10 cm,20cm and 30 cm) are 0.3,0.5,0.7 respectively, the original transverse error is 15cm, and the result obtained by interpolating the at least one transverse error attenuation coefficient is 0.4, taking 0.4 as the target transverse attenuation coefficient.

It can be understood that the target attenuation coefficient of the original state error is determined by a difference value mode, so that the target attenuation coefficient corresponding to the original state error can be obtained more accurately and reasonably.

Optionally, at least one transversal segment attenuation coefficient may be interpolated according to the original transversal error to obtain the target transversal attenuation coefficient. It can be understood that the target transverse attenuation coefficient of the original transverse error is determined by a difference value mode, so that the target transverse attenuation coefficient corresponding to the original transverse error can be obtained more accurately and reasonably.

Optionally, at least one heading angle segment attenuation coefficient may be interpolated according to the original heading angle error to obtain a target heading angle attenuation coefficient. It can be understood that the target course angle attenuation coefficient of the original course angle error is determined in a difference mode, so that the target course angle attenuation coefficient corresponding to the original course angle error can be accurately and reasonably obtained.

FIG. 3 is a flow chart of yet another vehicle lateral control method provided in accordance with an embodiment of the present disclosure; based on the above embodiments, the present embodiment describes in detail how to identify whether a scene in which a vehicle is located is a high-speed flat road section. As shown in fig. 3, the vehicle lateral control method of the present embodiment may include:

s301, identifying whether the vehicle is in a high-speed straight road section or not according to the planned vehicle speed and the curvature of the track points in the track point information of at least one planned track.

In this embodiment, the track point information further includes a planned vehicle speed and a track point curvature; the planned vehicle speed refers to the vehicle speed of the planned vehicle at the planned track; the track point curvature refers to the curvature of the road segment where the track is planned.

Specifically, if the planned vehicles in the track point information of the planned at least one planned track are all larger than the vehicle speed threshold value and the track point curvatures are all smaller than the curvature threshold value within a distance planned in the future, determining that the vehicles are in a high-speed straight road section. The vehicle speed threshold value can be determined according to the speed limit of the lane vehicle in high speed; the curvature threshold may be set by those skilled in the art according to the actual scene.

S302, under the condition that the vehicle is identified to be in a high-speed straight road section, determining an original state error of the vehicle according to current state information of the vehicle and track point information of a planned track.

S303, in response to the original state error being smaller than the state error boundary, correcting the original state error to obtain a target state error.

S304, inputting the target state error into a transverse controller to obtain an actual steering wheel control angle of the vehicle so as to transversely control the vehicle.

According to the technical scheme provided by the embodiment of the disclosure, whether the vehicle is positioned on a high-speed straight road section is identified according to the planned vehicle speed and the curvature of the track points in the track point information of at least one planned track, under the condition that the vehicle is positioned on the high-speed straight road section is identified, the original state error of the vehicle is determined according to the current state information of the vehicle and the track point information of the planned track, then the original state error is corrected in response to the original state error being smaller than the state error boundary, the target state error is obtained, and then the target state error is input into a transverse controller, so that the actual steering wheel control angle of the vehicle is obtained, and the vehicle is transversely controlled. According to the technical scheme, whether the scene where the vehicle is located is a high-speed straight road section or not is identified through the planned vehicle speed and the track point curvature in the track point information planned by the vehicle, and the scene where the vehicle is located can be identified rapidly and accurately.

On the basis of the above embodiment, as an alternative way of the disclosure, it is also possible to identify whether the vehicle is in a high-speed straight road section or not, and collect the lane image in the scene where the vehicle is located; and identifying the lane image, and determining whether the vehicle is in a high-speed straight road section according to the identification result.

The lane image refers to an image of a road where the collected vehicle is located.

Specifically, a lane image in a scene where the vehicle is located can be acquired from the image acquisition device in the vehicle, then the lane image can be identified based on the straight road section identification model, whether the vehicle is in a high-speed straight road section is determined according to the identification result, and if the identification result is that the lane is a straight line, the vehicle is determined to be in the high-speed straight road section.

