CN114852085A

CN114852085A - Automatic vehicle driving track planning method based on road right invasion degree

Info

Publication number: CN114852085A
Application number: CN202210524663.8A
Authority: CN
Inventors: 李克强; 连小珉; 许庆; 陈超义; 王建强; 丛炜; 蔡孟池; 王嘉伟
Original assignee: Tsinghua University
Current assignee: Tsinghua University
Priority date: 2022-05-13
Filing date: 2022-05-13
Publication date: 2022-08-05

Abstract

The application discloses a vehicle automatic driving track planning method based on road right invasion degree, wherein the method comprises the following steps: identifying the position of an obstacle in front of the running of the vehicle according to the road environment information of the road where the vehicle is located; planning a local path according to the current position of the vehicle and the position of the obstacle to generate a plurality of vehicle feasible tracks; the optimal track of the vehicle is matched in the plurality of vehicle feasible tracks according to the road right intrusion degree of the obstacle, and the vehicle is controlled to run according to the optimal track, so that the vehicle can generate the optimal motion track in real time according to the road condition, the vehicle is controlled to run according to the optimal track, and the safety performance of automatic driving of the vehicle is greatly improved. Therefore, the problems that in the automatic driving process, the track planning accuracy is low, the curvature is discontinuous, the vehicle is difficult to execute, the safety performance cannot be guaranteed and the like are solved.

Description

Automatic vehicle driving track planning method based on road right invasion degree

Technical Field

The application relates to the technical field of automatic driving, in particular to a vehicle automatic driving track planning method based on road right invasion degree.

Background

With the development of society and the continuous improvement of the living standard of people, the number of the passenger cars in China is increased by tens of times, and the number of the passenger cars in the future is estimated to be 4 hundred million. However, the increasing energy crisis, high-load traffic pressure and social requirements for driving safety have accelerated the pace of landing unmanned technologies. As one of the cores of the unmanned technology, a trajectory planning strategy must improve the safety of an algorithm to respond to the change of the environment and avoid unnecessary personal and property losses caused by collision, and meanwhile, the strategy must also improve the completeness of the algorithm to adapt to the change of traffic, improve the comfort and reduce traffic congestion.

In the related art, an algorithm with analytic completeness or probabilistic completeness, such as a sampling method or a searching method, is generally considered to be used, but the algorithm has a blind searching process, the solving process is extremely time-consuming, a generated track is a broken line segment of a segment, the curvature is not continuous, vehicles are difficult to execute, accidents are easy to happen aiming at complex road conditions, the safety performance is low, and the problem needs to be solved urgently.

Disclosure of Invention

The application provides a vehicle automatic driving track planning method based on road right invasion degree, and aims to solve the problems that in the automatic driving process, track planning accuracy is low, curvature is discontinuous, a vehicle is difficult to execute, safety performance cannot be guaranteed and the like.

An embodiment of a first aspect of the present application provides a method for planning a vehicle automatic driving trajectory based on road right intrusion degree, including the following steps: identifying the position of an obstacle in front of the running of the vehicle according to the road environment information of the road where the vehicle is located; planning a local path according to the current position of the vehicle and the position of the obstacle to generate a plurality of vehicle feasible tracks; and matching the optimal track of the vehicle in the plurality of vehicle feasible tracks according to the road right intrusion degree of the obstacle, and controlling the vehicle to run according to the optimal track.

Optionally, in an embodiment of the present application, the planning a local path according to the current position of the vehicle and the position of the obstacle, and generating a plurality of vehicle feasible trajectories includes: and translating the position points corresponding to the obstacles on the road left and right by a first preset distance to obtain a plurality of obstacle target points, and generating a plurality of Bezier curves according to a vehicle dynamics differential equation by taking the current position of the vehicle as a starting point and the plurality of obstacle target points as a terminal point to obtain a plurality of vehicle feasible tracks.

Optionally, in an embodiment of the present application, the matching the optimal trajectory of the vehicle among the plurality of vehicle feasible trajectories according to the degree of road right intrusion of the obstacle includes: translating each vehicle feasible track left and right by a second preset distance to generate a track expected passing area of the vehicle; and taking the parallel distance from the obstacle to the central line of the track expected passing area as the road right invasion degree, taking the vehicle feasible track corresponding to the minimum value of the road right invasion degree as the optimal track of the vehicle, wherein the obstacle is not in the track expected passing area.

