CN115675529A - Simulation evaluation method and device for vehicle trajectory planning - Google Patents
Simulation evaluation method and device for vehicle trajectory planning Download PDFInfo
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Abstract
The application relates to a simulation evaluation method and a simulation evaluation device for vehicle trajectory planning, wherein the method comprises the following steps: acquiring planning data required by simulation, matching the current position of a vehicle with the optimal track of the previous period, determining a planning starting point, taking a road center line as a reference line according to the requirements of the transverse and longitudinal lane change boundary, selecting the length of the lane change process according to the speed to scatter points, obtaining a plurality of groups of local planning tracks, re-planning at intervals of a preset time length, calculating and obtaining the total track cost of each track, taking the track with the minimum total track cost as an optimal local path, and comparing the optimal curve obtained by fitting the position point based on the optimal local path in the whole process with the position of the vehicle in the actual tracking process to obtain an evaluation result. Therefore, the technical problems that only a rough planning track can be obtained through evaluation of a static safety boundary in the dynamic planning process and the accuracy of an evaluation result is low in the related technology are solved.
Description
Technical Field
The application relates to the technical field of motion planning, in particular to a simulation evaluation method and device for vehicle trajectory planning.
Background
Motion planning strategies, which were originally developed from the application of mobile robots, are considered as key to robot navigation, providing global and local trajectory planning to describe the behavior of the robot, while taking into account dynamic and kinematic models of the robot from a starting position to a final position. The difference between the vehicle and the robot is that the vehicle needs to consider the road condition constraint complying with the traffic rules, lane changing and overtaking of the vehicle are one of the common driving operations of the driver, the unmanned vehicle can frequently face the working condition in the driving process, the vehicle needs to correspondingly adjust according to the relative speed and distance between vehicles in the driving environment and the change information of other environments around the vehicle in the driving process to complete the driving requirement, and in the process, the vehicle needs to accurately evaluate the passing performance of safe lane changing and overtaking, so that the vehicle can safely run. Therefore, trajectory planning for unmanned vehicles is an important component for ensuring safe vehicle driving.
In the current stage of track planning, the method for quantitative evaluation of track planning is less, in the related technology, the curve shape can be determined by using control points and vehicle safety convenient points, the control points are selected as variables to obtain the optimal track, and evaluation is performed by comparing the track points in the whole planning and tracking process with the optimal track.
However, the related art is a dynamic planning process, and the state quantity changes continuously with the re-planning, and the dynamic re-planning process is evaluated through a static security boundary, and often only a rough planning trajectory can be obtained, and the accuracy of the trajectory planning evaluation is low and needs to be improved.
Disclosure of Invention
The application provides a simulation evaluation method and device for vehicle track planning, and aims to solve the technical problems that only a rough planning track can be obtained through evaluation by a static safety boundary in a dynamic planning process and the accuracy of an evaluation result is low in the related technology.
The embodiment of the first aspect of the application provides a simulation evaluation method for vehicle trajectory planning, which comprises the following steps: acquiring planning data required by simulation; matching the current position of the vehicle with the optimal track of the previous period based on the planning data, determining a planning starting point, taking the road center line as a reference line according to the requirements of the transverse and longitudinal lane change boundary, selecting the length of the lane change process according to the speed to scatter points to obtain a plurality of groups of local planning tracks, and re-planning at intervals of a preset time length; and calculating the priority cost, the collision cost, the transition cost and the maximum transverse acceleration cost of each track to obtain the total track cost of each track, taking the track with the minimum total track cost as an optimal local path, and comparing an optimal curve obtained by fitting the position points based on the optimal local path in the whole process with the vehicle position in the actual tracking process to obtain an evaluation result.
Optionally, in an embodiment of the present application, the planning data includes at least one of a position of the vehicle, a lane center line track point, an obstacle vehicle position, a vehicle size, and a safe distance during the lane change.