It should be noted that the straight road section recognition model may be obtained by training in advance based on a machine learning algorithm according to a history lane image.

It can be understood that the recognition of the high-speed straight road section is performed through the lane image acquired by the vehicle, so that the recognition modes of the high-speed straight road section are enriched.

Furthermore, the planned vehicle speed, the track point curvature and the lane image in the track point information of at least one planned track can be combined to cooperatively identify whether the vehicle is positioned on a high-speed straight road section. For example, whether the vehicle is in a high-speed straight road section or not may be first identified based on the planned vehicle speed and the curvature of the track points in the track point information of at least one planned track, and then the identification result may be verified in combination with the lane image.

Fig. 4 is a schematic structural view of a vehicle lateral control device provided according to an embodiment of the present disclosure; the embodiment is suitable for the situation how to improve the stability of the steering wheel of the vehicle in an automatic driving scene. The device may be implemented in software and/or hardware and may be integrated in an electronic device carrying vehicle lateral control functions, such as a vehicle terminal, in particular an autonomous vehicle terminal. As shown in fig. 4, the vehicle lateral control device 400 of the present embodiment includes:

the original state error determining module 401 is configured to determine an original state error of the vehicle according to current state information of the vehicle and track point information of a planned track when the vehicle is identified to be in a high-speed flat road section; wherein the original state error comprises an original lateral error and/or an original course angle error;

a target state error determining module 402, configured to correct the original state error in response to the original state error being smaller than the state error boundary, to obtain a target state error;

the lateral control module 403 is configured to input the target state error into a lateral controller, and obtain an actual steering wheel control angle of the vehicle, so as to perform lateral control on the vehicle.

Further, the original state error determining module 401 is specifically configured to:

and determining the original transverse error of the vehicle according to the current position in the current state information of the vehicle and the planning position in the track point information of the planning track.

and determining an original course angle error of the vehicle according to the current course angle in the current state information of the vehicle and the planned course angle in the track point information of the planned track.

Further, the target state error determination module 402 includes:

the segmentation state error determining unit is used for segmenting the original state error to obtain at least one segmentation state error;

the segment attenuation coefficient determining unit is used for configuring corresponding segment attenuation coefficients for at least one segment state error respectively;

a target attenuation coefficient determination unit configured to determine a target attenuation coefficient from at least one segment attenuation coefficient;

and the target state error determining unit is used for determining the target state error according to the original state error and the target attenuation coefficient.

Further, the target attenuation coefficient determining unit is specifically configured to:

and interpolating at least one segment attenuation coefficient according to the original state error to obtain a target attenuation coefficient.

Further, the larger the segment state error is, the larger the segment attenuation coefficient corresponding to the segment state error is; the piecewise attenuation coefficient is greater than 0 and less than or equal to 1.

Further, the state error boundaries include lateral error boundaries; the lateral error boundary is determined from the lane width and the vehicle width.

Further, the apparatus further comprises:

and the road section identification module is used for identifying whether the vehicle is positioned on a high-speed straight road section or not according to the planned vehicle speed and the track point curvature in the track point information of at least one planned track.

Further, the road section identification module is further configured to:

collecting lane images in a scene where a vehicle is located;

and identifying the lane image, and determining whether the vehicle is in a high-speed straight road section according to the identification result.

According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

FIG. 5 is a block diagram of an electronic device for implementing a vehicle lateral control method of an embodiment of the present disclosure; fig. 5 illustrates a schematic block diagram of an example electronic device 500 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 5, the electronic device 500 includes a computing unit 501 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 502 or a computer program loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 may also be stored. The computing unit 501, ROM 502, and RAM 503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.