Optionally, in an embodiment of the present application, the controlling the vehicle to run according to the optimal trajectory includes: calculating curvatures of a plurality of preview points on the optimal track, and matching the optimal longitudinal vehicle speed according to the curvatures; calculating an optimal steering wheel angle of the vehicle by using a feed-forward-feedback control strategy according to the current position of the vehicle and the plurality of preview points; controlling the vehicle to travel according to the optimal longitudinal vehicle speed and the optimal steering wheel angle.

Optionally, in an embodiment of the present application, after controlling the vehicle to travel according to the optimal trajectory, the method further includes: comparing the current position of the vehicle with the optimal trajectory; and when the vehicle deviates from the optimal track, adjusting the vehicle speed and/or the steering wheel angle according to the vehicle deviation degree, or correcting the optimal track according to the current position of the vehicle and the position of the obstacle.

An embodiment of a second aspect of the present application provides a vehicle automatic driving trajectory planning device based on road right invasion degree, including: the identification module is used for identifying the position of an obstacle in front of the running of the vehicle according to the road environment information of the road where the vehicle is located currently; the planning module is used for planning a local path according to the current position of the vehicle and the position of the obstacle to generate a plurality of vehicle feasible tracks; and the matching module is used for matching the optimal track of the vehicle in the plurality of vehicle feasible tracks according to the road right invasion degree of the obstacle and controlling the vehicle to run according to the optimal track.

Optionally, in an embodiment of the application, the planning module is specifically configured to translate a position point corresponding to the obstacle on a road left and right by a first preset distance to obtain a plurality of obstacle target points, and generate a plurality of bezier curves according to a differential equation of vehicle dynamics with a current position of the vehicle as a starting point and the plurality of obstacle target points as a finishing point to obtain the plurality of vehicle feasible trajectories.

Optionally, in an embodiment of the present application, the matching module includes: the generating unit is used for translating each vehicle feasible track left and right by a second preset distance to generate a track expected passing area of the vehicle; and the comparison unit is used for taking the parallel distance from the obstacle to the central line of the expected passing area of the track as the road right invasion degree, taking the vehicle feasible track corresponding to the minimum value of the road right invasion degree, which is not in the expected passing area of the track, as the optimal track of the vehicle.

Optionally, in an embodiment of the present application, the matching module further includes: the first calculation unit is used for calculating the curvatures of a plurality of preview points on the optimal track and matching the optimal longitudinal vehicle speed according to the curvatures; the second calculation unit is used for calculating the optimal steering wheel angle of the vehicle by utilizing a feed-forward-feedback control strategy according to the current position of the vehicle and the plurality of preview points; a control unit for controlling the vehicle to travel according to the optimal longitudinal vehicle speed and the optimal steering wheel angle.

Optionally, in an embodiment of the present application, after controlling the vehicle to travel according to the optimal trajectory, the method further includes: the comparison module is used for comparing the current position of the vehicle with the optimal track; and the correction module is used for adjusting the vehicle speed and/or the steering wheel angle according to the vehicle deviation degree when the vehicle deviates from the optimal track, or correcting the optimal track according to the current position of the vehicle and the position of the obstacle.

An embodiment of a third aspect of the present application provides an electronic device, including: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to execute the method for planning the automatic driving track of the vehicle based on the road right invasion degree according to the embodiment.

A fourth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to execute the method for planning an automatic driving trajectory of a vehicle based on road right intrusion according to the foregoing embodiment.

Therefore, the embodiment of the application has the following beneficial effects:

the method comprises the steps of identifying the position of an obstacle in front of the running of a vehicle according to road environment information of a road where the vehicle is located currently; planning a local path according to the current position of the vehicle and the position of the obstacle to generate a plurality of vehicle feasible tracks; the optimal track of the vehicle is matched in the plurality of vehicle feasible tracks according to the road right intrusion degree of the obstacle, and the vehicle is controlled to run according to the optimal track, so that the vehicle can generate the optimal motion track in real time according to the road condition, the vehicle is controlled to run according to the optimal track, and the safety performance of automatic driving of the vehicle is greatly improved. Therefore, the problems that in the automatic driving process, the track planning accuracy is low, the curvature is discontinuous, the vehicle is difficult to execute, the safety performance cannot be guaranteed and the like are solved.

Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.

