CN114506343A - Trajectory planning method, device, equipment, storage medium and automatic driving vehicle - Google Patents

Trajectory planning method, device, equipment, storage medium and automatic driving vehicle Download PDF

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Publication number
CN114506343A
CN114506343A CN202210205416.1A CN202210205416A CN114506343A CN 114506343 A CN114506343 A CN 114506343A CN 202210205416 A CN202210205416 A CN 202210205416A CN 114506343 A CN114506343 A CN 114506343A
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Prior art keywords
track
information
sampling
determining
point
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夏中谱
潘屹峰
朱振广
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Apollo Intelligent Technology Beijing Co Ltd
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Apollo Intelligent Technology Beijing Co Ltd
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Priority to CN202210205416.1A priority Critical patent/CN114506343A/en
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/0098—Details of control systems ensuring comfort, safety or stability not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0015—Planning or execution of driving tasks specially adapted for safety
    • B60W60/0017—Planning or execution of driving tasks specially adapted for safety of other traffic participants
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/50—Barriers

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Human Computer Interaction (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Abstract

The disclosure provides a track planning method, a device, equipment, a storage medium and an automatic driving vehicle, and relates to the technical field of artificial intelligence, in particular to the fields of unmanned driving, automatic driving, intelligent transportation and the like. The specific implementation scheme is as follows: determining a first planned track point in the planned path according to the current position and the planned path of the vehicle, wherein the first planned track point is the next planned track point of the current position; determining a plurality of track points to be selected corresponding to the first planning track point according to the barrier information of the current position and the first planning track point; acquiring sampling information of the plurality of to-be-selected track points; and determining a target track point in the plurality of track points to be selected according to the sampling information of the track points to be selected and the obstacle information, and controlling the vehicle to run towards the target track point. The rapid strain capacity of the vehicle to the environment in the trajectory planning is improved.

Description

Trajectory planning method, device, equipment, storage medium and automatic driving vehicle
Technical Field
The disclosure relates to the technical field of artificial intelligence, in particular to a trajectory planning method, device, equipment, storage medium and an automatic driving vehicle, which can be used in the fields of unmanned driving, automatic driving, intelligent transportation and the like.
Background
When planning a driving path of an autonomous vehicle, it is necessary to sample track points in a driving space and then plan the driving path for the autonomous vehicle based on the sampled data.
In the related art, for a feasible region to be planned, map data in the feasible region is usually acquired at a starting point, then a planned path in the feasible region is obtained according to the map data and sampling information of track points in the feasible region, and the automatic driving vehicle is guided to run according to the planned path.
Since the road conditions in the automatic driving scene are changed frequently, the scheme is difficult to adapt to the changed environmental scene, and the rapid strain capability is poor.
Disclosure of Invention
The disclosure provides a trajectory planning method, a trajectory planning device, a trajectory planning apparatus, a storage medium and an autonomous vehicle.
According to a first aspect of the present disclosure, there is provided a trajectory planning method, including:
determining a first planned track point in the planned path according to the current position and the planned path of the vehicle, wherein the first planned track point is the next planned track point of the current position;
determining a plurality of track points to be selected corresponding to the first planning track point according to the barrier information of the current position and the first planning track point;
acquiring sampling information of the plurality of to-be-selected track points;
and determining a target track point in the plurality of track points to be selected according to the sampling information of the plurality of track points to be selected and the obstacle information, and controlling the vehicle to run towards the target track point.
According to a second aspect of the present disclosure, there is provided a trajectory planning apparatus comprising:
the determining unit is used for determining a first planned track point in the planned path according to the current position and the planned path of the vehicle, wherein the first planned track point is the next planned track point of the current position;
the processing unit is used for determining a plurality of track points to be selected corresponding to the first planning track point according to the barrier information of the current position and the first planning track point;
the acquisition unit is used for acquiring the sampling information of the plurality of track points to be selected;
and the planning unit is used for determining a target track point in the plurality of track points to be selected according to the sampling information of the plurality of track points to be selected and the obstacle information, and controlling the vehicle to run towards the target track point.
According to a third aspect of the present disclosure, there is provided an electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect.
According to a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the first aspect
According to a fifth aspect of the present disclosure, there is provided a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of an electronic device can read the computer program, execution of the computer program by the at least one processor causing the electronic device to perform the method of the first aspect.
According to a sixth aspect of the present disclosure, there is provided an autonomous vehicle comprising an electronic device as described in the third aspect.
