CN117885764A - Vehicle track planning method and device, vehicle and storage medium - Google Patents
Vehicle track planning method and device, vehicle and storage medium Download PDFInfo
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Abstract
The application relates to the technical field of automatic driving of vehicles, in particular to a track planning method and device for vehicles, the vehicles and a storage medium, wherein the method comprises the following steps: based on the perception information of the vehicle to be planned, constructing a constraint range of a preset constraint condition of the vehicle to be planned and a planning problem objective function, and obtaining a final track planning problem according to the constraint range of the preset constraint condition and the planning problem objective function; and solving a final track planning problem according to the current position information, the current lane information, the surrounding obstacle information and the track prediction information of the surrounding obstacles to obtain a solution vector of a planned track point at a future moment, and generating a final planned track of the vehicle to be planned. Therefore, the problems that the space-time decoupling planning mode separately processes the path planning and the speed planning, so that information is lost and global optimum cannot be achieved are solved, the time-space joint planning is realized, the planning efficiency is improved, and the feasibility, the safety and the flexibility of the vehicle driving track are ensured.
Description
Technical Field
The present application relates to the field of automatic driving technologies of vehicles, and in particular, to a method and apparatus for planning a trajectory of a vehicle, and a storage medium.
Background
With the popularization of vehicles in life, automatic driving is also gradually entering into people's daily life. The key to vehicle autopilot is the planning of the autopilot trajectory at a future time. Therefore, the trajectory planning technology in the field of autopilot is crucial for achieving safe, efficient, natural driving behavior.
In the related art, the track planning technology adopted in the current automatic driving field mostly separates the time dimension and the space dimension in the planning problem, and simplifies the planning problem in a distributed solution mode so as to meet the limitation of the calculation force of an automatic driving system.
However, the separate processing of the time dimension and the space dimension may result in partial information loss, and not be globally optimized, so that the decoupled trajectory planning method performs poorly for complex traffic conditions (such as multi-vehicle interaction, obstacle avoidance, etc.), and an improvement is needed.
Disclosure of Invention
The application provides a vehicle track planning method and device, a vehicle and a storage medium, and aims to solve the problems that information is lost and global optimum cannot be achieved due to the fact that a space-time decoupling planning mode is used for processing path planning and speed planning separately.
An embodiment of a first aspect of the present application provides a track planning method for a vehicle, including the steps of:
Obtaining perception information of a vehicle to be planned, wherein the perception information comprises current position information, current lane information, surrounding barrier information and track prediction information of surrounding barriers;
Based on the perception information, constructing a constraint range of at least one preset constraint condition of the vehicle to be planned and a planning problem objective function, and obtaining a final track planning problem according to the constraint range of the at least one preset constraint condition and the planning problem objective function; and
And solving the final track planning problem according to the current position information, the current lane information, the surrounding obstacle information and the track prediction information of the surrounding obstacle to obtain a solution vector of a future time planning track point, and generating a final planning track of the vehicle to be planned according to the solution vector of the future time planning track point.
According to the technical means, the problems that the space-time decoupling planning mode is used for processing path planning and speed planning separately, so that information is lost and global optimum cannot be achieved are solved, time-space joint planning is achieved, planning efficiency is improved, and feasibility, safety and flexibility of vehicle running tracks are guaranteed.
According to one embodiment of the present application, the constructing, based on the perceived information, a constraint range of at least one preset constraint condition of the vehicle to be planned and a planning problem objective function includes:
Acquiring a motion constraint condition, a speed constraint condition, a boundary constraint condition, a global reference line offset distance cost item and a control quantity cost item of the vehicle to be planned;
determining a first constraint range of the motion constraint condition, a second constraint range of the speed constraint condition and a third constraint range of the boundary constraint condition based on the perception information;
and respectively converting the global reference line offset distance cost item and the control quantity cost item into quadratic forms to obtain an offset distance cost function and a control quantity cost function, and obtaining the planning problem objective function according to the offset distance cost function and the control quantity cost function.
According to the technical means, the motion constraint condition considers that the motion state of the automatic driving vehicle needs to meet the kinematic constraint, the speed constraint condition ensures that the speed of each time point in the vehicle track planning result does not exceed the set running speed, the global reference line offset distance cost term considers that the automatic driving vehicle needs to keep running on a lane given by a route and an upper layer decision in the running process, and the control quantity cost term ensures the executability of the planning track.
According to one embodiment of the present application, the obtaining the final trajectory planning problem according to the constraint range of the at least one preset constraint condition and the planning problem objective function includes:
And obtaining the final track planning problem according to the first constraint range, the second constraint range, the third constraint range and the planning problem objective function.
According to the technical means, constraint conditions in different aspects are comprehensively considered by combining the first constraint range, the second constraint range and the third constraint range, so that the generated final track meets all constraints, and the feasibility of a planning result is improved.
