CN115257729B

CN115257729B - Vehicle track planning method, device, computer equipment and storage medium

Info

Publication number: CN115257729B
Application number: CN202211016579.1A
Authority: CN
Inventors: 张佳桥
Original assignee: DeepRoute AI Ltd
Current assignee: DeepRoute AI Ltd
Priority date: 2022-08-24
Filing date: 2022-08-24
Publication date: 2025-07-29
Anticipated expiration: 2042-08-24
Also published as: CN115257729A

Abstract

The present application relates to a vehicle trajectory planning method, apparatus, computer equipment, storage medium and computer program product. The method comprises: obtaining the current speed and reference speed corresponding to at least one target traffic object; the target traffic object is a traffic object moving around a target vehicle, and the reference speed is determined based on the historical motion environment information of the target traffic object; based on the speed difference between the reference speed and the current speed, determining an abnormal traffic object from each target traffic object; based on the current speed and reference speed corresponding to the abnormal traffic object, generating a motion loss, and based on the motion loss, generating a current efficiency impact corresponding to the abnormal traffic object; based on the current efficiency impact, determining a target trajectory from each candidate trajectory corresponding to the target vehicle. The use of this method can increase the efficiency evaluation time, make the evaluation more stable, and thus improve the accuracy of the efficiency evaluation of the autonomous driving vehicle trajectory.

Description

Vehicle track planning method, device, computer equipment and storage medium

Technical Field

The present application relates to the field of computer technology, and in particular, to a vehicle track planning method, apparatus, computer device, storage medium, and computer program product.

Background

With the development of computer technology, automatic driving technology has emerged, which employs advanced communication, computer, network and control technologies, so that computer devices can automatically and safely operate vehicles without any human initiative.

In the conventional technology, when planning a track for a vehicle, it is common to evaluate information of the track itself, for example, the speed, length, time used, etc. of candidate tracks, and determine a target track from a plurality of candidate tracks based on the evaluation result. However, the target track is determined based on the information of the track, the information available for reference is limited, and the problem of inaccurate track planning exists.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a vehicle trajectory planning method, apparatus, computer device, computer readable storage medium, and computer program product that can improve the accuracy of trajectory planning.

The application provides a vehicle track planning method. The method comprises the following steps:

The method comprises the steps of obtaining a current speed and a reference speed corresponding to at least one target traffic object, wherein the target traffic object is a traffic object moving around a target vehicle, and the reference speed is determined based on historical movement environment information of the target traffic object;

Determining an abnormal traffic object from among the respective target traffic objects based on a speed difference between the reference speed and the current speed;

Generating motion loss based on the current speed and the reference speed corresponding to the abnormal traffic object, and generating current efficiency influence degree corresponding to the abnormal traffic object based on the motion loss;

determining an intermediate track corresponding to the abnormal traffic object from each candidate track corresponding to the target vehicle, and generating track efficiency information corresponding to the intermediate track based on the current efficiency influence degree;

and determining a target track from the candidate tracks based on the track efficiency information.

The application also provides a vehicle track planning device. The device comprises:

the speed acquisition module is used for acquiring the current speed and the reference speed corresponding to at least one target traffic object, wherein the target traffic object is a traffic object moving around a target vehicle, and the reference speed is determined based on the historical movement environment information of the target traffic object;

An abnormal traffic object determining module for determining an abnormal traffic object from among the respective target traffic objects based on a speed difference between the reference speed and the current speed;

the current efficiency influence degree calculation module is used for generating motion loss based on the current speed and the reference speed corresponding to the abnormal traffic object and generating the current efficiency influence degree corresponding to the abnormal traffic object based on the motion loss;

The track efficiency information determining module is used for determining an intermediate track corresponding to the abnormal traffic object from each candidate track corresponding to the target vehicle, and generating track efficiency information corresponding to the intermediate track based on the current efficiency influence degree;

And the target track determining module is used for determining target tracks from the candidate tracks based on the track efficiency information.

A computer device comprising a memory storing a computer program and a processor implementing the steps of the vehicle trajectory planning method described above when the processor executes the computer program.

A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the vehicle trajectory planning method described above.

A computer program product comprising a computer program which, when executed by a processor, implements the steps of the vehicle track planning method described above.

The vehicle track planning method, device, computer equipment, storage medium and computer program product are used for acquiring the current speed and the reference speed corresponding to at least one target traffic object, wherein the target traffic object is a traffic object moving around the target vehicle, the reference speed is determined based on historical motion environment information of the target traffic object, abnormal traffic objects are determined from all the target traffic objects based on speed differences between the reference speed and the current speed, motion loss is generated based on the current speed and the reference speed corresponding to the abnormal traffic object, current efficiency influence degree corresponding to the abnormal traffic object is generated based on the motion loss, intermediate tracks corresponding to the abnormal traffic object are determined from all candidate tracks corresponding to the target vehicle, track efficiency information corresponding to the intermediate tracks is generated based on the current efficiency influence degree, and the target track is determined from all the candidate tracks based on the track efficiency information. In this way, the target traffic object is a traffic object moving around the target vehicle, the abnormal traffic object can be determined from the target traffic object based on the speed difference between the current speed and the reference speed corresponding to the target traffic object, the abnormal traffic object can have a larger influence on the running of the target vehicle, and the accuracy of track planning can be effectively improved by referring to the related information of the abnormal traffic object when the running track of the target vehicle is planned. Further, motion loss can be generated based on the current speed and the reference speed corresponding to the abnormal traffic object, current efficiency influence degree corresponding to the abnormal traffic object can be generated based on the motion loss, the current efficiency influence degree can reflect influence degree of the abnormal traffic object on track efficiency of a running track of the target vehicle, track efficiency information of candidate tracks corresponding to the abnormal traffic object is generated based on the current efficiency influence degree, the target track is determined from the candidate tracks corresponding to the target vehicle based on the track efficiency information, and accuracy of track planning can be effectively improved.