According to the track planning method, the track planning device, the track planning equipment, the storage medium and the automatic driving vehicle, firstly, a first planned track point is determined in a planned path according to the current position and the planned path of the vehicle, and the first planned track point is the next planned track point of the current position; then determining a plurality of track points to be selected corresponding to the first planning track point according to the barrier information of the current position; after a plurality of to-be-selected track points are determined, sampling is carried out on the plurality of to-be-selected track points to obtain sampling information of the plurality of to-be-selected track points, so that a target track point can be determined in the plurality of to-be-selected track points based on the sampling information of the plurality of to-be-selected track points and the obstacle information of the current position, and the vehicle is controlled to run towards the target track point. According to the technical scheme, when the track points are planned, a plurality of to-be-selected track points which are sampled can be determined according to the barrier information of the current position to be sampled, and the track planning is carried out based on the sampling information and the barrier information of the current position.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a schematic view of an application scenario provided by an embodiment of the present disclosure;
fig. 2 is a schematic flow chart of a trajectory planning method provided in the embodiment of the present disclosure;
fig. 3 is a schematic diagram of obtaining a planned path according to an embodiment of the present disclosure;
fig. 4 is a schematic flow chart of determining a track point to be selected according to the embodiment of the present disclosure;
FIG. 5 is a schematic diagram of determining a sampling region according to an embodiment of the disclosure;
FIG. 6 is a schematic diagram of a trajectory planning provided by an embodiment of the present disclosure;
FIG. 7 is a schematic diagram of a trajectory planning provided by an embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of a trajectory planning device according to an embodiment of the present disclosure;
fig. 9 is a block diagram of an electronic device for implementing a trajectory planning method of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In embodiments of the present disclosure, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the access relationship of the associated object, meaning that there may be three relationships, e.g., A and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. In the description of the text of the present disclosure, the character "/" generally indicates that the former and latter associated objects are in an "or" relationship. In addition, in the embodiments of the present disclosure, "first", "second", "third", "fourth", "fifth", and "sixth" are only used to distinguish the contents of different objects, and have no other special meaning.
The trajectory planning means performing trajectory planning in a feasible region of the autonomous vehicle based on relevant sampling information of trajectory points on roads in the feasible region, obstacle information, and the like, and controlling the autonomous vehicle to travel according to the planned trajectory.
The process of trajectory planning may be understood, for example, in connection with fig. 1. Fig. 1 is a schematic view of an application scenario provided by an embodiment of the present disclosure, as shown in fig. 1, where a vehicle 10 is at a starting point and a trajectory of the vehicle 10 in a feasible area needs to be planned.
The feasible region is a travel space of the vehicle 10, and may be represented by S, where S is (X, Y, H, V), where X represents a range of abscissa in the feasible region S, Y represents a range of ordinate in the feasible region S, X and Y collectively represent a range of coordinates of the feasible region S, H represents a vehicle heading range in the feasible region S, and V represents a speed range in the feasible region S. That is, the feasible region includes not only the coordinate range in which the vehicle 10 is allowed to travel, but also the orientation range and the speed range in which the vehicle 10 travels. At different locations within the feasible region S, the corresponding coordinate ranges, heading ranges, and speed ranges may be different, and the relevant range requirements need to be met when the vehicle 10 is traveling in a certain region on the feasible region S. For example, if a certain area within the selectable area S requires a speed limit of 60km/h, the vehicle 10 will not travel more than 60km/h if the vehicle 10 travels into the area.
In the process of trajectory planning, trajectory points in a feasible region need to be sampled, and the sampling process is the basis of trajectory planning. Taking sampling in the feasible region as an example, the feasible region can be divided according to a certain method, so that a plurality of track points are obtained in the feasible region. After obtaining a plurality of track points, can sample a plurality of track points, obtain the sampling information of track point, the sampling information can include the coordinate range, orientation range, speed range etc. that the track point corresponds for example.
In the related art, a scheme for planning a track based on track sampling generally includes initially sampling track points in an entire feasible region to obtain sampling information of the track points. Then, road-related information in the feasible region, including, for example, information on intersections, the number of lanes, and the like in the feasible region, and obstacle information, including, for example, information on the number, position, size, type, and the like of obstacles, are acquired based on the high-precision map.
After the sampling information of the track points, the road related information and the obstacle information are obtained, the running track of the vehicle in the feasible region can be planned according to the road related information, the obstacle information and the sampling information of the track points, and the vehicle is controlled to run according to the planned running track.
The above scheme is a one-time planning process, namely the track sampling process can be completed only once, the track planning time consumption is low, but the obstacle information on the road changes at any time, the scheme easily causes the vehicle to react slowly, and the rapid strain can not be realized in the changed scene. Usually, the rapid strain of the vehicle to the changing scene can be realized only by performing the trajectory planning in real time, but when performing the trajectory planning in real time, the trajectory point sampling is performed on the whole feasible region, so as to determine the driving trajectory point of the next frame according to the obstacle information and the road related information acquired in real time. The fast strain capability of the scheme is good, but the spatial dimension of sampling is high, and the solution is time-consuming.
In view of the above technical problems, the present disclosure proposes the following technical concepts: and aiming at the feasible region to be planned, firstly determining a planned path, then determining a track point to be selected according to the obstacle information of the current position of the vehicle and the planned path, sampling, finally determining a target track point of the current position, and controlling the vehicle to drive to the target track point.