Optionally, in an embodiment of the present application, after obtaining the planning data required by the simulation, the method further includes: and performing difference processing on the track points of the lane center line so as to ensure that the processed uniform difference value ensures that the interval between the front point and the rear point meets the preset distance.
Optionally, in an embodiment of the present application, the calculation formula of the collision cost is:
the calculation formula of the transition cost is as follows:
r 3 ＝f((x t ,y t ),(x t-1 ,y t-1 ))＝(y t -y t-1 )d，
the maximum lateral acceleration cost calculation formula is as follows:
r 4 ＝f(κ)＝v 2 /r，
wherein r is 2 At the cost of collision, r 3 At a transition cost of r 4 At the maximum lateral acceleration penalty, x t 、y t For the time t corresponding to the position point coordinate, x, on the local planning track c 、y c Is the position of the obstacle, d c For planning the lateral distance of the trajectory from the obstacle,/ c For planning the longitudinal distance, x, of the trajectory from the obstacle t-1 、y t-1 And (3) corresponding to the coordinates of the position points on the planned track at the time t-1, wherein r is the curvature radius, v is the speed, and d is the track density.
Optionally, in an embodiment of the present application, the comparing the optimal curve obtained based on the position point fitting of the optimal local area path in the whole process with the vehicle position in the actual tracking process to obtain the evaluation result includes: obtaining a longitudinal deviation and/or curvature index range according to a plurality of reference values obtained by the collision cost and the maximum lateral acceleration cost; and obtaining a result of evaluating whether the lane change meets the requirement by comparing whether the error between the reference value of the middle position of the plurality of reference values and the actual value of the real vehicle meets the index range.
An embodiment of a second aspect of the present application provides a simulation evaluation device for vehicle trajectory planning, including: the acquisition module is used for acquiring planning data required by simulation; the re-planning module is used for matching the current position of the vehicle with the optimal track of the previous period based on the planning data, determining a planning starting point, selecting the length of the lane changing process according to the speed by taking the center line of the road as a reference line according to the requirements of lane changing boundary in the transverse direction and the longitudinal direction, scattering points to obtain a plurality of groups of local planning tracks, and re-planning at intervals of preset time; and the evaluation module is used for calculating the priority cost, the collision cost, the transition cost and the maximum transverse acceleration cost of each track to obtain the total track cost of each track, taking the track with the minimum total track cost as an optimal local path, and comparing an optimal curve obtained by fitting the position points based on the optimal local path in the whole process with the vehicle position in the actual tracking process to obtain an evaluation result.
Optionally, in an embodiment of the present application, the planning data includes at least one of a position of the vehicle, a lane center line track point, an obstacle vehicle position, a vehicle size, and a safe distance during lane change.
Optionally, in an embodiment of the present application, the method further includes: and the processing module is used for carrying out difference processing on the track points of the lane center line so as to ensure that the processed uniform difference value ensures that the interval between the front point and the rear point meets the preset distance.
Optionally, in an embodiment of the present application, the calculation formula of the collision cost is:
the calculation formula of the transition cost is as follows:
r 3 ＝f((x t ,y t ),(x t-1 ,y t-1 ))＝(y t -y t-1 )d，
the calculation formula of the maximum lateral acceleration cost is as follows:
r 4 ＝f(κ)＝v 2 /r，
wherein r is 2 At the cost of collision, r 3 At a transition cost of r 4 At the maximum lateral acceleration penalty, x t 、y t For the t moment corresponding to the position point coordinate, x, on the local planning track c 、y c Is the position of the obstacle, d c For planning the lateral distance of the trajectory from the obstacle,/ c For planning the longitudinal distance, x, of the trajectory from the obstacle t-1 、y t-1 And (3) corresponding to the coordinates of the position points on the planned track at the time t-1, wherein r is the curvature radius, v is the speed, and d is the track density.