According to one embodiment of the application, the final trajectory planning problem is:
；
Wherein is an objective function of the optimization problem,/> is an offset distance cost function,/> is a control quantity cost function,/> is an i+1th moment state independent variable vector,/> is a state transfer function,/> is an i-th moment state independent variable vector,/> is a time step identifier,/> is a total number of state time steps,/> is a starting moment state independent variable vector,/> is a position state of the vehicle at the planning starting moment,/> is a constraint matrix,/> is an independent variable of the track planning problem, and/> is an upper limit vector of the constraint.
According to the technical means, the trajectory planning problem is converted into the quadratic programming problem, so that the quadratic programming problem can be solved more quickly, the planning efficiency is improved, and the trajectory running safety of the automatic driving vehicle is ensured compared with a non-convex optimization problem solving method used in space-time combined planning in the industry.
According to one embodiment of the present application, the generating the final planned trajectory of the vehicle to be planned according to the solution vector of the planned trajectory point at the future time includes:
Generating a final planned track of the vehicle to be planned according to the solution vector of the planned track point at the future moment based on a preset track planning relation, wherein the preset track planning relation is as follows:
；
Wherein 、/> is the coordinates of each point in the track planning result,/> 、/> is the position variable in the planning result,/> is the heading angle of each point,/> is the x-direction speed component at i time,/> is the y-direction speed component at i time,/> is the speed of each point,/> is the x-direction acceleration component at i time,/> is the y-direction acceleration component at i time,/> is the jerk of each point,/> is the i-time acceleration,/> is the i-1 time acceleration,/> is the i-time accumulated mileage,/> is the i-1 time accumulated mileage,/> is the time interval between the planned track points,/> is the x-axis coordinates at i-1 time, and/> is the y-axis coordinates at i-1 time.
According to the technical means, the efficiency of path planning can be improved through preset path planning, the consistency of the whole path can be ensured by generating the final planned path according to the solution vector of the planned path points at the future moment, and therefore the optimal planned path is generated for the vehicle to be planned.
According to one embodiment of the present application, after generating the final planned trajectory of the vehicle to be planned according to the solution vector of the planned trajectory point at the future time, the method further includes:
and controlling the vehicle to be planned to run according to the final planned track.
According to the technical means, the vehicle is controlled to run according to the final planned track, so that the accuracy and stability of an automatic driving system can be improved, the vehicle can run according to the planned path more accurately, the vehicle is prevented from colliding with other vehicles or obstacles, and the running safety of the vehicle is improved.
According to one embodiment of the present application, the current lane information includes at least one of road center line information, road first boundary information, road second boundary information, and two adjacent lane center information of the vehicle to be planned;
The surrounding obstacle information includes at least one of coordinate information of the surrounding obstacle, heading angle information of the surrounding obstacle, speed information of the surrounding obstacle, and acceleration information of the surrounding obstacle.
According to the technical means, the road center line information and the road boundary information are beneficial to determining the position of the vehicle in the lane, and the adjacent lane center information is beneficial to planning a path of the vehicle, so that the running efficiency and the safety are improved. The surrounding obstacle information can provide the vehicle to sense and position the positions of other objects, the course angle information of the surrounding obstacle can inform the directions of the other objects of the vehicle, the speed information of the surrounding obstacle is beneficial to the vehicle to predict the motion trail of the other objects, and the acceleration information of the surrounding obstacle can provide more accurate and real-time object motion states.
According to the track planning method for the vehicle, provided by the embodiment of the application, the constraint range and the planning problem objective function are constructed based on the perception information of the vehicle, the final track planning problem is solved according to the track prediction information to obtain the solution vector of the future time planning track point, and the final planning track is generated. Therefore, the problems that the space-time decoupling planning mode separately processes the path planning and the speed planning, so that information is lost and global optimum cannot be achieved are solved, the time-space joint planning is realized, the planning efficiency is improved, and the feasibility, the safety and the flexibility of the vehicle driving track are ensured.
An embodiment of a second aspect of the present application provides a trajectory planning device for a vehicle, including:
The system comprises an acquisition module, a calculation module and a calculation module, wherein the acquisition module is used for acquiring perception information of a vehicle to be planned, wherein the perception information comprises current position information, current lane information, surrounding obstacle information and track prediction information of surrounding obstacles;
the processing module is used for constructing a constraint range of at least one preset constraint condition of the vehicle to be planned and a planning problem objective function based on the perception information, and obtaining a final track planning problem according to the constraint range of the at least one preset constraint condition and the planning problem objective function; and
And the track planning module is used for solving the final track planning problem according to the current position information, the current lane information, the surrounding obstacle information and the track prediction information of the surrounding obstacle to obtain a solution vector of a future time planning track point, and generating a final planning track of the vehicle to be planned according to the solution vector of the future time planning track point.