Drawings

FIG. 1 is an application environment diagram of a vehicle trajectory planning method in one embodiment;

FIG. 2 is a flow chart of a vehicle trajectory planning method in one embodiment;

FIG. 3 is a schematic diagram of determining whether a traffic object is a reference traffic object in one embodiment;

FIG. 4 is a velocity change image of a traffic participant in one embodiment;

FIG. 5 is a flowchart illustrating determining track efficiency information corresponding to an intermediate track according to an embodiment;

FIG. 6 is a schematic diagram of determining whether an abnormal traffic object has an effect on a trajectory in one embodiment;

FIG. 7 is a block diagram of a vehicle trajectory planning device in one embodiment;

FIG. 8 is an internal block diagram of a computer device in one embodiment;

Fig. 9 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

The vehicle track planning method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices, which may be smart televisions, smart car devices, and the like. The portable wearable device may be a smart watch, a smart headset, or the like. The server 104 may be implemented as a stand-alone server or as a server cluster or cloud server composed of a plurality of servers. The terminal 102 and the server 104 may be directly or indirectly connected through wired or wireless communication, and the present application is not limited herein.

The terminal and the server can be independently used for executing the vehicle track planning method provided by the embodiment of the application.

For example, the terminal obtains a current speed and a reference speed corresponding to at least one target traffic object, and determines an abnormal traffic object from among the respective target traffic objects based on a speed difference between the reference speed and the current speed. Wherein the target traffic object is a traffic object moving around the target vehicle, and the reference speed is determined based on historical movement environment information corresponding to the target traffic object. The terminal generates motion loss based on the current speed and the reference speed corresponding to the abnormal traffic object, generates current efficiency influence degree corresponding to the abnormal traffic object based on the motion loss, determines intermediate tracks corresponding to the abnormal traffic object from candidate tracks corresponding to the target vehicle, and generates track efficiency information corresponding to the intermediate tracks based on the current efficiency influence degree. The terminal determines a target track from among the candidate tracks based on the track efficiency information.

The terminal and the server can also cooperate to perform the vehicle track planning method provided in the embodiments of the present application.

For example, the terminal sends a vehicle trajectory planning request to a server, the server obtains a current speed and a reference speed corresponding to at least one target traffic object, and determines an abnormal traffic object from among the target traffic objects based on a speed difference between the reference speed and the current speed. Wherein the target traffic object is a traffic object moving around the target vehicle, and the reference speed is determined based on historical movement environment information corresponding to the target traffic object. The server generates motion loss based on the current speed and the reference speed corresponding to the abnormal traffic object, generates current efficiency influence degree corresponding to the abnormal traffic object based on the motion loss, determines intermediate tracks corresponding to the abnormal traffic object from candidate tracks corresponding to the target vehicle, and generates track efficiency information corresponding to the intermediate tracks based on the current efficiency influence degree. The server determines a target track from among the candidate tracks based on the track efficiency information. And the server sends the target track to the terminal. The terminal can display the target track and can also run according to the target track.

In one embodiment, the terminal 102 may be installed with an application that enables vehicle trajectory planning. The server 104 may be a background server of a vehicle trajectory planning application installed in the terminal 102. In one embodiment, the terminal 102 is a target vehicle.

In one embodiment, as shown in fig. 2, a vehicle track planning method is provided, and the method is applied to a computer device, which may be a terminal or a server, for example, and includes the following steps:

in step S202, a current speed and a reference speed corresponding to at least one target traffic object are obtained, wherein the target traffic object is a traffic object moving around the target vehicle, and the reference speed is determined based on historical movement environment information of the target traffic object.

The traffic object is an object that can move on a road, such as pedestrians, non-motor vehicles, sprinkler, buses, private cars, etc. The target vehicle refers to a vehicle for which trajectory planning is required. The target traffic object is a traffic object that moves around the target vehicle, for example, if the distance between the traffic object and the target vehicle is within a preset range.

The current speed corresponding to the target traffic object refers to the speed of the target traffic object in the current time period, and can reflect the current movement condition of the target traffic object. The reference speed corresponding to the target traffic object is determined based on the historical motion environment information corresponding to the target traffic object, and can reflect the past motion condition of the target traffic object. The historical movement environment information is used for reflecting the movement environment of the target traffic object in the historical time period, and the historical movement environment information can comprise at least one of movement information corresponding to surrounding movement objects of the target traffic object or traffic speed limit information corresponding to the target traffic object in the historical time period.

Specifically, when the computer device performs track planning on the target vehicle, a traffic object moving around the target vehicle may be obtained as a target traffic object, a current speed and a reference speed corresponding to at least one target traffic object are obtained, and track planning is performed with reference to the current speed and the reference speed corresponding to the target traffic object, so as to improve accuracy of track planning.

Step S204, determining an abnormal traffic object from among the respective target traffic objects based on the speed difference between the reference speed and the current speed.

The abnormal traffic object refers to a target traffic object with a great difference between the current movement condition and the historical movement condition.

Specifically, after the computer device obtains the current speed and the reference speed of each target traffic object corresponding to the target vehicle, the current speed of the same target traffic object is compared with the reference speed, and an abnormal traffic object is determined from each target traffic object based on the speed difference between the reference speed and the current speed. For example, a target traffic object whose speed difference is greater than a preset difference may be determined as an abnormal traffic object. It can be understood that if the speed difference between the reference speed and the current speed is larger, which indicates that there is a larger difference between the current movement condition and the historical movement condition of the target traffic object, the target traffic object has an abnormal condition, and such target traffic object may have a certain influence on the running of the target vehicle, and such target traffic object may be used as an abnormal traffic object, so that when the track planning is performed on the target vehicle, the accuracy of the track planning may be effectively improved.

Step S206, generating motion loss based on the current speed and the reference speed corresponding to the abnormal traffic object, and generating the current efficiency influence corresponding to the abnormal traffic object based on the motion loss.

The motion loss refers to the loss caused by the abnormal traffic object traveling according to the current speed and the reference speed, and is used for reflecting the motion difference condition of the abnormal traffic object in the past and the present. The current efficiency influence degree refers to influence degree of the abnormal traffic object on track efficiency of the running track of the target vehicle, and is used for reflecting influence degree of the abnormal traffic object on track efficiency of the running track of the target vehicle.

Specifically, after determining the abnormal traffic object, the computer device may calculate a motion loss based on the current speed and the reference speed corresponding to the abnormal traffic object, for example, may calculate a speed difference between the current speed and the reference speed corresponding to the abnormal traffic object, and obtain the motion loss based on the speed difference. Further, the computer device may calculate a current efficiency impact level corresponding to the abnormal traffic object based on the motion loss. The computer device may calculate the current efficiency impact level based on the motion loss using a variety of methods. For example, the motion loss may be directly used as the current efficiency influence degree, the product of the motion loss and a preset value may be used as the current efficiency influence degree, and the like.