Optionally, in an embodiment of the present application, the evaluation module: the calculation unit is used for obtaining the index range of the longitudinal deviation and/or the curvature according to a plurality of reference values obtained by the collision cost and the maximum lateral acceleration cost; and the evaluation unit is used for obtaining a result of evaluating whether the lane change meets the requirement by comparing whether the error between the reference value of the middle position of the plurality of reference values and the actual value of the real vehicle meets the index range.
An embodiment of a third aspect of the present application provides a vehicle, comprising: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the simulation evaluation method for vehicle trajectory planning according to the embodiment.
An embodiment of a fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program, and when the program is executed by a processor, the computer program implements the simulation evaluation method for vehicle trajectory planning as above.
According to the method and the device, re-planning can be performed according to a certain period through a dynamic point-scattering planning method based on planning data, the optimal local path is selected through adding cost, an optimal curve obtained through position point fitting based on the optimal local path in the whole process is compared with the vehicle position in the actual tracking process, an evaluation result is obtained, and the theoretical precision and the function landing speed of the evaluation can be effectively improved. Therefore, the technical problems that only a rough planning track can be obtained through evaluation of a static safety boundary in the dynamic planning process and the accuracy of an evaluation result is low in the related technology are solved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of a simulation evaluation method for vehicle trajectory planning according to an embodiment of the present application;
FIG. 2 is a schematic view of a lane coordinate system of a simulation evaluation method for vehicle trajectory planning according to an embodiment of the present application;
FIG. 3 is a schematic view of a local path spot of a simulation evaluation method for vehicle trajectory planning according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a lane-change model and curvature calculation and display of a simulation evaluation method for vehicle trajectory planning according to an embodiment of the present application;
FIG. 5 is a schematic diagram illustrating an optimal trajectory comparison of a simulation evaluation method for vehicle trajectory planning according to an embodiment of the application;
FIG. 6 is a flow chart of a method for simulation assessment of vehicle trajectory planning according to one embodiment of the present application;
fig. 7 is a schematic structural diagram of a simulation evaluation device for vehicle trajectory planning according to an embodiment of the present application;
FIG. 8 is a schematic structural diagram of a vehicle according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The following describes a simulation evaluation method and apparatus for vehicle trajectory planning according to an embodiment of the present application with reference to the drawings. In order to solve the technical problems that only a rough planning track can be obtained through evaluation by a static safety boundary in the process of dynamic planning and the accuracy of an evaluation result is low in the related technology mentioned in the background technology center, the application provides a simulation evaluation method for vehicle track planning. Therefore, the technical problems that only a rough planning track can be obtained through evaluation of a static safety boundary in the dynamic planning process and the accuracy of an evaluation result is low in the related technology are solved.
Specifically, fig. 1 is a schematic flowchart of a simulation evaluation method for vehicle trajectory planning according to an embodiment of the present application.
As shown in fig. 1, the simulation evaluation method for vehicle trajectory planning includes the following steps:
in step S101, planning data required for simulation is acquired.
In the actual implementation process, the embodiment of the application can acquire planning data required by simulation, including sensing information and vehicle information.
Optionally, in an embodiment of the present application, the planning data includes at least one of a position of the host vehicle, a lane center line track point, an obstacle vehicle position, a vehicle size, and a safe distance during the lane change.
Specifically, as shown in fig. 2, the embodiment of the application may acquire planning data required for simulation, and establish a corresponding lane coordinate system, where the planning data required for simulation may include positions x and y of the vehicle, track points of a lane center line, and a position x of an obstacle vehicle in a lane changing process c 、y c Vehicle size l c W, safe distance s, etc.
Optionally, in an embodiment of the present application, after acquiring planning data required by the simulation, the method further includes: and performing difference processing on track points of the center line of the lane so as to ensure that the processed uniform difference ensures that the interval between the front point and the rear point meets the preset distance.
As a possible implementation mode, the embodiment of the application can perform difference processing on the acquired lane center track point after acquiring planning data required by simulation, and the uniform difference ensures that the interval between the front point and the rear point meets the preset distance, and if the interval between the front point and the rear point is less than 0.5m, dynamic point scattering is performed subsequently.