On the basis of the above introduction, the following describes the trajectory planning method provided by the present disclosure with reference to specific embodiments. The execution main body of each embodiment in the present disclosure may be, for example, a device with a data processing function, such as a server, a processor, a microprocessor, a chip, and the like, and the specific execution main body of each embodiment in the present disclosure is not limited, and may be selected and set according to actual needs, and any device with a data processing function may be used as the execution main body of each embodiment in the present disclosure.
First, description is made with reference to fig. 2, where fig. 2 is a schematic flow chart of a trajectory planning method provided in the embodiment of the present disclosure, as shown in fig. 2, the method may include:
and S21, determining a first planned track point in the planned path according to the current position and the planned path of the vehicle, wherein the first planned track point is the next planned track point of the current position.
The executing body of the embodiment of the present disclosure may be, for example, a server, a power amplifier, or other devices with certain data processing capability on a vehicle, and in the following embodiments, the server on the vehicle will be described as an example. The server can acquire the current position of the vehicle and then plan the driving track of the vehicle.
The planned path in the embodiment of the present disclosure is a path determined before planning a vehicle driving trajectory. When the vehicle is located at the starting point, a section of feasible region of the vehicle from the starting point can be divided to obtain a plurality of track points, and the track points represent a part of the feasible region. And then, carrying out track sampling on a plurality of track points of the feasible region, and determining a planned path according to track sampling information of the plurality of track points and the state of the vehicle at the starting point.
The planned route is a route obtained according to data such as current obstacle information, map data of a feasible region, and track sampling information of a track point when the vehicle is located at a starting point, and is a theoretically optimal driving route. The planning path comprises a plurality of planning track points, and the planning track points correspond to the primary track point planning of the vehicle.
The first planned track point is one of a plurality of planned track points of the planned path, and the first planned track point is the next planned track point of the current position, namely if the vehicle runs according to the planned path at the current position, the server can control the vehicle to run to the first planned track point.
And S22, determining a plurality of track points to be selected corresponding to the first planning track point according to the obstacle information of the current position.
After the first planned track point is determined, the obstacle information of the current position can be obtained, and then a plurality of to-be-selected track points corresponding to the first planned track point are determined according to the obstacle information of the current position.
The trajectory point to be selected is a next possible trajectory point of the current position, and the obstacle information of the current position may include, for example, a position where the vehicle acquires an obstacle at the current position, a type of the obstacle, a size of the obstacle, and the like. Because the obstacle information is changed in real time, in the embodiment of the disclosure, the obstacle information of the current position is obtained in real time when the trajectory planning is performed, so that a plurality of trajectory points to be selected are determined according to the obstacle information of the current position.
And S23, acquiring the sampling information of the plurality of to-be-selected track points.
After a plurality of to-be-selected track points are determined, track sampling needs to be performed on the plurality of to-be-selected track points, and sampling information of the plurality of to-be-selected track points is obtained. The sampling information of the track point to be selected may include, for example, a coordinate range of the track point to be selected, a vehicle heading range of the track point to be selected, an allowable speed range of the track point to be selected, and the like.
And S24, determining a target track point in the plurality of track points to be selected according to the sampling information and the obstacle information of the plurality of track points to be selected, and controlling the vehicle to drive to the target track point.
After the sampling information of a plurality of to-be-selected track points and the obstacle information of the current position are obtained, the target track point can be determined according to the sampling information of the plurality of to-be-selected track points and the obstacle information, and the target track point is one of the plurality of to-be-selected track points.
The target track point is suitable for driving the vehicle to go to and needs to be comprehensively determined according to sampling information and barrier information of the track point to be selected. For example, which obstacles are included in a path from the current position to the trajectory point to be selected, the size, type, motion condition and the like of the obstacles can be determined according to the obstacle information, the trajectory point to be selected which meets the requirement of the sampling information and can avoid the obstacle is selected as the target trajectory point by combining the information such as the orientation range, the allowable speed range and the like in the sampling information, and the vehicle is controlled to travel to the target trajectory point.
According to the track planning method provided by the embodiment of the disclosure, first, according to the current position and the planned path of a vehicle, a first planned track point is determined in the planned path, and the first planned track point is the next planned track point of the current position; then determining a plurality of track points to be selected corresponding to the first planning track point according to the barrier information of the current position; after a plurality of to-be-selected track points are determined, sampling is carried out on the plurality of to-be-selected track points to obtain sampling information of the plurality of to-be-selected track points, so that a target track point can be determined in the plurality of to-be-selected track points based on the sampling information of the plurality of to-be-selected track points and the obstacle information of the current position, and the vehicle is controlled to run towards the target track point. According to the technical scheme, when the track points are planned, a plurality of to-be-selected track points which are sampled can be determined according to the barrier information of the current position to be sampled, and the track planning is carried out based on the sampling information and the barrier information of the current position.
Based on the above description, the trajectory planning method provided by the present disclosure is further described in detail below with reference to the accompanying drawings.