According to one embodiment of the application, the processing module is configured to:
Acquiring a motion constraint condition, a speed constraint condition, a boundary constraint condition, a global reference line offset distance cost item and a control quantity cost item of the vehicle to be planned;
determining a first constraint range of the motion constraint condition, a second constraint range of the speed constraint condition and a third constraint range of the boundary constraint condition based on the perception information;
and respectively converting the global reference line offset distance cost item and the control quantity cost item into quadratic forms to obtain an offset distance cost function and a control quantity cost function, and obtaining the planning problem objective function according to the offset distance cost function and the control quantity cost function.
According to one embodiment of the application, the processing module is configured to:
And obtaining the final track planning problem according to the first constraint range, the second constraint range, the third constraint range and the planning problem objective function.
According to one embodiment of the application, the final trajectory planning problem is:
；
Wherein is an objective function of the optimization problem,/> is an offset distance cost function,/> is a control quantity cost function,/> is an i+1th moment state independent variable vector,/> is a state transfer function,/> is an i-th moment state independent variable vector,/> is a time step identifier,/> is a total number of state time steps,/> is a starting moment state independent variable vector,/> is a position state of the vehicle at the planning starting moment,/> is a constraint matrix,/> is an independent variable of the track planning problem, and/> is an upper limit vector of the constraint.
According to one embodiment of the application, the trajectory planning module is configured to:
Generating a final planned track of the vehicle to be planned according to the solution vector of the planned track point at the future moment based on a preset track planning relation, wherein the preset track planning relation is as follows:
；
Wherein 、/> is the coordinates of each point in the track planning result,/> 、/> is the position variable in the planning result,/> is the heading angle of each point,/> is the x-direction speed component at i time,/> is the y-direction speed component at i time,/> is the speed of each point,/> is the x-direction acceleration component at i time,/> is the y-direction acceleration component at i time,/> is the jerk of each point,/> is the i-time acceleration,/> is the i-1 time acceleration,/> is the i-time accumulated mileage,/> is the i-1 time accumulated mileage,/> is the time interval between the planned track points,/> is the x-axis coordinates at i-1 time, and/> is the y-axis coordinates at i-1 time.
According to one embodiment of the present application, after generating a final planned trajectory of the vehicle to be planned according to the solution vector of the planned trajectory point at the future time, the trajectory planning module is further configured to:
and controlling the vehicle to be planned to run according to the final planned track.
According to one embodiment of the present application, the current lane information includes at least one of road center line information, road first boundary information, road second boundary information, and two adjacent lane center information of the vehicle to be planned;
The surrounding obstacle information includes at least one of coordinate information of the surrounding obstacle, heading angle information of the surrounding obstacle, speed information of the surrounding obstacle, and acceleration information of the surrounding obstacle.
According to the track planning device for the vehicle, provided by the embodiment of the application, the constraint range and the planning problem objective function are constructed based on the perception information of the vehicle, the final track planning problem is solved according to the track prediction information to obtain the solution vector of the planning track point at the future moment, and the final planning track is generated. Therefore, the problems that the space-time decoupling planning mode separately processes the path planning and the speed planning, so that information is lost and global optimum cannot be achieved are solved, the time-space joint planning is realized, the planning efficiency is improved, and the feasibility, the safety and the flexibility of the vehicle driving track are ensured.
An embodiment of a third aspect of the present application provides a vehicle including: the vehicle track planning system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the vehicle track planning method according to the embodiment.
A fourth aspect embodiment of the present application provides a computer-readable storage medium storing computer instructions for causing a computer to execute the trajectory planning method of a vehicle as described in the above embodiment.
Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.
Drawings
The foregoing and/or additional aspects and advantages of the application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
fig. 1 is a flowchart of a track planning method for a vehicle according to an embodiment of the present application;
FIG. 2 is a flow chart of space-time joint trajectory planning in accordance with one embodiment of the application;
FIG. 3 is a block schematic diagram of a trajectory planning device of a vehicle according to an embodiment of the present application;
Fig. 4 is a schematic structural diagram of a vehicle according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.
The following describes a track planning method, a track planning device, a vehicle and a storage medium of a vehicle according to an embodiment of the present application with reference to the accompanying drawings. Aiming at the problems that track planning information is lost and global optimization is difficult to achieve due to the fact that the track planning information is lost in a step-by-step mode in the space-time decoupling planning method in the background technology, the application provides a track planning method for a vehicle, a constraint range and a planning problem objective function are constructed based on perception information of the vehicle, a final track planning problem is solved according to track prediction information to obtain a solution vector of a future time planning track point, and a final planning track is generated. Therefore, the problems that the space-time decoupling planning mode separately processes the path planning and the speed planning, so that information is lost and global optimum cannot be achieved are solved, the time-space joint planning is realized, the planning efficiency is improved, and the feasibility, the safety and the flexibility of the vehicle driving track are ensured.
Specifically, fig. 1 is a flow chart of a track planning method for a vehicle according to an embodiment of the present application.