Step S208, determining an intermediate track corresponding to the abnormal traffic object from the candidate tracks corresponding to the target vehicles, and generating track efficiency information corresponding to the intermediate track based on the current efficiency influence degree.

The candidate track refers to a running track of the target vehicle which can be selected. The middle track refers to a candidate track corresponding to an abnormal traffic object, and refers to a candidate track affected by the abnormal traffic object. The track efficiency information is used for representing the running efficiency of the vehicle on the track and is used for representing the track efficiency of the running track.

Specifically, after determining the current efficiency impact level corresponding to the abnormal traffic object, the computer device may determine the target track from the respective candidate tracks corresponding to the target vehicle based on the current efficiency impact level. First, the computer device may determine an intermediate track corresponding to the abnormal traffic object from among the respective candidate tracks corresponding to the target vehicle, for example, a candidate track having a coincidence with a traveling track of the abnormal traffic object may be taken as an intermediate track corresponding to the abnormal traffic object, a candidate track having a coincidence with a moving direction of the abnormal traffic object may be taken as an intermediate track corresponding to the abnormal traffic object, a candidate track having an absolute distance between the abnormal traffic object and the target vehicle smaller than a preset distance may be taken as an intermediate track corresponding to the abnormal traffic object, and so on. Furthermore, the computer device may generate track efficiency information corresponding to the intermediate track based on the current efficiency influence degree corresponding to the abnormal traffic object, for example, the current efficiency influence degree may be used as track efficiency information, the current efficiency influence degree may be scaled to obtain track efficiency information, and so on.

Step S210, determining a target track from the candidate tracks based on the track efficiency information.

The target track refers to a running track finally determined by the target vehicle.

Specifically, after determining the track efficiency information corresponding to the intermediate track, the computer device may determine the target track from the candidate tracks based on the track efficiency information, for example, if the smaller the track efficiency information indicates the higher the track efficiency, the candidate track with the smallest track efficiency information is taken as the target track. After determining the target trajectory, the computer device may instruct the target vehicle to travel according to the target trajectory to improve the traveling efficiency of the target vehicle.

It can be understood that, besides the intermediate track, the track efficiency information of other candidate tracks can be preset efficiency information, and can also be calculated based on a custom formula or algorithm.

In one embodiment, the candidate tracks may be divided into a first type of track and a second type of track, where the first type of track is a middle track, and refers to a candidate track that may be affected by an abnormal traffic object, and the second type of track refers to a candidate track that may not be affected by an abnormal traffic object. The computer device may generate track efficiency information corresponding to the first type of track based on the current efficiency influence of the corresponding abnormal traffic object, and generate track efficiency information corresponding to the second type of track based on the track efficiency information corresponding to the first type of track, where the track efficiency indicated by the track efficiency information corresponding to the second type of track is higher than the track efficiency indicated by the track efficiency information corresponding to the first type of track. For example, the candidate tracks include a track a and a track B, the track a is a first type track, the track B is a second type track, track efficiency information corresponding to the track a is generated based on a current efficiency influence degree corresponding to an abnormal traffic object that affects the track a, and track efficiency information corresponding to the track B is generated based on the track efficiency information corresponding to the track a. If the smaller the track efficiency information is, the higher the track efficiency is, and the track efficiency information corresponding to the track B should be smaller than the track efficiency information corresponding to the track A.

It can be appreciated that the target vehicle is not affected by the abnormal traffic object while traveling on the second type of track as compared to the first type of track, so the track efficiency of the second type of track is higher than the track efficiency of the first type of track.

In one embodiment, the target vehicle is an autonomous vehicle and the candidate trajectory is generated by a trajectory planning module of the autonomous vehicle. Candidate trajectories may be generated for the autonomous vehicle at regular times, a plurality of candidate trajectories may be generated for each planning period, and a target trajectory may be determined from the respective candidate trajectories based on the trajectory efficiency information within each trajectory period. Furthermore, in addition to the track efficiency information, other information may be combined to comprehensively determine the target track from the candidate tracks. For example, the target track can be determined from each candidate track based on track efficiency information, track safety information and track comfort information, track evaluation is comprehensively performed from three aspects of safety, comfort and efficiency, and the target vehicle is helped to make final track selection.

The vehicle track planning method comprises the steps of obtaining the current speed and the reference speed corresponding to at least one target traffic object, determining the reference speed of the traffic object moving around the target vehicle based on historical motion environment information of the target traffic object, determining abnormal traffic objects from all the target traffic objects based on speed differences between the reference speed and the current speed, generating motion loss based on the current speed and the reference speed corresponding to the abnormal traffic objects, generating current efficiency influence degree corresponding to the abnormal traffic objects based on the motion loss, determining intermediate tracks corresponding to the abnormal traffic objects from all candidate tracks corresponding to the target vehicle, generating track efficiency information corresponding to the intermediate tracks based on the current efficiency influence degree, and determining the target track from all the candidate tracks based on the track efficiency information. In this way, the target traffic object is a traffic object moving around the target vehicle, the abnormal traffic object can be determined from the target traffic object based on the speed difference between the current speed and the reference speed corresponding to the target traffic object, the abnormal traffic object can have a larger influence on the running of the target vehicle, and the accuracy of track planning can be effectively improved by referring to the related information of the abnormal traffic object when the running track of the target vehicle is planned. Further, motion loss can be generated based on the current speed and the reference speed corresponding to the abnormal traffic object, current efficiency influence degree corresponding to the abnormal traffic object can be generated based on the motion loss, the current efficiency influence degree can reflect influence degree of the abnormal traffic object on track efficiency of a running track of the target vehicle, track efficiency information of candidate tracks corresponding to the abnormal traffic object is generated based on the current efficiency influence degree, the target track is determined from the candidate tracks corresponding to the target vehicle based on the track efficiency information, and accuracy of track planning can be effectively improved.