Drawings

The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

fig. 1 is a flowchart of a method for planning an automatic driving trajectory of a vehicle based on road right intrusion according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a Bezier curve provided in accordance with an embodiment of the present application;

FIG. 3 is a schematic diagram of a feasible trajectory provided in accordance with an embodiment of the present application;

FIG. 4 is a schematic diagram of trajectory selection based on road-right intrusion according to an embodiment of the present application;

FIG. 5 is a schematic illustration of a suitable desired velocity versus curvature provided in accordance with an embodiment of the present application;

FIG. 6 is a schematic diagram of a feedforward-feedback controller according to an embodiment of the present application;

FIG. 7 is a schematic diagram of a feedforward control model provided in accordance with an embodiment of the present application;

fig. 8 is a schematic diagram of a single point preview feedback control model according to an embodiment of the present application;

fig. 9 is an exemplary diagram of a vehicle automatic driving trajectory planning device based on road right intrusion degree according to an embodiment of the present application;

fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Description of reference numerals: identification module-100, planning module-200, matching module-300, memory-1001, processor-1002, and communication interface-1003.

Detailed Description

Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.

The following describes a method, an apparatus, an electronic device, and a storage medium for planning an automatic driving trajectory of a vehicle based on road right intrusion degree according to an embodiment of the present application with reference to the drawings. In order to solve the problems mentioned in the background art, the application provides a method for planning an automatic driving track of a vehicle based on road right invasion, in the method, information of road environments such as lanes, pedestrians and obstacles is collected, each target is detected, identified and tracked, then preliminary judgment is carried out on the obstacle situation in front of the vehicle operation according to the environment information collected by environment perception, feasible area analysis is carried out, an optimal track is generated, and then a vehicle transverse and longitudinal control instruction is generated according to the optimal track, so that executable action instructions such as a steering wheel corner and an accelerator pedal are obtained. Therefore, the problems that in the automatic driving process, the track planning accuracy is low, the curvature is discontinuous, the vehicle is difficult to execute, the safety performance cannot be guaranteed and the like are solved.

Specifically, fig. 1 is a flowchart of a method for planning an automatic driving trajectory of a vehicle based on road right intrusion degree according to an embodiment of the present application.

As shown in fig. 1, the method for planning the automatic driving trajectory of the vehicle based on the road right intrusion degree comprises the following steps:

in step S101, the position of an obstacle ahead of the vehicle is identified based on the road environment information of the road on which the vehicle is currently located.

In the embodiment of the application, in order to realize the trajectory planning in the automatic driving of the vehicle, firstly, the road environment information of the road where the current vehicle is located is acquired through the vehicle-mounted camera or other sensor devices, so that the environment around the vehicle is preliminarily judged according to the acquired various sensor information, the obstacle in front of the vehicle in operation is identified, the position information of the obstacle and the vehicle is acquired, and therefore the appropriate driving behavior is selected.

In step S102, a local path is planned according to the current position of the vehicle and the position of the obstacle, and a plurality of vehicle feasible trajectories are generated.

When an obstacle exists on a current lane of a vehicle and a vehicle overtaking or obstacle avoidance behavior is to be executed, an embodiment of the application may generate a series of alternative reference travel paths, which is described below.

Optionally, in an embodiment of the present application, planning a local path according to a current position of the vehicle and a position of the obstacle, and generating the plurality of feasible vehicle trajectories includes: and translating the position points corresponding to the obstacles on the road left and right by a first preset distance to obtain a plurality of obstacle target points, and generating a plurality of Bezier curves according to a vehicle dynamics differential equation by taking the current position of the vehicle as a starting point and the plurality of obstacle target points as a terminal point to obtain a plurality of vehicle feasible tracks.

As will be understood by those skilled in the art, in an autonomous driving program, there is generally a reference trajectory as a desired travel trajectory of the vehicle. The reference track is divided into aiming points, and in the vehicle single-point aiming algorithm, the aiming points are used as reference input of vehicle transverse control. As shown in fig. 2, when there is no obstacle, the vehicle is on the left side of the driving track, the reference track is on the right side, and the vehicle needs to plan the track to the right. If an obstacle exists near the vehicle reference track, the path needs to be re-planned. The function of the local path planning is to generate a vehicle-executable running track according to the information of the obstacle in front of the vehicle. When the environment perception sensor confirms that an obstacle exists in front and the vehicle and the obstacle have a collision risk, the vehicle must perform obstacle avoidance.