It should be noted that the preset distance may be set by a person skilled in the art according to practical situations, and is not limited in particular.
In step S102, based on the planning data, the current position of the vehicle is matched with the optimal trajectory in the previous cycle, a planning starting point is determined, and according to the requirements of the lane change boundary in the horizontal and vertical directions, the center line of the road is used as a reference line, the length of the lane change process is selected according to the speed to perform point scattering, so as to obtain a plurality of groups of local planning trajectories, and re-planning is performed at preset intervals.
In some embodiments, the present application may determine the planning start point by matching the current position of the vehicle with the optimal trajectory of the previous cycle based on the planning data.
In the related technology, the closest point on the optimal track of a period on the distance from the current position can be selected as the starting point of the period plan so as to ensure the smoothness of the whole lane change plan, however, in the actual test, due to the delay of planning and controlling the response of the vehicle on the bottom layer, the selection of the closest point often leads to the delay of the lane change process, the lane change track is too slow, and the distance required by the lane change process is very long; therefore, the target point can be selected by pre-aiming at the speed on the basis of the closest point, so that smoothness can be guaranteed, and the lane change can be safely and quickly carried out.
The pre-aiming distance selection formula can be as follows:
l＝kv+d，
and d is the pre-aiming distance at rest, the length of the vehicle body can be selected during value taking, v is the current vehicle speed, and k is a speed factor.
Further, when performing dynamic point scattering, as shown in fig. 3, in the embodiment of the present application, a center line of a road may be used as a reference line according to a requirement of a lane change boundary in a horizontal direction and a vertical direction, a length of a lane change process is selected according to a speed to perform point scattering, so as to obtain a plurality of groups of local planning tracks, and re-planning is performed at preset time intervals.
The specific implementation can be as follows: as shown in fig. 4, the vertical interval dis of each local path is calculated, where m is the number of local paths and d is the sampling vertical interval.
for(inti＝0；i<m+1；i++)
{
dis＝d*(i-m/2)；
}
The position of the corresponding point of each corresponding local path is calculated according to the position of the lane central line point, wherein p is the position of the corresponding point, different local paths correspond to a series of different track points p along with the circulation according to the difference of dis, the track points are stored, namely, x and y of the track points corresponding to the local tracks, n is the number of the central line track points, and the Center comprises coordinates x and y and a course angle a.
The calculation formula may be as follows:
for(int j＝0；i<n+1；j++)
{
p.x＝Center.at(j).x-dis*cos(Center.at(j).a+M_PI_2)；
p.y＝Center.at(j).y-dis*sin(Center.at(j).a+M_PI_2)；
}
according to the embodiment of the application, multiple groups of local planning tracks can be obtained through the steps, planning is carried out according to preset time, the planning starting point is updated, and cyclic planning is carried out, so that the whole dynamic planning process is obtained.
It should be noted that the preset time period may be set by a person skilled in the art according to actual situations, and is not limited specifically herein.
In step S103, a priority cost, a collision cost, a transition cost, and a maximum lateral acceleration cost of each trajectory are calculated to obtain a total trajectory cost of each trajectory, the trajectory with the minimum total trajectory cost is used as an optimal local path, and an optimal curve obtained by fitting a position point based on the optimal local path in the whole process is compared with a vehicle position in the actual tracking process to obtain an evaluation result.
In the actual execution process, the priority cost, the collision cost, the transition cost and the maximum lateral acceleration cost of each sampling track can be calculated to obtain the total track cost of each sampling track, the sampling track with the minimum track cost is used as the optimal local path, and as shown in fig. 5, the optimal track in the whole process and the vehicle position in the actual tracking process are compared to obtain an evaluation result, whether the deviation range meets the requirement or not is determined, and because the planned starting point is selected from the optimal track in the last frame, the influence of tracking control on the planning can be weakened during the whole lane change evaluation, and the planning module can be evaluated more accurately.