In one embodiment, step S202 includes:

The method comprises the steps of obtaining a traffic object which is in a target range from a current target traffic object in a historical time period and is consistent with the movement direction of the current target traffic object as a reference traffic object corresponding to the current target traffic object, wherein the target range is increased along with the increase of the historical speed of the current target traffic object in the historical time period, no traffic blocking object exists between the current target traffic object and the reference traffic object, counting the movement speed of the reference traffic object in the historical time period to obtain a reference sub-speed corresponding to the current target traffic object in the historical time period, and obtaining a reference speed corresponding to the current target traffic object based on the reference sub-speed corresponding to the current target traffic object in the historical time period.

Wherein the current target traffic object refers to the currently processed target traffic object. The current target traffic object may be any target traffic object. The reference traffic object refers to a traffic object which is consistent with the moving direction of the target traffic object, moves within the target range of the target traffic object, and does not have a traffic blocking object with the target traffic object. The traffic blocking object is an object that can block traffic objects such as traffic lights, sidewalks, and stop signs.

Specifically, the computer device may count the movement speeds of traffic objects moving around the target traffic object for a historical period of time to generate a reference speed corresponding to the target traffic object.

First, the computer device may set a traffic object, which is consistent with the moving direction of the current target traffic object and moves within the target range of the current target traffic object and between which there is no traffic blocking object, as a reference traffic object corresponding to the current target traffic object. It will be appreciated that when a traffic object surrounding a certain target traffic object can be used as a reference traffic object, the following condition should be satisfied that 1, the absolute distance between the surrounding traffic object of the target traffic object and the target traffic object cannot exceed a distance threshold, and the distance threshold is positively related to the historical speed of the target traffic object in the historical time period. For example, as shown in fig. 3 (a), when the absolute distance between the surrounding traffic objects of the target traffic object and the target traffic object exceeds the distance threshold, it is indicated that the surrounding traffic object is far away from the current target traffic object, and it is difficult to influence the current target traffic object, so that such a surrounding traffic object cannot be used as a reference traffic object thereof. 2. The surrounding traffic of the target traffic cannot be blocked by the traffic blocking object, for example, as shown in fig. 3 (b), the surrounding traffic of the target traffic is blocked by a red light, and if the target traffic is behind the red light, the surrounding traffic before the red light cannot be used as the reference traffic. 3. The surrounding traffic objects of the target traffic object should have the same movement intention as the target traffic object. For example, as shown in fig. 3 (c), a surrounding traffic object whose movement intention is to go straight forward and turn right cannot be regarded as its reference traffic object. The reference traffic object of the target traffic object may be referred to as a reference traffic flow around the target traffic object, and other surrounding traffic objects of the target traffic object may be referred to as non-reference traffic flows around the target traffic object. Furthermore, one target traffic object may have at least one reference traffic object.

Furthermore, the computer device calculates the movement speed of the reference traffic object in the historical time period, obtains the reference sub-speed corresponding to the current target traffic object in the historical time period based on the movement speed of the reference traffic object in the historical time period, for example, the average value of the movement speeds of the reference traffic objects in the historical time period can be calculated as the reference sub-speed, the weighted average value of the movement speeds of the reference traffic objects in the historical time period can be calculated as the reference sub-speed, the weight corresponding to the reference traffic object can be determined according to the distance between the reference traffic object and the current target traffic object, and the closer the distance is, the larger the weight is, and the like. It will be appreciated that the computer device may obtain the speed of movement of individual traffic objects on the road from sensors provided on the target vehicle or sensors provided on the road side or from other devices. Reference traffic objects existing around a certain target traffic object include sprinkler, bus and non-motor vehicles as shown in fig. 4, and fig. 4 shows the moving speed of each reference traffic object over a history period of time. When the bus stops, the bus can show a tendency of decelerating to 0 and accelerating. The sprinkler is usually near uniform speed and keeps running at low speed. Non-motor vehicles (e.g., bicycles) typically have large speed fluctuations, but remain traveling at low speeds throughout.

Finally, the computer device may obtain a reference speed corresponding to the current target traffic object based on the reference sub-speed corresponding to the current target traffic object in the historical time period, for example, using the reference sub-speed as the reference speed.

In the above embodiment, a traffic object whose distance from the current target traffic object in the history period is within the target range and coincides with the moving direction of the current target traffic object and which does not have a traffic blocking object with the current target traffic object is acquired as the reference traffic object corresponding to the current target traffic object. And the traffic object which can obviously influence the target traffic object is obtained through various limiting conditions to serve as a reference traffic object, so that the accuracy of determining the reference speed of the target traffic object is improved. The target range is increased along with the increase of the historical speed of the current target traffic object in the historical time period, and the larger the movement speed of the target traffic object is, the larger the selection range of the reference traffic object is, so that the accuracy of determining the reference speed of the target traffic object is further improved. And counting the movement speed of the reference traffic object in the historical time period to obtain the reference sub-speed corresponding to the current target traffic object in the historical time period, and obtaining the reference speed corresponding to the current target traffic object based on the reference sub-speed corresponding to the current target traffic object in the historical time period. In this way, the historical speed of the reference traffic object can effectively reflect the speed of the traffic flow around the target traffic object, the reference speed of the current target traffic object is determined based on the movement speed of the reference traffic object in the historical time period, the accuracy of the reference speed can be effectively improved, and the accuracy of track planning is further improved.

In one embodiment, a vehicle trajectory planning method includes:

And when the current target traffic object does not have the reference traffic object in the historical time period, obtaining the reference sub-speed corresponding to the current target traffic object in the historical time period based on the traffic speed limit information of the current target traffic object in the historical time period.

The traffic speed limit information is used for limiting the movement speed of the traffic object, and can specifically include speed limit information brought by roads and objects on the roads. Traffic speed limit information includes, for example, legal speed limits for roads, speed limits imposed by objects with road semantic information. The speed limit imposed by the object with road semantic information includes speed limit imposed by traffic lights, speed reduction imposed by stop signs, etc.

Specifically, if the current target traffic object does not have the reference traffic object in the historical time period, the computer device may calculate the reference sub-speed according to traffic speed limit information of the current target traffic object on the driving road in the historical time period, for example, a minimum value of each speed in the traffic speed limit information may be used as the reference sub-speed, each speed in the traffic speed limit information may be ranked from small to large, an average value of at least two speeds ranked forward may be calculated as the reference sub-speed, and so on.