Therefore, in the embodiment of the present application, when the vehicle finds that there is an obstacle on the current lane through the sensor and confirms that the overtaking or obstacle avoidance behavior is to be performed, a series of candidate reference travel paths are generated according to the vehicle dynamics differential equation with the current position of the vehicle as a starting point and with poses having a series of lateral offset distances as target poses, spatial position information of the vehicle is added at each position on each travel curve, the paths where a collision will occur are screened out by comparison with position information of the obstacle, and finally only one safe curve meeting the vehicle travel requirements is kept in the same lateral position deviation, as shown in fig. 3.

In step S103, an optimal trajectory of the vehicle is matched among the plurality of vehicle feasible trajectories according to the road right intrusion degree of the obstacle, and the vehicle is controlled to travel according to the optimal trajectory.

After the plurality of feasible vehicle trajectories are obtained, further, the embodiment of the application selects the optimal trajectory from the trajectories.

Optionally, in an embodiment of the present application, matching the optimal trajectory of the vehicle among the plurality of vehicle feasible trajectories according to the degree of road right intrusion of the obstacle includes: translating each vehicle feasible track left and right by a second preset distance to generate a track expected passing area of the vehicle; and taking the parallel distance from the obstacle to the central line of the track expected passing area as the road right invasion degree, taking the vehicle feasible track corresponding to the minimum value of the road right invasion degree as the vehicle optimal track, wherein the obstacle is not in the track expected passing area.

Specifically, as shown in fig. 4, after a plurality of vehicle feasible trajectories are generated, an optimal trajectory needs to be selected among the trajectories. And respectively translating the dotted line tracks to the left and the right by taking one half of the width of the vehicle as a boundary for each track generated by the Bezier curve to generate the expected passing area of the track of the vehicle. This area represents the right of way area of the vehicle on this trajectory. Taking the parallel distance from the obstacle to the track central line as the road right invasion degree, and selecting the track according to the following two standards:

(1) the obstacle coordinates are not in the vehicle trajectory wayside area, i.e., the wayside intrusion of the obstacle is greater than one-half of the vehicle width.

(2) And generating a track corresponding to the minimum obstacle road weight intrusion degree. Therefore, a track can be selected in the left direction and the right direction respectively, and then the left direction or the right direction is selected for planning the track according to the local law. For example, in china, if it is specified that a lane change should be made to the left to overtake, the left track is selected as the optimal track. And after the track changing track is obtained, replacing the reference track by the track changing track, and changing the pre-aiming point to the reference track.

After the optimal track of the vehicle is matched in the plurality of vehicle feasible tracks according to the road right intrusion degree of the obstacle, the cloud end can plan and control the speed and the like of the vehicle running according to the optimal track.

Optionally, in an embodiment of the present application, controlling the vehicle to travel according to the optimal trajectory includes: calculating curvatures of a plurality of pre-aiming points on the optimal track, and matching the optimal longitudinal vehicle speed according to the curvatures; calculating the optimal steering wheel angle of the vehicle by utilizing a feed-forward-feedback control strategy according to the current position of the vehicle and a plurality of preview points; and controlling the vehicle to run according to the optimal longitudinal vehicle speed and the optimal steering wheel angle.

Specifically, longitudinal speed planning is primarily based on vehicle driving conditions to establish a suitable, safe driving speed expectation. In the embodiment of the application, the appropriate vehicle speed is determined according to the curvature of the preview point, and the desired speed is determined by interpolation by adopting a piecewise linear relation, as shown in fig. 5.

In the transverse speed planning, the tracking method is a single-point preview, namely, a target point is found in the driving direction of a reference path and is called as a preview point, and a certain controller is designed to minimize the deviation of certain parameters between a vehicle and the preview point so as to achieve the purpose of course tracking. The distance from the preview point to the center of the vehicle is called the preview distance l _d . A classical feedforward-feedback controller is used as shown in figure 6. The controller proposes the premise that the vehicle conforms to a linear two-degree-of-freedom vehicle model assumption. The purpose of the steering feed forward is to provide an estimate of the steering angle of a reference path that tracks known curvature and speed information, compensating for disturbances in road curvature. This reduces the gain of the feedback control, which is advantageous for stability and can reduce tracking errors. The feed forward steering angle is related only to the reference path curvature and the reference vehicle speed. Therefore, it is assumed that the vehicle center is already located on the trajectory and is to travel in accordance with the curvature of the current waypoint, as shown in fig. 7. The steering sensitivity formula can be derived:

where δ is the front wheel steering angle, u is the speed of travel, ω _r Is the yaw rate, K is the stability factor, L is the wheelbase of the front and rear axles of the vehicle,

is a curvature of

The steering angle of the front wheel can be calculated according to the curvature of the current waypoint by the above formula. After the conversion of the steering system transmission ratio, the actual input quantity of feedforward can be obtained:

since the vehicle speed is low in general experimental conditions and the influence of the stability factor is small, the stability factor K may be 0. The feedforward control quantity is then only dependent on the curvature of the road.