As shown in fig. 1, the track planning method of the vehicle includes the following steps:
in step S101, perceived information of a vehicle to be planned is acquired, wherein the perceived information includes current position information, current lane information, surrounding obstacle information, and trajectory prediction information of surrounding obstacles.
Wherein in some embodiments, the current location information includes coordinate information of the vehicle to be planned, heading angle information of the vehicle to be planned, speed information of the vehicle to be planned, and acceleration information of the vehicle to be planned, and the current lane information includes at least one of road center line information, road first boundary information, road second boundary information, and two adjacent lane center information of the vehicle to be planned; the surrounding obstacle information includes at least one of coordinate information of the surrounding obstacle, heading angle information of the surrounding obstacle, speed information of the surrounding obstacle, and acceleration information of the surrounding obstacle, and the trajectory prediction information of the surrounding obstacle includes position and speed information of the obstacle vehicle within a future preset time.
It should be noted that, the common space-time decoupling mode transfers the coordinate system to the Frenet coordinate system based on the road reference line, and since the Frenet coordinate system limits the automatic driving vehicle to the reference line, the method depends on the smoothness of the reference line, and the principle thereof results in that the space-time decoupling planning method is difficult to realize under the road with large curvature. Therefore, the coordinate system of the vehicle track planning process of the application is a Cartesian coordinate system, and the coordinate information of the vehicle to be planned and the coordinate information of surrounding obstacles are coordinate values under the Cartesian coordinate system.
Alternatively, the road first boundary information may be road left boundary information, the road second boundary information may be road right boundary information, and the two adjacent lane center information may be left lane center information and right lane center information.
Specifically, the application can acquire the current position information through a positioning module (such as a positioning system), can acquire the current lane information through an upstream sensor sensing and map module (such as a navigation system and the like), can acquire surrounding obstacle information through a sensing module (such as a camera combined with a laser radar or a sensor), can provide route information through a route module, can acquire host vehicle reference line information through processing the upstream module combined with the map information, and can acquire track prediction information of surrounding obstacles through a prediction module (such as a prediction model established by learning the movement of an obstacle vehicle through using historical data). It should be noted that, the above-mentioned manner of obtaining the sensing information of the vehicle to be planned is merely exemplary, and is not limiting to the present application, and those skilled in the art may take other manners to obtain the sensing information of the vehicle to be planned according to the actual situation, so that redundancy is avoided and detailed descriptions thereof are omitted.
In step S102, based on the perception information, a constraint range of at least one preset constraint condition of the vehicle to be planned and a planning problem objective function are constructed, and a final track planning problem is obtained according to the constraint range of the at least one preset constraint condition and the planning problem objective function.
Specifically, by constructing the constraint range and the planning problem objective function by using the upstream input perception information, the behavior and the environment limitation of the vehicle to be planned can be described more accurately, thereby improving the accuracy of track planning.
Further, in some embodiments, constructing a constraint range and a planning problem objective function of at least one preset constraint condition of the vehicle to be planned based on the perception information includes: acquiring a motion constraint condition, a speed constraint condition, a boundary constraint condition, a global reference line offset distance cost item and a control quantity cost item of a vehicle to be planned; determining a first constraint range of the motion constraint condition, a second constraint range of the speed constraint condition and a third constraint range of the boundary constraint condition based on the perception information; and respectively converting the global reference line offset distance cost item and the control quantity cost item into quadratic forms to obtain an offset distance cost function and a control quantity cost function, and obtaining a planning problem objective function according to the offset distance cost function and the control quantity cost function.
Specifically, considering that the motion state of the automatic driving vehicle needs to meet the kinematic constraint, setting the motion trail of the vehicle to be planned to meet the following motion constraint conditions under a Cartesian coordinate system:
Wherein is the i+1 time x-axis coordinate,/> is the i time x-axis coordinate,/> is the i time x-axis direction velocity component, is the time step,/> is the i time x-axis direction acceleration component,/> is the i+1 time y-axis coordinate,/> is the i time y-axis coordinate,/> is the i time y-axis direction velocity component,/> is the i time y-axis direction acceleration component,/> is the i+1 time x-axis direction velocity component, and/> is the i+1 time y-axis direction velocity component.
The track planning starting point state is consistent with the initial position of the vehicle, and the following first constraint range is obtained:
Wherein is the initial time x-axis position,/> is the initial time y-axis position,/> is the initial time x-axis direction velocity component,/> is the initial time y-axis direction velocity component,/> is the x-axis coordinate position of the vehicle at the planned starting time,/> is the y-axis coordinate position of the vehicle at the planned starting time,/> is the speed of the vehicle at the starting time to be planned, and/> is the heading angle of the vehicle at the starting time to be planned.