A number of components in electronic device 500 are connected to I/O interface 505, including: an input unit 506 such as a keyboard, a mouse, etc.; an output unit 507 such as various types of displays, speakers, and the like; a storage unit 508 such as a magnetic disk, an optical disk, or the like; and a communication unit 509 such as a network card, modem, wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

The computing unit 501 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 501 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The calculation unit 501 executes the respective methods and processes described above, such as the vehicle lateral control method. For example, in some embodiments, the vehicle lateral control method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 500 via the ROM 502 and/or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the vehicle lateral control method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the vehicle lateral control method by any other suitable means (e.g. by means of firmware).

Various implementations of the systems and techniques described here above can be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

Artificial intelligence is the discipline of studying the process of making a computer mimic certain mental processes and intelligent behaviors (e.g., learning, reasoning, thinking, planning, etc.) of a person, both hardware-level and software-level techniques. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing, and the like; the artificial intelligent software technology mainly comprises a computer vision technology, a voice recognition technology, a natural language processing technology, a machine learning/deep learning technology, a big data processing technology, a knowledge graph technology and the like.

Cloud computing (cloud computing) refers to a technical system that a shared physical or virtual resource pool which is elastically extensible is accessed through a network, resources can comprise servers, operating systems, networks, software, applications, storage devices and the like, and resources can be deployed and managed in an on-demand and self-service mode. Through cloud computing technology, high-efficiency and powerful data processing capability can be provided for technical application such as artificial intelligence and blockchain, and model training.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.

The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims

1. A vehicle lateral control method, comprising:

2. The method of claim 1, wherein determining an original state error of the vehicle based on current state information of the vehicle and track point information of a planned track comprises:

3. The method of claim 1, wherein determining an original state error of the vehicle based on current state information of the vehicle and track point information of a planned track comprises:

4. The method of claim 1, wherein correcting the raw state error to obtain a target state error comprises:

segmenting the original state error to obtain at least one segmented state error;

configuring corresponding segment attenuation coefficients for at least one segment state error respectively;

determining a target attenuation coefficient from the at least one segmented attenuation coefficient;

and determining a target state error according to the original state error and the target attenuation coefficient.

5. The method of claim 4, wherein said determining a target attenuation coefficient from at least one piecewise attenuation coefficient comprises:

6. The method of claim 4 or 5, wherein the greater the segment state error, the greater the segment attenuation coefficient corresponding to the segment state error; the piecewise attenuation coefficient is greater than 0 and less than or equal to 1.

7. The method of claim 1, wherein the state error boundary comprises a lateral error boundary; the lateral error boundary is determined from the lane width and the vehicle width.

8. The method of claim 1, further comprising:

and identifying whether the vehicle is positioned on a high-speed straight road section or not according to the planned vehicle speed and the curvature of the track points in the track point information of at least one planned track.

9. The method of claim 1, further comprising:

collecting lane images in a scene where the vehicle is located;

10. A vehicle lateral control device comprising:

11. The apparatus of claim 10, wherein the raw state error determination module is specifically configured to:

12. The apparatus of claim 10, wherein the raw state error determination module is specifically configured to:

13. The apparatus of claim 10, wherein the target state error determination module comprises:

a segmentation state error determining unit, configured to segment the original state error to obtain at least one segmentation state error;

and the target state error determining unit is used for determining a target state error according to the original state error and the target attenuation coefficient.

14. The apparatus of claim 13, wherein the target attenuation coefficient determination unit is specifically configured to:

15. The apparatus of claim 13 or 14, wherein the greater the segment state error, the greater the segment attenuation coefficient corresponding to the segment state error; the piecewise attenuation coefficient is greater than 0 and less than or equal to 1.

16. The apparatus of claim 10, wherein the state error boundary comprises a lateral error boundary; the lateral error boundary is determined from the lane width and the vehicle width.

17. The apparatus of claim 10, further comprising:

18. The apparatus of claim 10, wherein the segment identification module is further configured to:

collecting lane images in a scene where the vehicle is located;

19. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the vehicle lateral control method of any one of claims 1-9.

20. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the vehicle lateral control method according to any one of claims 1 to 9.

21. A computer program product comprising a computer program which, when executed by a processor, implements the vehicle lateral control method according to any one of claims 1-9.