After the feedforward control, the feedback control functions to eliminate system deviations caused by crosswind, system uncertainty, etc. First, the yaw angle of the vehicle is defined as the angle between the longitudinal axis of the vehicle and the coordinate axis, as shown by δ in FIG. 8 _y As shown. The preview angle is the angle between the line connecting the center of the vehicle to the preview point and the coordinate axis, such as delta in FIG. 8 _p As shown. The controller is designed to minimize the difference between the preview angle and the yaw angle, e.g. delta in fig. 8 _a As shown. The action effect of the device is equivalent to that a pre-aiming point 'pulls' a vehicle to approach a reference track so as to achieve the purpose of tracking the reference track. Meanwhile, in order to further improve the tracking accuracy, the angle difference (yaw angle difference, δ in fig. 8) between the yaw angle of the vehicle and the heading (speed) of the pre-aiming point _y Shown) also takes a certain weight as a feedback input quantity to ensure that the vehicle is in the arrival stateWhen the path is considered, the deviation between the longitudinal axis direction and the reference heading is not too large, and the accuracy of path tracking is improved. However, it should be noted that the latter of the two feedback control quantities is only an auxiliary factor, the former is a main factor, and the tracking of the path mainly depends on the feedback of the angular deviation.

The final feedback controller input error is given by:

e＝(1-k)·δ _a +k·δ _y (5)

where k is a yaw angle difference weight, and may be 0 in general.

The final feedback controller selects a simple PID control, with the deviation angle described above as the controller input:

δ _fb ＝k _p e _i +k _i ·q·t∑e _i +k _d (e _i -e _i-1 )f (6)

in the formula e _i For the input error of the ith period, q is a parameter for controlling the integral input quantity to prevent integral overflow (preventing the vehicle from making aggressive motion when the integral of the error is large due to external factors), t is a control period, f is the updating frequency of the controller, and t is 1/f.

The final output reference steering angle is given by

δ＝δ _fwd +δ _fb (7)

Further, in an embodiment of the present application, after controlling the vehicle to travel according to the optimal trajectory, the method further includes: comparing the current position of the vehicle with the optimal track; when the vehicle deviates from the optimal track, the vehicle speed and/or the steering wheel angle are adjusted according to the vehicle deviation degree, or the optimal track is corrected according to the current position of the vehicle and the position of the obstacle, and the safety of the vehicle in the automatic driving process is further improved.

After the vehicle runs for a period of time according to the optimal track, comparing whether the current position of the vehicle is on the optimal track, if the current position deviates from the optimal track, correcting the position of the vehicle to enable the vehicle to return to the optimal track. Or the optimal trajectory is adjusted according to the current position of the vehicle, and the specific correction or adjustment method may use the method described in the above embodiment, which is not described again.

According to the method for planning the automatic driving track of the vehicle based on the road right invasion degree, the position of an obstacle in front of the vehicle in operation is identified according to the road environment information of the road where the vehicle is located; planning a local path according to the current position of the vehicle and the position of the obstacle to generate a plurality of vehicle feasible tracks; the optimal track of the vehicle is matched in the plurality of vehicle feasible tracks according to the road right intrusion degree of the obstacle, and the vehicle is controlled to run according to the optimal track, so that the vehicle can generate the optimal motion track in real time according to the road condition, the vehicle is controlled to run according to the optimal track, and the safety performance of automatic driving of the vehicle is greatly improved.

Next, a vehicle automatic driving trajectory planning device based on road right intrusion degree according to an embodiment of the present application will be described with reference to the drawings.

Fig. 9 is a block diagram schematically illustrating an automatic driving trajectory planning apparatus for a vehicle based on road right intrusion degree according to an embodiment of the present application.