Further, in order to ensure that the vehicle speed at each time point in the vehicle track planning result does not exceed the set running speed, planning is performed under a Cartesian coordinate system, so that the following speed constraint conditions are obtained:
Wherein is the x-axis direction speed component at i time,/> is the set cruising speed,/> is the i-time vehicle heading angle,/> is the transverse speed upper limit coefficient reserved for allowing lateral movement of the vehicle,/> is the y-axis direction speed component at i time,/> is the transverse speed lower limit coefficient reserved for allowing lateral movement of the vehicle.
Because the track planning is completed under the Cartesian coordinate system, if a large deviation exists between the road reference line and the X-axis of the Cartesian coordinate system, the following adjustment is carried out on the speed constraint:
for the acceleration control amount, it is limited to a certain fixed range:
Wherein is the x-axis direction acceleration component at i time,/> is the y-axis direction acceleration component at i time,/> is the set fixed acceleration control amount limit.
Therefore, the space-time combined track planning method based on the Cartesian coordinate system gets rid of the dependence of the traditional track planning method on the Frenet coordinate system, and improves the adaptability of the driving road.
Further, considering the vehicle running boundary constraint, because the embodiment of the application performs the track planning task under the Cartesian coordinate system, and adopts the coordinate rotation mode to perform the road boundary constraint on the future running track points of the vehicle, the embodiment of the application uses the lane keeping working condition as an example to describe the boundary constraint setting method:
for the left boundary constraint, the transverse offset of the future track point relative to the reference line is obtained through coordinate transformation to carry out constraint, and the following steps are obtained:
Wherein is the heading angle corresponding to the lane left boundary point,/> 、/> is the position coordinate of the left boundary point, and/> is the width of the vehicle to be planned.
Similarly, for the right boundary, it is obtained by coordinate transformation:
Wherein is the course angle corresponding to the lane right boundary point, and/(、/>) is the position coordinate of the right boundary point.
Because a certain driving distance is required to be kept between the automatic driving vehicle and surrounding traffic participants, the embodiment of the application restrains the future track boundary of the automatic driving vehicle based on the future track of the obstacle vehicle, and the specific implementation is realized by modifying the left and right side driving road boundaries:
If an obstacle vehicle appears on the right side in front of the automatic driving vehicle, positioning a track area which is possibly longitudinally overlapped in the future through distance and vehicle speed information, and modifying the right side boundary of the corresponding area into the left boundary of the obstacle vehicle plus a reserved transverse threshold value:
Wherein is the obstacle vehicle transverse coordinate, and/() is the set safety distance.
Therefore, the defect that the road shape is difficult to describe under a Cartesian coordinate system is overcome by a two-dimensional coordinate conversion method, and constraint of describing the relative road offset of the automatic driving vehicle through the rotation coordinates is realized.
Further, since the lane given by the route and the upper layer decision needs to be kept for driving in the running process of the automatic driving vehicle, a global reference line offset distance cost term is introduced:
Wherein is global reference line offset distance cost term,/> is total number of steps of planning time,/> is sum variable,/> 、 is position variable in planning result,/> 、/> is reference line position,/> is x-axis position deviation cost coefficient, and/> is y-axis position deviation cost coefficient.
Further, ignoring its constant term, converting it to quadratic form can be expressed as:
Wherein is an offset distance cost function converted into a quadratic form,/> is an independent variable of the track planning problem, is a quadratic term in the offset distance cost function, and/> is a first order term coefficient matrix in the offset distance cost function.
Wherein, , each variable in the column vector represents the vehicle track planning x-axis position coordinate, y-axis position coordinate, x-axis speed component, y-axis speed component, x-axis acceleration control quantity, y-axis acceleration control quantity respectively.
Further, in order to ensure the performability of the planned trajectory, the control amount required for planning the trajectory is required to be as small as possible, and therefore, a control amount cost term is set:
Wherein is a control amount cost term,/> is a total step number of planning time,/> is a sum variable,/> is an x-axis control amount cost coefficient,/> is an i-time x-axis direction acceleration component,/> is a y-axis control amount cost coefficient, and/> is an i-time y-axis direction acceleration component.
Converting the control quantity cost term into a quadratic form can be expressed as:
Wherein is a control quantity cost function converted into a quadratic form, and/() is an independent variable of the track planning problem, and is a quadratic term coefficient matrix in the cost function.
Further, in some embodiments, deriving the final trajectory planning problem from the constraint range of the at least one preset constraint and the planning problem objective function includes: and obtaining a final track planning problem according to the first constraint range, the second constraint range, the third constraint range and the planning problem objective function.
Wherein, in some embodiments, the final trajectory planning problem is:
；
Wherein is an objective function of the optimization problem,/> is an offset distance cost function,/> is a control quantity cost function,/> is an i+1th moment state independent variable vector,/> is a state transfer function,/> is an i-th moment state independent variable vector,/> is a time step identifier,/> is a total number of state time steps,/> is a starting moment state independent variable vector,/> is a position state of the vehicle at the planning starting moment,/> is a constraint matrix,/> is an independent variable of the track planning problem, and/> is an upper limit vector of the constraint.