Optionally, in an embodiment of the present application, wherein the calculation formula of the collision cost is:
the calculation formula of the transition cost is as follows:
r 3 ＝f((x t ,y t ),(x t-1 ,y t-1 ))＝(y t -y t-1 )d，
the maximum lateral acceleration cost is calculated by the formula:
r 4 ＝f(k)＝v 2 /r，
wherein r is 2 At a cost of collision, r 3 At a transition cost of r 4 At the maximum lateral acceleration penalty, x t 、y t For the t moment corresponding to the position point coordinate, x, on the local planning track c 、y c Is the position of the obstacle, d c For planning the lateral distance of the trajectory from the obstacle,/ c For planning the longitudinal distance, x, of the trajectory from the obstacle t-1 、y t-1 And (3) corresponding to the coordinates of the position points on the planned track at the time t-1, wherein r is the curvature radius, v is the speed, and d is the track density.
The calculation formula of the collision cost is as follows:
the calculation formula of the transition cost is as follows:
r 3 ＝f((x t ,y t ),(x t-1 ,y t-1 ))＝(y t -y t-1 )d，
the maximum lateral acceleration cost is calculated by the formula:
r 4 ＝f(κ)＝v 2 /r，
wherein r is 2 At a cost of collision, r 3 At a transition cost of r 4 At the maximum lateral acceleration penalty, x t 、y t For the t moment corresponding to the position point coordinate, x, on the local planning track c 、y c Is the position of an obstacle, d c For planning the lateral distance of the trajectory from the obstacle,/ c For planning the longitudinal distance, x, of the trajectory from the obstacle t-1 、y t-1 And (3) corresponding to the coordinates of the position points on the planned track at the time t-1, wherein r is the curvature radius, v is the speed, and d is the track density.
The total cost calculation formula is as follows:
total trajectory cost = t1 × r 1 +t2*r 2 +t3*r 3 +t4*r 4 ，
The method comprises the steps that t1 is a weight coefficient of priority cost, t2 is a weight coefficient of collision cost, t3 is a weight coefficient of transition cost, and t4 is a weight coefficient of maximum lateral acceleration cost.
Optionally, in an embodiment of the present application, comparing an optimal curve obtained based on the position point fitting of the optimal local path in the whole process with a vehicle position in the actual tracking process to obtain an evaluation result, where the evaluation result includes: obtaining a longitudinal deviation and/or curvature index range according to a plurality of reference values obtained by the collision cost and the maximum lateral acceleration cost; and obtaining a result for evaluating whether the lane change meets the requirement by comparing whether the error between the reference value of the middle position of the plurality of reference values and the actual value of the real vehicle meets the index range.
For example, the embodiment of the application can set a fixed period dt =20ms to perform dynamic planning, accumulate and store information of a current position point in a lane changing process, thereby obtaining a reference value of a whole lane changing track, and perform evaluation by comparing the reference value with an actual value.
The evaluation standard can be divided into two indexes: and according to the method in the steps, a series of reference values are obtained by adjusting the values of the collision cost t2 and the maximum transverse acceleration t4, an index range is obtained according to the reference values, and whether the lane change meets the requirement is evaluated by comparing whether the error between the reference value at the middle position and the actual value of the actual vehicle meets the range.
With reference to fig. 2 to fig. 6, the working principle of the simulation evaluation method for vehicle trajectory planning according to the embodiment of the present application is explained in detail by an embodiment.
As shown in fig. 6, the embodiment of the present application may include the following steps:
s601: planning data required for simulation is acquired. In the actual implementation process, the embodiment of the application can acquire planning data required by simulation, including sensing information and vehicle information.
Specifically, as shown in fig. 2, the embodiment of the application may acquire planning data required for simulation, and establish a corresponding lane coordinate system, where the planning data required for simulation may include positions x and y of the vehicle, track points of a lane center line, and a position x of an obstacle vehicle in a lane changing process c 、y c Vehicle size l c W, safe distance s, etc.