In one-segment trajectory planning, real-time planning needs to be performed based on the current position of the vehicle and the planned path, so that determining the planned path is a precondition for performing trajectory planning. The process of determining the planned path is first described below with reference to fig. 3.
Fig. 3 is a schematic diagram of obtaining a planned path according to an embodiment of the present disclosure, please refer to fig. 3, where a vehicle is initially located at a starting point O, and fig. 3 illustrates a feasible region from the starting point O, where a driving track of the vehicle in the feasible region from the starting point O needs to be planned.
Before the trajectory planning, the feasible region may be divided to obtain corresponding sub-regions, and the dividing manner may include, for example, a mesh division method, a grid division method, and the like. Taking a grid division method as an example, a plurality of sub-regions are obtained after the feasible region is subjected to grid division, and then the central point of the sub-region is taken as the track point of the sub-region, so that a plurality of track points in the feasible region are obtained.
In the embodiment of the disclosure, the feasible region can be divided in the horizontal direction at equal distance, so that a plurality of groups of track points are obtained, and the horizontal coordinates of each group of track points are relatively close. For example, in fig. 3, track point a1, track point a2, a.. and track point a6 are a set of track points, track point B1, track point B2, a.. and track point B6 are a set of track points, and track point C1, track point C2, a.. and track point C6 are a set of track points.
When the vehicle is at the starting point O, a plurality of track points in the feasible region may be sampled to obtain sampling information of the plurality of track points, where the sampling information may include, for example, information such as a position range, an orientation range, and a speed range of the track points.
Then, the server may obtain map data of the feasible region and initial obstacle information, where the map data may include data of lanes, traffic lights, intersections, and the like of the feasible region, and the map data may be obtained according to a high-precision electronic map. The initial obstacle information is obstacle information obtained by a sensor or the like on the vehicle when the vehicle is at the starting point O, and may include, for example, a position, a size, a type (for example, a static obstacle or a dynamic obstacle), and the like of an obstacle.
After the map data and the initial obstacle information of the feasible region are obtained, the planned path can be obtained according to the sampling information of the plurality of track points, the map data and the initial obstacle information. The method for obtaining the planned path may include, for example, a dynamic planning method, an a-star method, and the like, which are not described herein again.
In the disclosed embodiment, the planned path may be represented by τ ═ ti，xi，yi，hi，vi)，i＝1，2，3，...，n]Is represented by, wherein, tjFor a certain time in the future, xiIs tiAbscissa, y, of the planned trajectory point in the time-of-day planned pathiIs tiOrdinate, x, of a time-of-day planning track pointiAnd yiCollectively reflect tiPlanning the position of the track point at any moment, hiFor planning the planning orientation of the track points, viAnd n is the number of the planned track points in the planned path for planning the planning speed of the track points. In fig. 3, a possible planned trajectory is illustrated, i.e. a planned trajectory from the starting point O to the trajectory point a4, the trajectory point B4, the trajectory point C5 in sequence.
The planned track is only the optimal track determined according to the relevant information acquired from the starting point, and because the obstacle information in the feasible region is dynamically changed, the obstacle information of the current position needs to be acquired in real time in the track planning process, and the track planning is realized by combining the planned path. Referring to fig. 3, when the vehicle is at the starting point O, since the planned path is determined according to the initial obstacle information, the map data, and the sampling information of the track points, the initial obstacle information is the obstacle information acquired by the vehicle in real time at the starting point O, the vehicle can travel according to the planned path at this time. For example, in fig. 3, the vehicle may travel to track point a4 according to the planned path. In subsequent trajectory planning, planning may be performed based on the current position of the vehicle.
In the embodiment of the disclosure, after the target track point is determined according to the current position of the vehicle and the vehicle is controlled to run to the target track point, the track planning of the current frame is completed, the vehicle enters the next frame of track planning, the target track point at the moment becomes the current position of a new vehicle, and then the planning process is repeated. The implementation of the per-frame trajectory planning process of the vehicle is similar, and in the following embodiment, a one-frame trajectory planning process of the vehicle will be described.
First, a process of determining a track point to be selected is described with reference to fig. 4, where fig. 4 is a schematic flow chart of determining a track point to be selected according to an embodiment of the present disclosure, and as shown in fig. 4, the process includes:
and S41, acquiring the track information of the vehicle from the first position to the current position, wherein the first position is the position which is previous to the current position.
The first position is the previous position of the current position, the vehicle carries out previous frame track planning at the first position, and the current position is determined to be a target track point when the vehicle is located at the first position, so that the vehicle is controlled to drive towards the current position. After the vehicle is driven to the current position, the current frame trajectory planning is needed.
Since the current position is determined to be the target track point corresponding to the first position in the last frame of track planning, the server controls the vehicle to travel from the first position to the current position, so that a track from the first position to the current position is formed. When planning the track, the position of the target track point of the vehicle can be planned, and how to control the vehicle to travel to the target track point can be planned, for example, the direction and the speed of the vehicle to the target track point are set, and the information such as the direction and the speed is track information.