As shown in fig. 9, the automatic driving trajectory planning apparatus 10 for a vehicle based on road right intrusion degree includes: an identification module 100, a planning module 200, and a matching module 300.

The identification module 100 is configured to identify a position of an obstacle in front of a vehicle according to road environment information of a road where the vehicle is currently located; the planning module 200 is configured to plan a local path according to a current position of the vehicle and a position of an obstacle, and generate a plurality of vehicle feasible trajectories; the matching module 300 is configured to match an optimal trajectory of the vehicle among the plurality of vehicle feasible trajectories according to the road right intrusion degree of the obstacle, and control the vehicle to run according to the optimal trajectory.

Optionally, in an embodiment of the application, the planning module 200 is specifically configured to translate a position point corresponding to an obstacle on a road left and right by a first preset distance to obtain a plurality of obstacle target points, and generate a plurality of bezier curves according to a vehicle dynamics differential equation with a current position of the vehicle as a starting point and the plurality of obstacle target points as a finishing point to obtain a plurality of vehicle feasible trajectories.

Optionally, in an embodiment of the present application, the matching module 300 includes: the generating unit is used for translating each vehicle feasible track left and right by a second preset distance to generate a track expected passing area of the vehicle; and the comparison unit is used for taking the parallel distance from the obstacle to the central line of the expected passing area of the track as the road right invasion degree, taking the vehicle feasible track corresponding to the minimum value of the road right invasion degree as the optimal track of the vehicle, wherein the obstacle is not in the expected passing area of the track.

Optionally, in an embodiment of the present application, the matching module 300 further includes: the first calculating unit is used for calculating the curvatures of a plurality of pre-aiming points on the optimal track and matching the optimal longitudinal vehicle speed according to the curvatures; the second calculation unit is used for calculating the optimal steering wheel angle of the vehicle by utilizing a feedforward-feedback control strategy according to the current position of the vehicle and a plurality of preview points; and a control unit for controlling the vehicle to run according to the optimal longitudinal vehicle speed and the optimal steering wheel angle.

It should be noted that the foregoing explanation of the embodiment of the method for planning a vehicle automatic driving trajectory based on road right invasion degree is also applicable to the apparatus for planning a vehicle automatic driving trajectory based on road right invasion degree of this embodiment, and is not repeated here.

According to the automatic driving track planning device for the vehicle based on the road right invasion degree, which is provided by the embodiment of the application, the position of an obstacle in front of the vehicle in operation is identified according to the road environment information of the road where the vehicle is located; planning a local path according to the current position of the vehicle and the position of the obstacle to generate a plurality of vehicle feasible tracks; the optimal track of the vehicle is matched in the plurality of vehicle feasible tracks according to the road right intrusion degree of the obstacle, and the vehicle is controlled to run according to the optimal track, so that the vehicle can generate the optimal motion track in real time according to the road condition, the vehicle is controlled to run according to the optimal track, and the safety performance of automatic driving of the vehicle is greatly improved.

Fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:

memory 1001, processor 1002, and computer programs stored on memory 1001 and executable on processor 1002.

The processor 1002, when executing the program, implements the method for planning an automatic driving trajectory of a vehicle based on an infringement degree of road rights provided in the above-described embodiment.

Further, the electronic device further includes:

a communication interface 1003 for communicating between the memory 1001 and the processor 1002.

A memory 1001 for storing computer programs that may be run on the processor 1002.

Memory 1001 may include high-speed RAM memory and may also include non-volatile memory (e.g., at least one disk memory).

If the memory 1001, the processor 1002, and the communication interface 1003 are implemented independently, the communication interface 1003, the memory 1001, and the processor 1002 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 10, but this is not intended to represent only one bus or type of bus.

Optionally, in a specific implementation, if the memory 1001, the processor 1002, and the communication interface 1003 are integrated on one chip, the memory 1001, the processor 1002, and the communication interface 1003 may complete communication with each other through an internal interface.

The processor 1002 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.

The present embodiment also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is configured to implement the above method for planning an automatic driving trajectory of a vehicle based on an infringement degree of road right when executed by a processor.

In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.

It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.

Claims

1. A vehicle automatic driving track planning method based on road right invasion degree is characterized by comprising the following steps:

identifying the position of an obstacle in front of the running of the vehicle according to the road environment information of the road where the vehicle is located;

planning a local path according to the current position of the vehicle and the position of the obstacle to generate a plurality of vehicle feasible tracks;

and matching the optimal track of the vehicle in the plurality of vehicle feasible tracks according to the road right intrusion degree of the obstacle, and controlling the vehicle to run according to the optimal track.