As a possible implementation mode, the embodiment of the application can perform difference processing on the acquired lane center track point after acquiring planning data required by simulation, and the uniform difference ensures that the interval between the front point and the rear point meets the preset distance, and if the interval between the front point and the rear point is less than 0.5m, dynamic point scattering is performed subsequently.
It should be noted that the preset distance may be set by a person skilled in the art according to practical situations, and is not limited in particular.
S602: a planning starting point is selected. In some embodiments, the present application may determine the planning start point by matching the current position of the vehicle with the optimal trajectory of the previous cycle based on the planning data.
The method and the device for changing the target point can select the target point by means of speed pre-aiming on the basis of the closest point, can guarantee smoothness, and can safely and quickly change the track.
The pre-aiming distance selection formula can be as follows:
l＝kv+d，
and d is the pre-aiming distance at rest, the length of the vehicle body can be selected during value taking, v is the current vehicle speed, and k is a speed factor.
S603: and (5) dynamically scattering points. When performing dynamic point scattering, as shown in fig. 3, in the embodiment of the present application, a center line of a road may be used as a reference line according to a requirement of a lane change boundary in a horizontal direction and a vertical direction, a length of a lane change process is selected according to a speed to perform point scattering, so as to obtain a plurality of groups of local planning tracks, and re-planning is performed at preset time intervals.
The specific implementation can be as follows: as shown in fig. 4, the vertical interval dis of each local path is calculated, where m is the number of local paths and d is the sampling vertical interval.
for(inti＝0；i<m+1；i++)
{
dis＝d*(i-m/2)；
}
Calculating the position of the corresponding point corresponding to each local path according to the position of the lane Center line point, wherein p is the position of the corresponding point, different local paths correspond to a series of different track points p along with the circulation according to the difference of dis, the track points are stored, namely, the x and y of the track points corresponding to the local paths, n is the number of the Center line track points, and the Center comprises coordinates x and y and a course angle a.
The calculation formula may be as follows:
for(int j＝0；i<n+1；j++)
{
p.x＝Center.at(j).x-dis*cos(Center.at(j).a+M_PI_2)；
p.y＝Center.at(j).y-dis*sin(Center.at(j).a+M_PI_2)；
}
according to the embodiment of the application, multiple groups of local planning tracks can be obtained through the steps, planning is carried out according to preset time, the planning starting point is updated, and cyclic planning is carried out, so that the whole dynamic planning process is obtained.
It should be noted that the preset time period may be set by a person skilled in the art according to actual situations, and is not limited specifically herein.
S604: and selecting an optimal track. In an actual execution process, the priority cost, the collision cost, the transition cost and the maximum lateral acceleration cost of each sampling track can be calculated to obtain the total track cost of each sampling track, and the sampling track with the minimum track cost is used as the optimal local path.
The calculation formula of the collision cost is as follows:
the calculation formula of the transition cost is as follows:
r 3 ＝f((x t ,y t ),(x t-1 ,y t-1 ))＝(y t -y t-1 )d，
the maximum lateral acceleration cost is calculated by the formula:
r 4 ＝f(κ)＝v 2 /r，
wherein r is 2 At a cost of collision, r 3 At a transition cost of r 4 At the maximum lateral acceleration penalty, x t 、y t For the t moment corresponding to the position point coordinate, x, on the local planning track c 、y c Is the position of an obstacle, d c For planning the lateral distance of the trajectory from the obstacle,/ c For planning the longitudinal distance, x, of the trajectory from the obstacle t-1 、y t-1 And (3) corresponding to the coordinates of the position points on the planned track at the time t-1, wherein r is the curvature radius, v is the speed, and d is the track density.