In the above embodiment, if the current target traffic object does not have a reference traffic object in the historical time period, in order to avoid that the reference sub-speed is empty, the reference sub-speed of the current target traffic object may be calculated by traffic speed limit information of the current target traffic object on the road where the current target traffic object is located in the historical time period, and the traffic speed limit information may reflect the movement condition of the target traffic object from the side, so that the reference sub-speed determined based on the traffic speed limit information also has a certain accuracy, and is also helpful to effectively improve the accuracy of track planning.

In one embodiment, obtaining the reference speed corresponding to the current target traffic object based on the reference sub-speed corresponding to the current target traffic object in the historical time period includes:

the method comprises the steps of obtaining reference sub-speeds of a current target traffic object corresponding to at least two historical time periods respectively, generating speed weights of the reference sub-speeds corresponding to the historical time periods based on time differences of the historical time periods and the current time period, reducing the speed weights along with the increase of the time differences, and fusing the reference sub-speeds based on the speed weights of the reference sub-speeds to obtain the reference speeds corresponding to the current target traffic object.

Specifically, in order to improve accuracy of the reference speed, the computer device may acquire reference sub-speeds corresponding to the current target traffic object in at least two historical time periods, and perform weighted fusion on the respective reference sub-speeds to generate a reference speed corresponding to the target traffic object. The computer equipment obtains the reference sub-speeds respectively corresponding to the current target traffic object in at least two historical time periods, and generates the speed weight corresponding to the reference sub-speed corresponding to each historical time period according to the time difference between each historical time period and the current time period. It can be understood that the reference value of the data reflected by the history period that is closer to the current period is higher, and the reference value of the data reflected by the history period that is farther from the current period is lower, and therefore, the speed weight can be reduced with an increase in the time difference. And then, the computer equipment carries out weighted average on each reference sub-speed based on the speed weight corresponding to each reference sub-speed to obtain the final reference speed of the target traffic object.

In one embodiment, the velocity weight may be calculated by the following formula:

N=T/delta_t

t_i＝t_O-i*delta_t

W_i=2*(N-i)/(N*(N+1))

Wherein T is the statistical duration of the reference speed, and delta_t is the statistical period. For example, counting the reference sub-speeds every 10 seconds, calculating the reference speeds from each reference sub-speed for the past 5 minutes, delta_t is 10 seconds, and T is 5 minutes. N is the total number of time frames, t ₀ is the current time, t _i is a past time, indicating the past time i statistical cycles from the current time, and W _i is the speed weight corresponding to t _i.

In one embodiment, the computer device calculates the speed of each reference traffic object corresponding to the target traffic object once every preset time interval, for example, the preset time interval may be 0.1s, and simultaneously calculates the average value of the speeds of all the reference traffic objects as the reference sub-speeds of the target traffic object. The computer device counts a weighted average of all the reference sub-speeds of the target traffic object over a period of time as the reference speed.

In the above embodiment, different speed weights are given to the reference sub-speeds corresponding to each historical time period according to the difference between each historical time period and the current time period, the higher the speed weight of the reference sub-speed corresponding to the historical time period closer to the current time period is, the weighted average is performed on each reference sub-speed to obtain the final reference speed of the target traffic object, and the calculated reference speed has higher accuracy, so that the accuracy of track planning is improved.

In one embodiment, step S204 includes:

and obtaining the speed difference proportion corresponding to each target traffic object based on the ratio between the speed difference corresponding to the same target traffic object and the reference speed, and taking the target traffic object with the speed difference proportion larger than the preset proportion as an abnormal traffic object.

The speed difference corresponding to the target traffic object refers to the difference between the reference speed and the current speed of the target traffic object. The preset proportion refers to a threshold value of a speed difference proportion when judging whether the target traffic object is an abnormal traffic object, and when the speed difference proportion is larger than the threshold value, the target traffic object is judged to be the abnormal traffic object. The preset proportion is a preset proportion threshold value, and can be specifically set according to actual needs.

Specifically, the computer equipment acquires a reference speed and a current speed corresponding to a target traffic object, calculates a ratio of a speed difference determined by the reference speed and the current speed to the reference speed as a speed difference ratio, and when the speed difference ratio corresponding to a certain target traffic object is larger than a preset ratio, indicates that the difference between the current movement condition and the historical movement condition of the target traffic object is larger, so that the target traffic object is judged to be an abnormal traffic object.

In one embodiment, the abnormal traffic object may be determined by the following formula:

Wherein V _ref is the reference speed of the target traffic object, V ₁ is the current speed of the target traffic object, The speed difference ratio is represented by T, which is a threshold value of the speed difference ratio when determining whether or not the target traffic object is an abnormal traffic object.

And when result >0, judging that the target traffic object is an abnormal traffic object.

In the above embodiment, by comparing the ratio between the speed difference corresponding to the target traffic object and the reference speed with the preset ratio, it is determined whether the target traffic object is an abnormal traffic object, and it is able to quickly determine whether the target traffic object is an abnormal traffic object.

In one embodiment, generating a motion loss based on a current speed and a reference speed corresponding to an abnormal traffic object includes:

the method comprises the steps of calculating first displacement corresponding to an abnormal traffic object based on a current speed corresponding to the abnormal traffic object and a preset time period, calculating second displacement corresponding to the abnormal traffic object based on a reference speed corresponding to the abnormal traffic object and the preset time period, and generating motion loss based on the first displacement and the second displacement.

The preset time period is a preset time period, and can be set according to actual needs. In one embodiment, the preset time period may be a planning period of the vehicle track. The first displacement refers to a distance that an abnormal traffic object can travel according to the current speed in a preset time period. The second displacement refers to a distance that the abnormal traffic object can travel according to the reference speed within a preset time period.

Specifically, the computer equipment obtains the current speed and the reference speed of the abnormal traffic object, calculates the first displacement and the second displacement obtained by the abnormal traffic object respectively according to the current speed and the reference speed in a preset running period, and finally generates the motion loss based on the first displacement and the second displacement. For example, the difference in position between the first displacement and the second displacement is taken as a loss of motion, the ratio of the difference in position between the first displacement and the second displacement to the second displacement is taken as a loss of motion, and so on.