2. The method of claim 1, wherein planning a local path based on the current position of the vehicle and the position of the obstacle, and generating a plurality of vehicle feasible trajectories comprises:

and translating the position points corresponding to the obstacles on the road left and right by a first preset distance to obtain a plurality of obstacle target points, and generating a plurality of Bezier curves according to a vehicle dynamics differential equation by taking the current position of the vehicle as a starting point and the plurality of obstacle target points as a terminal point to obtain a plurality of vehicle feasible tracks.

3. The method of claim 1, wherein the matching the optimal trajectory of the vehicle among the plurality of vehicle feasible trajectories according to the degree of road-right intrusion of the obstacle comprises:

translating each vehicle feasible track left and right by a second preset distance to generate a track expected passing area of the vehicle;

and taking the parallel distance from the obstacle to the central line of the track expected passing area as the road right invasion degree, taking the vehicle feasible track corresponding to the minimum value of the road right invasion degree as the optimal track of the vehicle, wherein the obstacle is not in the track expected passing area.

4. The method of claim 1, wherein said controlling the vehicle to travel according to the optimal trajectory comprises:

calculating curvatures of a plurality of preview points on the optimal track, and matching the optimal longitudinal vehicle speed according to the curvatures;

calculating an optimal steering wheel angle of the vehicle by using a feed-forward-feedback control strategy according to the current position of the vehicle and the plurality of preview points;

controlling the vehicle to travel according to the optimal longitudinal vehicle speed and the optimal steering wheel angle.

5. The method according to any one of claims 1 to 4, further comprising, after controlling the vehicle to travel according to the optimal trajectory:

comparing the current position of the vehicle with the optimal trajectory;

and when the vehicle deviates from the optimal track, adjusting the vehicle speed and/or the steering wheel angle according to the vehicle deviation degree, or correcting the optimal track according to the current position of the vehicle and the position of the obstacle.

6. A vehicle automatic driving track planning device based on road right invasion degree is characterized by comprising:

the identification module is used for identifying the position of an obstacle in front of the running of the vehicle according to the road environment information of the road where the vehicle is located currently;

the generating module is used for planning a local path according to the current position of the vehicle and the position of the obstacle and generating a plurality of vehicle feasible tracks;

and the planning module is used for matching the optimal track of the vehicle in the plurality of vehicle feasible tracks according to the road right invasion degree of the barrier and controlling the vehicle to run according to the optimal track.

7. The apparatus according to claim 6, characterized in that the generating means are, in particular for,

8. The apparatus of claim 6, wherein the planning module comprises:

the processing unit is used for translating each vehicle feasible track left and right by a second preset distance to generate a track expected passing area of the vehicle;

and the matching unit is used for taking the parallel distance from the obstacle to the central line of the expected passing area of the track as the road right invasion degree, taking the vehicle feasible track corresponding to the minimum value of the road right invasion degree, which is not in the expected passing area of the track, as the optimal track of the vehicle.

9. The apparatus of claim 6, wherein the planning module further comprises:

the first calculation unit is used for calculating the curvatures of a plurality of preview points on the optimal track and matching the optimal longitudinal vehicle speed according to the curvatures;

the second calculation unit is used for calculating the optimal steering wheel angle of the vehicle by utilizing a feed-forward-feedback control strategy according to the current position of the vehicle and the plurality of preview points;

a control unit for controlling the vehicle to travel according to the optimal longitudinal vehicle speed and the optimal steering wheel angle.

10. The apparatus according to any one of claims 6 to 9, further comprising, after controlling the vehicle to travel according to the optimal trajectory:

the comparison module is used for comparing the current position of the vehicle with the optimal track;

and the correction module is used for adjusting the vehicle speed and/or the steering wheel angle according to the vehicle deviation degree when the vehicle deviates from the optimal track, or correcting the optimal track according to the current position of the vehicle and the position of the obstacle.

11. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method of road right intrusion based vehicle automatic driving trajectory planning according to any one of claims 1-5.

12. A computer-readable storage medium, having stored thereon a computer program, characterized in that the program is executable by a processor for implementing a method for automatic driving trajectory planning for a vehicle based on road right intrusion according to any one of claims 1-5.