In the embodiment of the present disclosure, when planning the current frame trajectory, trajectory information of the vehicle from the first position to the current position is obtained, and the trajectory information from the first position to the current position may include, for example, information such as a heading, coordinates, and a speed of the vehicle in a process from the first position to the current position, and may further include information of an obstacle when the vehicle is at the first position, for example.
And S42, determining a plurality of track points to be selected according to the track information, the obstacle information and the first planning track point.
After obtaining the track information of the vehicle from the first position to the current position, a plurality of track points to be selected need to be determined according to the track information, the obstacle information and the first planned track point. Optionally, the plurality of to-be-selected track points are track points within a certain range near the first planned track point. By combining the first planning track point with the obstacle information of the current position and the track information from the first position to the current position, a smaller range can be determined in the whole feasible region, and the track point to be selected is determined in the smaller range for sampling, so that the calculation amount of sampling can be reduced, and the time consumption of track planning is reduced.
Specifically, firstly, according to the track information and the obstacle information of the vehicle from the first position to the current position, a sampling parameter corresponding to the first planning track point is obtained, wherein the sampling parameter is used for indicating a sampling range corresponding to the first planning track point. After the sampling parameters are determined, a plurality of track points to be selected can be determined according to the sampling parameters and the positions of the first planning track points.
In the embodiment of the present disclosure, for the trajectory planning of the current position, a change of a traffic environment around the vehicle from the first position to the current position may be determined based on trajectory information of the vehicle from the first position to the current position and obstacle information of the current position, where the change of the traffic environment may include changes in the number, size, position, direction, and the like of obstacles, for example. When the change of the traffic environment is large, a large sampling range can be set according to the sampling parameters, and subsequent track sampling is carried out so as to improve the success rate of track planning; when the change of the traffic environment is small, a small sampling range can be set according to the sampling parameters, so that the sampling range is reduced on the premise of ensuring the success of the trajectory planning, and the calculation amount of the trajectory planning is reduced.
In one possible implementation, the sampling parameters may include a sampling distance and a number of samples. After the sampling parameters are obtained according to the track information and the obstacle information, the sampling area of the first planned track point can be determined according to the sampling distance and the position of the first planned track point. Fig. 5 is a schematic diagram of determining a sampling region according to the embodiment of the present disclosure, and as shown in fig. 5, taking a first planned trace point as a trace point B4 as an example, and setting a sampling distance as r, a sampling region 50 may be determined according to the sampling distance r and the position of the trace point B4, and distances between any point in the sampling region 50 and the trace point B4 are both less than or equal to the sampling distance r.
After the sampling area is determined, a plurality of trace points to be selected can be determined in the sampling area according to the sampling number. Referring to fig. 5, the trace point B4 is the first planned trace point, and the sampling information of the trace point B4 is (t)1，x1，y1，h1，v1) The to-be-selected trace point can be determined by fixing the sampling information of the trace point B4 in a certain dimension and expanding the sampling information of other dimensions.
To fix xiFor example, according to the sampling information of the trace point B4, the corresponding sampling space is determined to be τ ═ t1+Δt，x1，y1+Δt，h1+Δt，v1+Δt)]. Under the condition that the sampling parameter is not changed, according to the planning path tau ═ ti，xi，yi，hi，vi)，i＝1，2，3，...，n]Then, the corresponding sampling space τ + Δ t ═ t [ (t)i+Δt，xi，yi+Δt，hi+Δt，vi+Δt)，i＝1，2，3，...，n]。
Compared with the method for sampling the trajectory in the whole feasible region S ═ X, Y, H, V, the scheme of the embodiment of the present disclosure determines the corresponding sampling space by planning the path and samples in the sampling space, the sampling space has a smaller scale than the feasible region, the sampling range is reduced, and thus the time consumption and the calculation amount of trajectory planning are reduced.
After a plurality of to-be-selected track points are determined, the plurality of to-be-selected track points can be sampled to obtain sampling information of the to-be-selected track points, and therefore target track points are determined in the plurality of to-be-selected track points according to the sampling information and the obstacle information of the to-be-selected track points.
Specifically, after the trajectory point to be selected is determined, the driving information of the vehicle at the current position may be obtained, where the driving information includes at least one of a coordinate of the vehicle at the current position, an orientation of the vehicle, and a speed of the vehicle. And then determining the track point to be selected which meets the driving requirement of the vehicle from the plurality of track points to be selected according to the driving information of the vehicle and the sampling information of the track point to be selected.
The server can optionally select one of the to-be-selected track points meeting the driving requirements of the vehicle as a target track point, also can select one to-be-selected track point which is most suitable for the current vehicle as the target track point from the to-be-selected track points meeting the driving requirements of the vehicle, and controls the vehicle to drive to the target track point from the current position according to the track plan, so that the real-time performance of the track plan is realized, and the strain capacity of the vehicle to the changing environment is improved.