In the embodiment, the first displacement corresponding to the abnormal traffic object is calculated based on the current speed corresponding to the abnormal traffic object and the preset time period, the second displacement corresponding to the abnormal traffic object is calculated based on the reference speed corresponding to the abnormal traffic object and the preset time period, and the motion loss is generated based on the first displacement and the second displacement. In this way, the losses generated by the first displacement and the second displacement may reflect past and present motion differences of the abnormal traffic object, and such motion losses help to improve the accuracy of the influence degree of the current efficiency of the subsequent calculation.

In one embodiment, generating a current efficiency impact for an abnormal traffic object based on motion loss includes:

The method comprises the steps of obtaining statistics times of historical efficiency influence degrees corresponding to abnormal traffic objects, generating loss weights based on the statistics times, enabling the loss weights to increase along with the increase of the statistics times and approach to a target value, and generating current efficiency influence degrees based on the loss weights and motion losses.

The historical efficiency influence degree refers to the efficiency influence degree calculated by the abnormal traffic object in the historical time period. The computer equipment can calculate the corresponding efficiency influence degree of the abnormal traffic object at regular time, and when the current efficiency influence degree is calculated, the previously calculated efficiency influence degree is the historical efficiency influence degree. For example, the efficiency impact is calculated once for an abnormal traffic object in each track period, and as the number of planning periods increases, the statistics of the historical efficiency impact also increase.

Specifically, in generating the current efficiency influence degree based on the motion loss, the accuracy of the current efficiency influence degree may be improved with reference to the number of times of calculation of the efficiency influence degree. After obtaining the motion loss corresponding to the abnormal traffic object, the computer equipment calculates the loss weight based on the statistical times of the historical efficiency influence degree corresponding to the abnormal traffic object. The loss weight increases with the increase of the statistics, that is, the greater the number of times of calculation of the efficiency influence, the higher the loss weight, and the loss weight approaches the target value with the increase of the statistics, that is, the greater the number of times of calculation of the efficiency influence, the loss weight does not increase blindly, and is gradually smoothed and approaches the target value. After obtaining the loss weight corresponding to the abnormal traffic object, the computer equipment calculates the current efficiency influence degree corresponding to the abnormal traffic object based on the loss weight and the motion loss. For example, the product of the loss weight and the motion loss is used as the current efficiency effect, the product of the loss weight and the motion loss is added with a constant value as the current efficiency effect, and the like.

In one embodiment, the motion loss and the current efficiency impact level may be calculated by the following formula:

Wherein i-1 is the statistics of the historical efficiency influence degree corresponding to the abnormal traffic object, J _i is the motion loss, V _ref is the reference speed of the target traffic object, and V _i is the current speed of the target traffic object. the time length of t _i is a constant parameter, and is mainly determined by the time period of the predicted trajectory of the object (i.e. the trajectory planning period), for example, the time length of t _i may be 5s. The cost _i is the i-th calculated efficiency influence (which may also be referred to as the current efficiency influence) corresponding to the abnormal traffic object, and γ is the specific gravity of the historical efficiency influence and the current efficiency influence, and is a constant value, for example, γ may be a constant value of 0.5. It will be appreciated that the larger i, the closer the cost _i will be to J _i, and as i is progressively incremented, the cost _i term will progressively tend to J _i, ensuring that the data is smooth and will not increment infinitely over time.

In the above embodiment, the computer device generates the loss weight based on the statistics number of the historical efficiency influence degrees corresponding to the abnormal traffic object, and performs the weighted calculation on the loss weight and the motion loss to obtain the current efficiency influence degree, when the statistics number is gradually accumulated, the current efficiency influence degree gradually tends to the motion loss, so that the current efficiency influence degree value can be ensured to be smoother, the accuracy of the current efficiency influence degree can not be improved along with the increase of the accumulation number, and the accuracy of the track planning is further improved effectively.

In one embodiment, as shown in fig. 5, step S208 includes:

step S502, corresponding intermediate tracks are determined from the candidate tracks based on the current motion information of the abnormal traffic objects, and the intermediate tracks corresponding to the abnormal traffic objects are obtained.

And step S504, generating track efficiency information based on the current efficiency influence degree of each abnormal traffic object corresponding to the same intermediate track, and obtaining track efficiency information corresponding to each intermediate track.

The current motion information refers to current motion information of an abnormal traffic object and is used for reflecting current motion conditions of the abnormal traffic object. The current movement information may include at least one of a travel track of an abnormal traffic object, a movement intention, whether a traffic obstructing object exists with the target vehicle, and a distance with the target vehicle. The intermediate trajectory refers to a trajectory affected by an abnormal traffic object among candidate trajectories of the target vehicle.

Specifically, the computer device obtains current motion information of all abnormal traffic objects corresponding to the target vehicle and candidate trajectories of the target vehicle, and judges whether each abnormal traffic object has an influence on the candidate trajectories of the target vehicle. When the computer equipment judges that the abnormal traffic object has influence on one candidate track of the target vehicle, the candidate track is determined to be an intermediate track corresponding to the abnormal traffic object. The candidate track can be influenced by at least one abnormal traffic object, so that when track efficiency information is calculated, track efficiency information corresponding to one intermediate track is generated based on the current efficiency influence degree of each abnormal traffic object corresponding to the same intermediate track, and finally track efficiency information corresponding to each intermediate track can be obtained. For example, for one intermediate track, an average value of the current efficiency influence levels of the respective abnormal traffic objects may be calculated as track efficiency information, a maximum value of the respective current efficiency influence levels may be calculated as track efficiency information, and so on.

In one embodiment, the current movement information includes a travel track of an abnormal traffic object, a movement intention, whether or not there is a traffic blocking object with the target vehicle, a distance with the target vehicle, and the like. The abnormal traffic object is judged not to affect the candidate track, and the following conditions are satisfied that 1, the running track of the abnormal traffic object does not affect the running track of the target vehicle, for example, if the track of the target vehicle is a detour or a detour in front abnormal traffic object as shown in fig. 6 (a), 2, a traffic blocking object exists between the abnormal traffic object and the target vehicle, for example, the abnormal traffic object and the target vehicle are blocked by a red light as shown in fig. 6 (b), 3, the movement intention of the abnormal traffic object and the target vehicle is different, for example, the movement intention of the target vehicle is forward straight, the movement intention of the abnormal traffic object is right turn as shown in fig. 6 (c), and 4, the distance between the abnormal traffic object and the target vehicle is greater than a distance threshold, the distance threshold is positively correlated with the speed of the target vehicle, for example, the distance between the abnormal traffic object and the target vehicle is greater than the distance threshold as shown in fig. 6 (d).