Therefore, the space occupied by the running position of the vehicle to be planned, the speed, the acceleration and the steering wheel corner of the vehicle to be planned are taken as optimization variables, the quadratic programming problem is built, meanwhile, the motion state and the dynamics constraint of the vehicle to be planned are considered, the collision constraint of the vehicle to be planned and the obstacle vehicle is considered, the relative distance between the vehicle to be planned and the road reference line is the element, and the time-space joint programming is realized, so that the feasibility of the running track of the vehicle to be planned is ensured.
In step S103, the final track planning problem is solved according to the current position information, the current lane information, the surrounding obstacle information and the track prediction information of the surrounding obstacle to obtain a solution vector of the future time planning track point, and the final planning track of the vehicle to be planned is generated according to the solution vector of the future time planning track point.
Further, in some embodiments, generating a final planned trajectory of the vehicle to be planned from the solution vector of the planned trajectory points at the future time, includes: generating a final planned track of the vehicle to be planned according to a solution vector of the planned track point at a future moment based on a preset track planning relation, wherein the preset track planning relation is as follows:
；
wherein 、/> is the coordinates of each point in the track planning result,/> 、/> is the position variable in the planning result,/> is the heading angle of each point,/> is the x-direction speed component at i time,/> is the y-direction speed component at i time,/> is the speed of each point,/> is the x-direction acceleration component at i time,/> is the y-direction acceleration component at i time,/> is the jerk of each point,/> is the i-time acceleration,/> is the i-1 time acceleration,/> is the i-time accumulated mileage,/> is the i-1 time accumulated mileage,/> is the time interval between the planned track points,/> is the x-axis coordinates at i-1 time, and/> is the y-axis coordinates at i-1 time.
Specifically, the final track planning problem is input into an optimizer for solving, and a solution vector of the future time planning track point can be obtained, wherein/> is used for processing the solution vector of the future time planning track point according to a preset track planning relation, so that the final planning track of the vehicle to be planned is obtained.
Further, in some embodiments, after generating a final planned trajectory of the vehicle to be planned according to the solution vector of the planned trajectory point at the future time, the method further includes: and controlling the vehicle to be planned to run according to the final planned track.
Specifically, the planning module issues a track planning result, the control module converts the planning result into a control result after receiving the track, and the vehicle to be planned is controlled to run according to the final planning track, so that the running safety of the vehicle is improved.
Therefore, the application can simultaneously plan the position and speed information of the future running track point at one time through modeling and analyzing the dynamic and static obstacles of the local vehicle based on the environmental awareness, and generate the optimized local path so as to ensure that the vehicle avoids the obstacles in the dynamic environment, follows the traffic rules and maintains the stable running state.
In order to facilitate a clearer and intuitive understanding of the trajectory planning method for a vehicle according to an embodiment of the present application by those skilled in the art, the following detailed description is provided with reference to fig. 2.
As shown in fig. 2, the space-time joint trajectory planning procedure includes the following steps:
s201, acquiring environment information.
S202, optimizing targets and constructing constraint conditions.
And S203, solving an optimization problem and extracting a planning result.
S204, issuing a track planning result, and converting the control module into a control instruction.
Therefore, the track planning problem under space-time combination is converted into a secondary optimization problem through the design optimization problem, the time dimension and the space dimension are comprehensively considered under the condition that the calculation force requirement is not obviously increased, the transverse path planning problem and the longitudinal speed planning problem are solved in a combined mode, and the automatic driving track planning with higher safety and reliability is achieved.
According to the track planning method for the vehicle, which is provided by the embodiment of the application, the constraint range and the planning problem objective function are constructed based on the perception information of the vehicle, the final track planning problem is solved according to the track prediction information to obtain the solution vector of the future time planning track point, and the final planning track is generated. Therefore, the problems that the space-time decoupling planning mode separately processes the path planning and the speed planning, so that information is lost and global optimum cannot be achieved are solved, the time-space joint planning is realized, the planning efficiency is improved, and the feasibility, the safety and the flexibility of the vehicle driving track are ensured.
Next, a track planning apparatus for a vehicle according to an embodiment of the present application will be described with reference to the accompanying drawings.
Fig. 3 is a block schematic diagram of a trajectory planning device 10 of a vehicle according to an embodiment of the present application.
As shown in fig. 3, the trajectory planning device 10 of the vehicle includes: an acquisition module 100, a processing module 200 and a trajectory planning module 300.
The acquiring module 100 is configured to acquire sensing information of a vehicle to be planned, where the sensing information includes current position information, current lane information, surrounding obstacle information, and track prediction information of surrounding obstacles; the processing module 200 is configured to construct a constraint range of at least one preset constraint condition of a vehicle to be planned and a planning problem objective function based on the perception information, and obtain a final track planning problem according to the constraint range of the at least one preset constraint condition and the planning problem objective function; the track planning module 300 is configured to solve a final track planning problem according to the current position information, the current lane information, the surrounding obstacle information, and the track prediction information of the surrounding obstacle to obtain a solution vector of a planned track point at a future time, and generate a final planned track of the vehicle to be planned according to the solution vector of the planned track point at the future time.