Under some conditions, the track points to be selected which do not meet the driving requirements of the vehicle are not found in the plurality of track points to be selected, for example, under the condition that traffic environments such as barrier information and the like are suddenly changed, no suitable track points to be selected exist in the track points to be selected and serve as target track points, and at the moment, the sampling parameters can be updated, so that the track planning is carried out again. This process is described below in conjunction with fig. 6.
Fig. 6 is a schematic diagram of a trajectory planning provided by the embodiment of the present disclosure, and as shown in fig. 6, a plurality of trajectory points to be selected, namely trajectory point B3 and trajectory point B5, are determined according to the obstacle information of the current position and the first planned trajectory point (namely trajectory point B4).
After the plurality of to-be-selected track points are determined, whether the to-be-selected track points meeting the driving requirements of the vehicle exist in the plurality of to-be-selected track points needs to be determined. In the example of fig. 6, neither track point B3 nor track point B5 is suitable as the next target track point when the vehicle is at the current position, i.e., the target track point cannot be determined from the plurality of track points to be selected. At this time, the sampling parameters may be updated, and then the target track point may be determined according to the updated sampling parameters.
Specifically, after the sampling parameters are updated, at least one new trajectory point to be selected can be determined according to the updated sampling parameters. Because the sampling parameters can comprise sampling distance and sampling quantity, when the sampling parameters are updated, the sampling distance can be updated, the sampling quantity can also be updated, and both the sampling distance and the sampling quantity can also be updated.
When the sampling distance is updated, the sampling distance can be increased, so that the sampling range is expanded. When the sampling number is updated, the sampling number can be increased, so that more track points are sampled in the sampling area.
For example, in fig. 6, the sampling region 60 is re-determined according to the updated sampling parameters, as illustrated by the dashed box. After the new sampling region 60 is determined, the new sampling region 60 is sampled, and at least one new trajectory point to be selected, i.e., trajectory point B2 and trajectory point B6 in fig. 6, is determined. And then, acquiring new sampling information of the track point B2 and the track point B6, and determining a target track point in the new track point to be selected according to the new sampling information and the obstacle information. For example, in fig. 6, the track point B2 is determined as the target track point, and then the vehicle can be controlled to drive from the current position to the track point B2.
When no track point meeting the driving requirement exists in the track points to be selected, the sampling parameters can be adjusted, so that a new track point to be selected is determined according to the updated sampling parameters, and a target track point is re-determined according to the new track point to be selected, the continuity of front-back frame track planning of the vehicle is improved, the strain capacity under the condition of sudden jitter caused by environmental noise is improved, the anti-noise performance of the scheme is better, the sampling parameters can be adjusted in real time according to the change of the environment, and the adaptability is also better.
Fig. 7 is a schematic diagram of a trajectory planning provided by the embodiment of the present disclosure, as shown in fig. 7, where a starting point O to a trajectory point a4, a trajectory point B4, and a trajectory point C5 are initial planning paths, and in an actual trajectory planning, sampling trajectory points during trajectory planning are determined according to the planning paths, for example, trajectory point A3, trajectory point a5, trajectory point B3, trajectory point B5, trajectory point C4, trajectory point C6, and the like in fig. 7. By planning the path and the barrier information, the sampling area is greatly reduced, so that the real-time trajectory planning can be realized without sampling the whole feasible area, and the calculation amount of the trajectory planning is reduced on the premise of ensuring the rapid strain capability of the trajectory planning process to the changing environment.
In summary, the trajectory planning method provided by the present disclosure initially determines a planned path, then, based on the planned path, in a subsequent trajectory planning process, obtains the obstacle information of the current position in real time, and determines a plurality of trajectory points to be selected in combination with a corresponding first planned trajectory point in the planned path. The target track points at the current position are determined according to the sampling information after the plurality of track points to be selected are sampled, so that the vehicle is controlled to run towards the target track points, the real-time planning of the track is realized, and the strain and the processing capacity of the changing environment are improved.
Fig. 8 is a schematic structural diagram of a trajectory planning apparatus provided in an embodiment of the present disclosure, and as shown in fig. 8, the trajectory planning apparatus 80 may include:
the determining unit 81 is configured to determine a first planned trajectory point in the planned path according to the current position of the vehicle and the planned path, where the first planned trajectory point is a next planned trajectory point of the current position;
the processing unit 82 is configured to determine, according to the obstacle information of the current position and the first planned trajectory point, a plurality of trajectory points to be selected corresponding to the first planned trajectory point;
the obtaining unit 83 is configured to obtain sampling information of the multiple track points to be selected;
and the planning unit 84 is used for determining a target track point in the plurality of track points to be selected according to the sampling information of the track points to be selected and the obstacle information, and controlling the vehicle to run towards the target track point.