In one embodiment, the computer device may normalize the initial track efficiency by using track efficiency information corresponding to the intermediate track as the initial track efficiency, to obtain the target track efficiency, and use the target track efficiency as the track efficiency information. The normalization process may be to determine a track efficiency maximum value from the respective initial track efficiencies, and take a ratio of the initial track efficiency and the track efficiency maximum value as the target track efficiency.

In the above embodiment, the computer device determines, based on the current motion information of all the abnormal traffic objects corresponding to the target vehicle, the track affected by the abnormal traffic object in the candidate track of the target vehicle as the intermediate track, and calculates the track efficiency information corresponding to the intermediate track based on the current efficiency influence of all the abnormal traffic objects affecting the track on the intermediate track, so that the accuracy of the track efficiency information corresponding to the intermediate track can be effectively improved. The intermediate track is a track which is influenced by abnormal traffic participants in candidate tracks of the target vehicle, and track efficiency information of the intermediate track is referred to when the running track of the target vehicle is planned, so that the accuracy of track planning can be effectively improved.

In a specific embodiment, the vehicle trajectory planning method may be applied in an autopilot scenario.

The vehicle track planning method comprises the following steps:

1. calculating a reference speed of a traffic participant (i.e., a target traffic object)

The reference sub-speeds for each traffic participant are calculated at regular intervals and all reference sub-speeds calculated over a period of time are recorded. If there is a reference traffic flow around the traffic participant, the average speed of the reference traffic flow is taken as the reference sub-speed. If no reference traffic exists around the traffic participant, the reference sub-speed is calculated in combination with the legal speed limit of the road and the speed limit imposed by the object with road semantic information. The final reference speed of the traffic participant is the result of a weighted average of the reference sub-speeds over time, such that the calculation may effectively reduce fluctuations due to environmental or upstream data inaccuracies.

2. Determining abnormal traffic participants (i.e. abnormal traffic objects) from among the individual traffic participants

The computer device obtains the current speed of the traffic participant and judges whether the target traffic object is an abnormal traffic object according to the following formula:

when result >0, then the traffic participant is determined to be an abnormal traffic participant.

3. Calculating the current efficiency influence degree corresponding to abnormal traffic participants

The computer equipment obtains the current speed and the reference speed of the abnormal traffic participants, and calculates the current efficiency influence degree corresponding to the abnormal traffic participants through the following formula:

4. calculating track efficiency information for candidate tracks

The computer device obtains a plurality of candidate trajectories of the autonomous vehicle, and judges whether the abnormal traffic participant has an influence on the candidate trajectories according to the driving trajectories, the movement intentions of the abnormal traffic participant, whether a traffic blocking object exists between the abnormal traffic participant and the autonomous vehicle, and the distance between the abnormal traffic participant and the autonomous vehicle. The candidate trajectory that would be affected by the abnormal traffic participant is taken as the intermediate trajectory. When one intermediate track corresponds to only one abnormal traffic participant, the computer equipment takes the current efficiency influence degree of the abnormal traffic participant as track efficiency information of the intermediate track, and when one intermediate track corresponds to at least two abnormal traffic participants, the computer equipment takes the maximum value of the current efficiency influence degree of each abnormal traffic participant as track efficiency information of the intermediate track. The computer device determines track efficiency information corresponding to the remaining candidate tracks based on the track efficiency information of the intermediate tracks, the track efficiency indicated by the track efficiency information corresponding to the remaining candidate tracks being higher than the track efficiency indicated by the track efficiency information corresponding to the intermediate tracks.

5. Determining a target track from candidate tracks

The computer device determines a target track of the autonomous vehicle based on track efficiency information for each candidate track. Further, the candidate track can be evaluated from multiple aspects of safety, comfort, efficiency and the like, and the target track of the automatic driving vehicle can be determined. The autonomous vehicle travels along the target trajectory.

The computer device can conduct traffic flow track planning at regular time and update the target track of the automatic driving vehicle at regular time.

In the above embodiment, the computer device acquires and uses the movement speed, movement intention, and movement environment information of each traffic participant in the history period when evaluating the track efficiency, which can increase the observation time of the efficiency evaluation, so that the evaluation is more accurate and stable. When the influence degree of the current efficiency of the abnormal traffic participant is calculated, the calculation thought of first-order low-pass filtering is consulted, the calculation values of the current moment and the historical moment are weighted, the influence caused by environmental change, upstream data value fluctuation and the like is reduced, the obtained current efficiency influence degree value is smoother, and the vehicle track evaluation is more stable and accurate.

It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a vehicle track planning device for realizing the vehicle track planning method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in one or more embodiments of the vehicle track planning device provided below may refer to the limitation of the vehicle track planning method hereinabove, and will not be described herein.

In one embodiment, as shown in FIG. 7, a vehicle track planning apparatus is provided, comprising a speed acquisition module 702, an abnormal traffic object determination module 704, a current efficiency impact calculation module 706, a track efficiency information determination module 708, and a target track determination module 710, wherein:

The speed acquisition module 702 is configured to acquire a current speed and a reference speed corresponding to at least one target traffic object, where the target traffic object is a traffic object moving around a target vehicle, and the reference speed is determined based on historical movement environment information of the target traffic object.

An abnormal traffic object determination module 704 for determining an abnormal traffic object from among the respective target traffic objects based on a speed difference between the reference speed and the current speed.

The current efficiency influence degree calculation module 706 is configured to generate a motion loss based on the current speed and the reference speed corresponding to the abnormal traffic object, and generate a current efficiency influence degree corresponding to the abnormal traffic object based on the motion loss.

The track efficiency information determining module 708 is configured to determine an intermediate track corresponding to the abnormal traffic object from the candidate tracks corresponding to the target vehicle, and generate track efficiency information corresponding to the intermediate track based on the current efficiency influence degree.

The target track determining module 710 is configured to determine a target track from the candidate tracks based on the track efficiency information.