Further, in some embodiments, the processing module 200 is configured to: acquiring a motion constraint condition, a speed constraint condition, a boundary constraint condition, a global reference line offset distance cost item and a control quantity cost item of a vehicle to be planned; determining a first constraint range of the motion constraint condition, a second constraint range of the speed constraint condition and a third constraint range of the boundary constraint condition based on the perception information; and respectively converting the global reference line offset distance cost item and the control quantity cost item into quadratic forms to obtain an offset distance cost function and a control quantity cost function, and obtaining a planning problem objective function according to the offset distance cost function and the control quantity cost function.
Further, in some embodiments, the processing module 200 is configured to: and obtaining a final track planning problem according to the first constraint range, the second constraint range, the third constraint range and the planning problem objective function.
Further, in some embodiments, the final trajectory planning problem is:
；
Wherein is an objective function of the optimization problem,/> is an offset distance cost function,/> is a control quantity cost function,/> is an i+1th moment state independent variable vector,/> is a state transfer function,/> is an i-th moment state independent variable vector,/> is a time step identifier,/> is a total number of state time steps,/> is a starting moment state independent variable vector,/> is a position state of the vehicle at the planning starting moment,/> is a constraint matrix,/> is an independent variable of the track planning problem, and/> is an upper limit vector of the constraint.
Further, in some embodiments, the trajectory planning module 300 is configured to:
Generating a final planned track of the vehicle to be planned according to a solution vector of the planned track point at a future moment based on a preset track planning relation, wherein the preset track planning relation is as follows:
；
Wherein 、/> is the coordinates of each point in the track planning result,/> 、/> is the position variable in the planning result,/> is the heading angle of each point,/> is the x-direction speed component at i time,/> is the y-direction speed component at i time,/> is the speed of each point,/> is the x-direction acceleration component at i time,/> is the y-direction acceleration component at i time,/> is the jerk of each point,/> is the i-time acceleration,/> is the i-1 time acceleration,/> is the i-time accumulated mileage,/> is the i-1 time accumulated mileage,/> is the time interval between the planned track points,/> is the x-axis coordinates at i-1 time, and/> is the y-axis coordinates at i-1 time. /(I)
Further, in some embodiments, after generating the final planned trajectory of the vehicle to be planned according to the solution vector of the planned trajectory point at the future time, the trajectory planning module 300 is further configured to: and controlling the vehicle to be planned to run according to the final planned track.
Further, in some embodiments, the current lane information includes at least one of road centerline information, road first boundary information, road second boundary information, and two adjacent lane centerline information of the vehicle to be planned; the surrounding obstacle information includes at least one of coordinate information of the surrounding obstacle, heading angle information of the surrounding obstacle, speed information of the surrounding obstacle, and acceleration information of the surrounding obstacle.
It should be noted that the foregoing explanation of the embodiment of the track planning method for a vehicle is also applicable to the track planning apparatus for a vehicle of this embodiment, and will not be repeated here.
According to the track planning device for the vehicle, which is provided by the embodiment of the application, a constraint range and a planning problem objective function are constructed based on the perception information of the vehicle, a final track planning problem is solved according to track prediction information to obtain a solution vector of a future time planning track point, and a final planning track is generated. Therefore, the problems that the space-time decoupling planning mode separately processes the path planning and the speed planning, so that information is lost and global optimum cannot be achieved are solved, the time-space joint planning is realized, the planning efficiency is improved, and the feasibility, the safety and the flexibility of the vehicle driving track are ensured.
Fig. 4 is a schematic structural diagram of a vehicle according to an embodiment of the present application. The vehicle may include:
Memory 401, processor 402, and a computer program stored on memory 401 and executable on processor 402.
The processor 402 implements the trajectory planning method of the vehicle provided in the above-described embodiment when executing a program.
Further, the vehicle further includes:
a communication interface 403 for communication between the memory 401 and the processor 402.
A memory 401 for storing a computer program executable on the processor 402.
Memory 401 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
If the memory 401, the processor 402, and the communication interface 403 are implemented independently, the communication interface 403, the memory 401, and the processor 402 may be connected to each other by a bus and perform communication with each other. The bus may be an industry standard architecture (Industry Standard Architecture, abbreviated ISA) bus, an external device interconnect (PERIPHERAL COMPONENT INTERCONNECT, abbreviated PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 4, but not only one bus or one type of bus.
Alternatively, in a specific implementation, if the memory 401, the processor 402, and the communication interface 403 are integrated on a chip, the memory 401, the processor 402, and the communication interface 403 may perform communication with each other through internal interfaces.
Processor 402 may be a central processing unit (Central Processing Unit, abbreviated as CPU), or an Application SPECIFIC INTEGRATED Circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the application.