In a possible embodiment, the processing unit 82 comprises:
the first acquisition module is used for acquiring track information of the vehicle from the first position to the current position, wherein the first position is a position which is previous to the current position;
and the first determining module is used for determining the plurality of track points to be selected according to the track information, the obstacle information and the first planned track point.
In one possible implementation, the first determining module includes:
the first obtaining submodule is used for obtaining sampling parameters corresponding to the first planning track point according to the track information and the obstacle information;
and the first determining submodule is used for determining the plurality of track points to be selected according to the sampling parameters and the position of the first planning track point.
In one possible embodiment, the sampling parameters include a sampling distance and a sampling number; the first determination submodule is specifically configured to:
determining a sampling area of the first planned track point according to the sampling distance and the position of the first planned track point;
and determining the plurality of track points to be selected in the sampling area according to the sampling number.
In a possible embodiment, the planning unit 84 comprises:
the second acquisition module is used for acquiring the running information of the vehicle at the current position, and the running information comprises at least one of the coordinate, the orientation and the speed of the vehicle at the current position;
the second determining module is used for determining the track point to be selected which meets the driving requirement of the vehicle in the plurality of track points to be selected according to the driving information and the sampling information of the track point to be selected;
and the third determining module is used for determining the target track point in the to-be-selected track points meeting the driving requirement.
In a possible embodiment, if none of the trajectory points to be selected meet the driving requirement, the planning unit 84 is further configured to:
updating the sampling parameters, and determining at least one new track point to be selected according to the updated sampling parameters;
acquiring new sampling information of the at least one new track point to be selected;
and determining the target track point in the at least one new track point to be selected according to the new sampling information and the obstacle information.
In a possible implementation, the method further includes an obtaining unit, where the obtaining unit is configured to:
acquiring a plurality of track points in a feasible region, and map data and initial obstacle information of the feasible region;
acquiring sampling information of a plurality of track points in the feasible region;
and acquiring the planned path according to the sampling information of the plurality of track points, the map data and the initial obstacle information.
The trajectory planning device provided in the embodiment of the present application is used for executing the method embodiments, and the implementation principle and the technical effect are similar, which are not described herein again.
The invention provides a track planning method, a device, equipment, a storage medium and an automatic driving vehicle, which are applied to the fields of unmanned driving, automatic driving, intelligent transportation and the like in the artificial intelligence technology so as to achieve the purpose of reducing the calculated amount of track planning in the real-time track planning process.
It should be noted that the head model in this embodiment is not a head model for a specific user, and cannot reflect personal information of a specific user. It should be noted that the two-dimensional face image in the present embodiment is from a public data set.
In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
According to an embodiment of the present disclosure, the present disclosure also provides a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, the at least one processor executing the computer program causing the electronic device to perform the solution provided by any of the embodiments described above.
According to an embodiment of the present disclosure, the present disclosure further provides an autonomous vehicle, where the autonomous vehicle includes an electronic device, and when the autonomous vehicle is in operation, at least one processor of the electronic device in the autonomous vehicle may read a computer program from a readable storage medium, and the at least one processor executes the computer program to enable the electronic device to execute the scheme provided in any of the above embodiments, so as to implement trajectory planning of the autonomous vehicle, and enable the autonomous vehicle to operate according to the planned trajectory.
FIG. 9 illustrates a schematic block diagram of an example electronic device 900 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 9, the apparatus 900 includes a computing unit 901, which can perform various appropriate actions and processes in accordance with a computer program stored in a Read Only Memory (ROM)902 or a computer program loaded from a storage unit 908 into a Random Access Memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The calculation unit 901, ROM 902, and RAM 903 are connected to each other via a bus 904. An input/output (I/O) interface 905 is also connected to bus 904.
A number of components in the device 900 are connected to the I/O interface 905, including: an input unit 906 such as a keyboard, a mouse, and the like; an output unit 907 such as various types of displays, speakers, and the like; a storage unit 908 such as a magnetic disk, optical disk, or the like; and a communication unit 909 such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 909 allows the device 900 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 901 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 901 performs the respective methods and processes described above, such as a trajectory planning method. For example, in some embodiments, the trajectory planning method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 908. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 900 via ROM 902 and/or communications unit 909. When loaded into RAM 903 and executed by computing unit 901, may perform one or more of the steps of the trajectory planning method described above. Alternatively, in other embodiments, the computing unit 901 may be configured to perform the trajectory planning method by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims (18)

1. A trajectory planning method, comprising:
determining a first planned track point in the planned path according to the current position and the planned path of the vehicle, wherein the first planned track point is the next planned track point of the current position;
determining a plurality of track points to be selected corresponding to the first planning track point according to the barrier information of the current position and the first planning track point;
acquiring sampling information of the plurality of to-be-selected track points;
and determining a target track point in the plurality of track points to be selected according to the sampling information of the plurality of track points to be selected and the obstacle information, and controlling the vehicle to run towards the target track point.