The total cost calculation formula is as follows:
total trajectory cost = t1 × r 1 +t2*r 2 +t3*r 3 +t4*r 4 ，
The method comprises the steps that t1 is a weight coefficient of priority cost, t2 is a weight coefficient of collision cost, t3 is a weight coefficient of transition cost, and t4 is a weight coefficient of maximum lateral acceleration cost.
S605: and (6) evaluation. As shown in fig. 5, in the embodiment of the present application, an evaluation result can be obtained by comparing the optimal trajectory in the whole process with the vehicle position in the actual tracking process, and whether the deviation range meets the requirement is determined.
For example, the embodiment of the application can set a fixed period dt =20ms to perform dynamic planning, accumulate and store information of a current position point in a lane changing process, thereby obtaining a reference value of a whole lane changing track, and perform evaluation by comparing the reference value with an actual value.
The evaluation standard can be divided into two indexes: and according to the method in the steps, a series of reference values are obtained by adjusting the values of the collision cost t2 and the maximum transverse acceleration t4, an index range is obtained according to the reference values, and whether the lane change meets the requirement is evaluated by comparing whether the error between the reference value at the middle position and the actual value of the actual vehicle meets the range.
According to the simulation evaluation method for vehicle track planning provided by the embodiment of the application, re-planning can be performed according to a certain period by a dynamic point-scattering planning method based on planning data, an optimal local path is selected by adding cost, an optimal curve obtained by fitting based on the position point of the optimal local path in the whole process is compared with the position of a vehicle in the actual tracking process, an evaluation result is obtained, and the theoretical precision and the function landing speed of the evaluation can be effectively improved. Therefore, the technical problems that only a rough planning track can be obtained through evaluation of a static safety boundary in the dynamic planning process and the accuracy of an evaluation result is low in the related technology are solved.
Next, a simulation evaluation device for vehicle trajectory planning according to an embodiment of the present application will be described with reference to the drawings.
Fig. 7 is a block diagram schematically illustrating a simulation evaluation device for vehicle trajectory planning according to an embodiment of the present application.
As shown in fig. 7, the simulation evaluation device 10 for vehicle trajectory planning includes: the system comprises an acquisition module 100, a re-planning module 200 and an evaluation module 300.
In particular, the obtaining module 100 is configured to obtain planning data required by the simulation.
And the re-planning module 200 is configured to match the current position of the vehicle with the optimal trajectory of the previous period based on the planning data, determine a planning starting point, select a lane change process length according to the speed by using a road center line as a reference line according to the requirements of lane change boundary in the transverse direction and the longitudinal direction, perform point scattering to obtain multiple groups of local planning trajectories, and perform re-planning at preset time intervals.
The evaluation module 300 is configured to calculate a priority cost, a collision cost, a transition cost, and a maximum lateral acceleration cost of each track, obtain a total track cost of each track, use a track with the minimum total track cost as an optimal local path, and compare an optimal curve obtained by fitting a position point based on the optimal local path in the whole process with a vehicle position in the actual tracking process, so as to obtain an evaluation result.
Optionally, in an embodiment of the present application, the planning data includes at least one of a position of the vehicle, a lane centerline track point, an obstacle vehicle position, a vehicle size, and a safe distance during the lane change.
Optionally, in an embodiment of the present application, the simulation evaluation device 10 for vehicle trajectory planning further includes: and a processing module.
The processing module is used for carrying out difference processing on track points of the center line of the lane so as to enable the processed uniform difference to ensure that the interval between the front point and the rear point meets the preset distance.
Optionally, in an embodiment of the present application, wherein the calculation formula of the collision cost is:
the calculation formula of the transition cost is as follows:
r 3 ＝f((x t ,y t ),(x t-1 ,y t-1 ))＝(y t -y t-1 )d，
the maximum lateral acceleration cost is calculated by the formula:
r 4 ＝f(κ)＝v 2 /r，
wherein r is 2 At a cost of collision, r 3 At a transition cost of r 4 At the maximum lateral acceleration penalty, x t 、y t For the t moment corresponding to the position point coordinate, x, on the local planning track c 、y c Is the position of the obstacle, d c For planning the lateral distance of the trajectory from the obstacle,/ c For planning the longitudinal distance, x, of the trajectory from the obstacle t-1 、y t-1 And (3) corresponding to the coordinates of the position points on the planned track at the time t-1, wherein r is the curvature radius, v is the speed, and d is the track density.