The present embodiment also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the trajectory planning method of a vehicle as above.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, for example, two, three, etc., unless specifically defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer cartridge (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (10)
1. A method of trajectory planning for a vehicle, comprising the steps of:
Obtaining perception information of a vehicle to be planned, wherein the perception information comprises current position information, current lane information, surrounding barrier information and track prediction information of surrounding barriers;
Based on the perception information, constructing a constraint range of at least one preset constraint condition of the vehicle to be planned and a planning problem objective function, and obtaining a final track planning problem according to the constraint range of the at least one preset constraint condition and the planning problem objective function; and
And solving the final track planning problem according to the current position information, the current lane information, the surrounding obstacle information and the track prediction information of the surrounding obstacle to obtain a solution vector of a future time planning track point, and generating a final planning track of the vehicle to be planned according to the solution vector of the future time planning track point.
2. The method according to claim 1, wherein constructing a constraint range and a planning problem objective function of at least one preset constraint of the vehicle to be planned based on the perception information comprises:
Acquiring a motion constraint condition, a speed constraint condition, a boundary constraint condition, a global reference line offset distance cost item and a control quantity cost item of the vehicle to be planned;
determining a first constraint range of the motion constraint condition, a second constraint range of the speed constraint condition and a third constraint range of the boundary constraint condition based on the perception information;
and respectively converting the global reference line offset distance cost item and the control quantity cost item into quadratic forms to obtain an offset distance cost function and a control quantity cost function, and obtaining the planning problem objective function according to the offset distance cost function and the control quantity cost function.
3. The method according to claim 2, wherein said deriving a final trajectory planning problem from said constraint range of said at least one preset constraint and said planning problem objective function comprises:
And obtaining the final track planning problem according to the first constraint range, the second constraint range, the third constraint range and the planning problem objective function.
4. A method according to claim 3, characterized in that the final trajectory planning problem is:
；
Wherein is an objective function of the optimization problem,/> is an offset distance cost function,/> is a control quantity cost function, is an i+1th moment state independent variable vector,/> is a state transfer function,/> is an i-th moment state independent variable vector, is a time step identifier,/> is a total number of state time steps,/> is a starting moment state independent variable vector,/> is a position state of the vehicle at the planning starting moment,/> is a constraint matrix,/> is an independent variable of the track planning problem, and/> is an upper limit vector of the constraint.
5. The method of claim 4, wherein the generating the final planned trajectory of the vehicle to be planned from the solution vector of the future time planned trajectory points comprises:
Generating a final planned track of the vehicle to be planned according to the solution vector of the planned track point at the future moment based on a preset track planning relation, wherein the preset track planning relation is as follows:
；
Wherein 、/> is the coordinates of each point in the track planning result,/> 、/> is the position variable in the planning result,/> is the heading angle of each point,/> is the x-direction speed component at i time,/> is the y-direction speed component at i time,/> is the speed of each point,/> is the x-direction acceleration component at i time,/> is the y-direction acceleration component at i time,/> is the jerk of each point, is the i-time acceleration,/> is the i-1-time acceleration,/> is the i-time accumulated mileage,/> is the i-1-time accumulated mileage,/> is the time interval between the planned track points,/> is the i-1-time x-axis coordinate, and/> is the i-1-time y-axis coordinate.
6. The method of claim 1, further comprising, after generating a final planned trajectory of the vehicle to be planned from the solution vector of planned trajectory points at the future time,:
and controlling the vehicle to be planned to run according to the final planned track.
7. The method according to any one of claims 1 to 6, wherein,
The current lane information comprises at least one of road center line information, road first boundary information, road second boundary information and two adjacent lane center information of the vehicle to be planned;
The surrounding obstacle information includes at least one of coordinate information of the surrounding obstacle, heading angle information of the surrounding obstacle, speed information of the surrounding obstacle, and acceleration information of the surrounding obstacle.
8. A trajectory planning device of a vehicle, characterized by comprising:
The system comprises an acquisition module, a calculation module and a calculation module, wherein the acquisition module is used for acquiring perception information of a vehicle to be planned, wherein the perception information comprises current position information, current lane information, surrounding obstacle information and track prediction information of surrounding obstacles;
the processing module is used for constructing a constraint range of at least one preset constraint condition of the vehicle to be planned and a planning problem objective function based on the perception information, and obtaining a final track planning problem according to the constraint range of the at least one preset constraint condition and the planning problem objective function; and
And the track planning module is used for solving the final track planning problem according to the current position information, the current lane information, the surrounding obstacle information and the track prediction information of the surrounding obstacle to obtain a solution vector of a future time planning track point, and generating a final planning track of the vehicle to be planned according to the solution vector of the future time planning track point.
9. A vehicle, characterized by comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the trajectory planning method of a vehicle as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for implementing a trajectory planning method of a vehicle as claimed in any one of claims 1-7.
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