2. The method according to claim 1, wherein the determining a plurality of trajectory points to be selected corresponding to the first planned trajectory point according to the obstacle information of the current position and the first planned trajectory point includes:
acquiring track information of the vehicle from a first position to the current position, wherein the first position is a position which is previous to the current position;
and determining the plurality of track points to be selected according to the track information, the obstacle information and the first planning track point.
3. The method of claim 2, wherein determining the plurality of trajectory points to be selected from the trajectory information, the obstacle information, and the first planned trajectory point comprises:
acquiring sampling parameters corresponding to the first planning track point according to the track information and the obstacle information;
and determining the plurality of track points to be selected according to the sampling parameters and the position of the first planning track point.
4. The method of claim 3, wherein the sampling parameters include a sampling distance and a number of samples; determining the plurality of track points to be selected according to the sampling parameters and the position of the first planning track point, including:
determining a sampling area of the first planned track point according to the sampling distance and the position of the first planned track point;
and determining the plurality of track points to be selected in the sampling area according to the sampling number.
5. The method according to claim 3 or 4, wherein the determining a target track point in the plurality of track points to be selected according to the sampling information of the plurality of track points to be selected and the obstacle information comprises:
acquiring running information of the vehicle at the current position, wherein the running information comprises at least one of coordinates, orientation and speed of the vehicle at the current position;
determining a track point to be selected which meets the driving requirement of the vehicle from the track points to be selected according to the driving information and the sampling information of the track points to be selected;
and determining the target track points in the to-be-selected track points meeting the driving requirements.
6. The method according to claim 5, wherein if none of the plurality of trajectory points to be selected meets the driving requirement, the method further comprises:
updating the sampling parameters, and determining at least one new track point to be selected according to the updated sampling parameters;
acquiring new sampling information of the at least one new track point to be selected;
and determining the target track point in the at least one new track point to be selected according to the new sampling information and the obstacle information.
7. The method of any of claims 1-6, wherein the method further comprises:
acquiring a plurality of track points in a feasible region, and map data and initial obstacle information of the feasible region;
acquiring sampling information of a plurality of track points in the feasible region;
and acquiring the planned path according to the sampling information of the plurality of track points, the map data and the initial obstacle information.
8. A trajectory planning apparatus comprising:
the determining unit is used for determining a first planned track point in the planned path according to the current position and the planned path of the vehicle, wherein the first planned track point is the next planned track point of the current position;
the processing unit is used for determining a plurality of track points to be selected corresponding to the first planning track point according to the barrier information of the current position and the first planning track point;
the acquisition unit is used for acquiring the sampling information of the plurality of track points to be selected;
and the planning unit is used for determining a target track point in the plurality of track points to be selected according to the sampling information of the plurality of track points to be selected and the obstacle information, and controlling the vehicle to run towards the target track point.
9. The apparatus of claim 8, wherein the processing unit comprises:
the first acquisition module is used for acquiring track information of the vehicle from a first position to the current position, wherein the first position is a position which is previous to the current position;
and the first determining module is used for determining the plurality of track points to be selected according to the track information, the obstacle information and the first planned track point.
10. The apparatus of claim 9, wherein the first determining means comprises:
the first obtaining submodule is used for obtaining sampling parameters corresponding to the first planning track point according to the track information and the obstacle information;
and the first determining submodule is used for determining the plurality of track points to be selected according to the sampling parameters and the position of the first planning track point.
11. The apparatus of claim 10, wherein the sampling parameters include a sampling distance and a number of samples; the first determination submodule is specifically configured to:
determining a sampling area of the first planned track point according to the sampling distance and the position of the first planned track point;
and determining the plurality of track points to be selected in the sampling area according to the sampling number.
12. The apparatus according to claim 10 or 11, wherein the planning unit comprises:
the second acquisition module is used for acquiring the running information of the vehicle at the current position, and the running information comprises at least one of the coordinate, the orientation and the speed of the vehicle at the current position;
the second determining module is used for determining the track points to be selected which meet the driving requirements of the vehicle from the track points to be selected according to the driving information and the sampling information of the track points to be selected;
and the third determining module is used for determining the target track point in the to-be-selected track points meeting the driving requirement.
13. The apparatus of claim 12, wherein if none of the plurality of to-be-selected trajectory points satisfies the driving requirement, the planning unit is further configured to:
updating the sampling parameters, and determining at least one new track point to be selected according to the updated sampling parameters;
acquiring new sampling information of the at least one new track point to be selected;
and determining the target track point in the at least one new track point to be selected according to the new sampling information and the obstacle information.
14. The apparatus according to any one of claims 8-13, further comprising an obtaining unit configured to:
acquiring a plurality of track points in a feasible region, and map data and initial obstacle information of the feasible region;
acquiring sampling information of a plurality of track points in the feasible region;
and acquiring the planned path according to the sampling information of the plurality of track points, the map data and the initial obstacle information.
15. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
16. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-7.
17. A computer program product comprising a computer program which, when executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
18. An autonomous vehicle comprising the electronic device of claim 15.
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