According to the vehicle track planning device, the target traffic object is a traffic object moving around the target vehicle, the abnormal traffic object can be determined from the target traffic object based on the speed difference between the current speed and the reference speed corresponding to the target traffic object, the abnormal traffic object can have a large influence on the running of the target vehicle, and the accuracy of track planning can be effectively improved by referring to the related information of the abnormal traffic object when the running track of the target vehicle is planned. Further, motion loss can be generated based on the current speed and the reference speed corresponding to the abnormal traffic object, current efficiency influence degree corresponding to the abnormal traffic object can be generated based on the motion loss, the current efficiency influence degree can reflect influence degree of the abnormal traffic object on track efficiency of a running track of the target vehicle, track efficiency information of candidate tracks corresponding to the abnormal traffic object is generated based on the current efficiency influence degree, the target track is determined from the candidate tracks corresponding to the target vehicle based on the track efficiency information, and accuracy of track planning can be effectively improved.

In one embodiment, the speed acquisition module 702 is further configured to:

In one embodiment, the abnormal traffic object determination module 704 is further configured to:

In one embodiment, the current efficiency impact calculation module 706 is further configured to:

In one embodiment, the track efficiency information determination module 708 is further to:

And generating track efficiency information based on the current efficiency influence degree of each abnormal traffic object corresponding to the same intermediate track to obtain track efficiency information corresponding to each intermediate track.

The various modules in the vehicle trajectory planning device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 8. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer equipment is used for storing data such as reference speed, traffic speed limit information and the like corresponding to the target traffic object. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a vehicle trajectory planning method.

In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 9. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a vehicle trajectory planning method. The display unit of the computer equipment is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device, wherein the display screen can be a liquid crystal display screen or an electronic ink display screen, the input device of the computer equipment can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on a shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.

It will be appreciated by persons skilled in the art that the structures shown in fig. 8 and 9 are merely block diagrams of portions of structures associated with aspects of the application and are not intended to limit the computer apparatus to which aspects of the application may be applied, and that a particular computer apparatus may include more or less components than those shown, or may combine some of the components, or have a different arrangement of components.

In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.

In one embodiment, a computer-readable storage medium is provided, storing a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

In one embodiment, a computer program product or computer program is provided that includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps in the above-described method embodiments.

It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region.

Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magneto-resistive random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (PHASE CHANGE Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.

Claims

1. A vehicle trajectory planning method, the method comprising:

Generating motion loss based on the current speed and the reference speed corresponding to the abnormal traffic object, and generating current efficiency influence degree corresponding to the abnormal traffic object based on the motion loss, wherein the current efficiency influence degree refers to influence degree of the abnormal traffic object on track efficiency of a running track of the target vehicle;

determining an intermediate track corresponding to the abnormal traffic object from candidate tracks corresponding to the target vehicle based on the current motion information of the abnormal traffic object, and generating track efficiency information corresponding to the intermediate track based on the current efficiency influence degree;

2. The method of claim 1, wherein the obtaining the current speed and the reference speed corresponding to the at least one target traffic object comprises:

The method comprises the steps of obtaining a traffic object which is in a target range from a current target traffic object in a historical time period and is consistent with the movement direction of the current target traffic object as a reference traffic object corresponding to the current target traffic object, wherein the target range is increased along with the increase of the historical speed of the current target traffic object in the historical time period, and no traffic blocking object exists between the current target traffic object and the reference traffic object;

Counting the movement speed of the reference traffic object in the historical time period to obtain a reference sub-speed corresponding to the current target traffic object in the historical time period;

And obtaining the reference speed corresponding to the current target traffic object based on the reference sub-speed corresponding to the current target traffic object in the historical time period.

3. The method according to claim 2, wherein the method further comprises:

4. The method of claim 2, wherein the obtaining the reference speed corresponding to the current target traffic object based on the reference sub-speed corresponding to the current target traffic object in the historical time period comprises:

Acquiring reference sub-speeds respectively corresponding to the current target traffic object in at least two historical time periods;

Generating a speed weight of a reference sub-speed corresponding to the historical time period based on the time difference between the historical time period and the current time period, wherein the speed weight is reduced along with the increase of the time difference;

And fusing all the reference sub-speeds based on the speed weights of all the reference sub-speeds to obtain the reference speed corresponding to the current target traffic object.

5. The method of claim 1, wherein the determining abnormal traffic objects from among the respective target traffic objects based on a speed difference between the reference speed and the current speed comprises;

obtaining the speed difference proportion corresponding to each target traffic object based on the ratio between the speed difference corresponding to the same target traffic object and the reference speed;

And taking the target traffic object with the speed difference proportion larger than the preset proportion as the abnormal traffic object.

6. The method of claim 1, wherein the generating a motion loss based on the current speed and the reference speed corresponding to the abnormal traffic object comprises:

calculating a first displacement corresponding to the abnormal traffic object based on the current speed and a preset time period corresponding to the abnormal traffic object, and calculating a second displacement corresponding to the abnormal traffic object based on the reference speed and the preset time period corresponding to the abnormal traffic object;

The motion loss is generated based on the first displacement and the second displacement.

7. The method of claim 1, wherein the generating the current efficiency impact level for the abnormal traffic object based on the motion loss comprises:

acquiring the statistics times of the historical efficiency influence degree corresponding to the abnormal traffic object;

generating a loss weight based on the statistics, the loss weight increasing with increasing statistics and approaching a target value;

the current efficiency impact is generated based on the loss weight and the motion loss.

8. The method of claim 1, wherein the generating track efficiency information corresponding to the intermediate track based on the current efficiency impact comprises:

track efficiency information is generated based on the current efficiency influence degree of each abnormal traffic object corresponding to the same intermediate track, and track efficiency information corresponding to each intermediate track is obtained.

9. A vehicle trajectory planning device, the device comprising:

The system comprises a current efficiency influence degree calculation module, a target vehicle, a motion loss generation module and a speed control module, wherein the current efficiency influence degree calculation module is used for generating motion loss based on a current speed and a reference speed corresponding to the abnormal traffic object and generating a current efficiency influence degree corresponding to the abnormal traffic object based on the motion loss;

The track efficiency information determining module is used for determining an intermediate track corresponding to the abnormal traffic object from candidate tracks corresponding to the target vehicle based on the current motion information of the abnormal traffic object, and generating track efficiency information corresponding to the intermediate track based on the current efficiency influence degree;

10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 8 when the computer program is executed.

11. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 8.

12. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the method of any one of claims 1 to 8.