Optionally, in an embodiment of the present application, the evaluation module 300 includes: a calculation unit and an evaluation unit.
And the calculation unit is used for obtaining the index range of the longitudinal deviation and/or the curvature according to a plurality of reference values obtained by the collision cost and the maximum lateral acceleration cost.
And the evaluation unit is used for obtaining a result of evaluating whether the lane change meets the requirement by comparing whether the error between the reference value of the middle position of the plurality of reference values and the actual value of the real vehicle meets the index range.
It should be noted that the explanation of the embodiment of the simulation evaluation method for vehicle trajectory planning is also applicable to the simulation evaluation device for vehicle trajectory planning of the embodiment, and is not repeated herein.
According to the simulation evaluation device for vehicle track planning provided by the embodiment of the application, re-planning can be performed according to a certain period by a dynamic point-scattering planning method based on planning data, an optimal local path is selected by adding cost, an optimal curve obtained by fitting based on the position point of the optimal local path in the whole process is compared with the position of a vehicle in the actual tracking process, an evaluation result is obtained, and the theoretical precision and the function landing speed of the evaluation can be effectively improved. Therefore, the technical problems that only a rough planning track can be obtained through evaluation of a static safety boundary in the dynamic planning process and the accuracy of an evaluation result is low in the related technology are solved.
Fig. 8 is a schematic structural diagram of a vehicle according to an embodiment of the present application. The vehicle may include:
a memory 801, a processor 802, and a computer program stored on the memory 801 and executable on the processor 802.
The processor 802, when executing the program, implements the simulation evaluation method for vehicle trajectory planning provided in the above-described embodiments.
Further, the vehicle further includes:
a communication interface 803 for communicating between the memory 801 and the processor 802.
A memory 801 for storing computer programs operable on the processor 802.
The memory 801 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
If the memory 801, the processor 802 and the communication interface 803 are implemented independently, the communication interface 803, the memory 801 and the processor 802 may be connected to each other via a bus and communicate with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 8, but this is not intended to represent only one bus or type of bus.
Alternatively, in practical implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated into one chip, the memory 801, the processor 802 and the communication interface 803 may communicate with each other through an internal interface.
The processor 802 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.
The present embodiment also provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor, implements the simulation evaluation method for vehicle trajectory planning as above.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement 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 diskette (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). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via 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 should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may also be stored in a computer-readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are exemplary and should not be construed as limiting the present application and that changes, modifications, substitutions and alterations in the above embodiments may be made by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A simulation evaluation method for vehicle trajectory planning is characterized by comprising the following steps:
acquiring planning data required by simulation;
matching the current position of the vehicle with the optimal track of the previous period based on the planning data, determining a planning starting point, taking the road center line as a reference line according to the requirements of the transverse and longitudinal lane change boundary, selecting the length of the lane change process according to the speed to scatter points to obtain a plurality of groups of local planning tracks, and re-planning at intervals of a preset time length; and
calculating the priority cost, the collision cost, the transition cost and the maximum transverse acceleration cost of each track to obtain the total track cost of each track, taking the track with the minimum total track cost as an optimal local path, and comparing an optimal curve obtained by fitting the position points based on the optimal local path in the whole process with the vehicle position in the actual tracking process to obtain an evaluation result.
2. The method of claim 1, wherein the planning data includes at least one of a position of the host vehicle, a lane centerline track point, an obstacle vehicle position, a vehicle size, and a safe distance during the lane change.
3. The method of claim 2, after obtaining planning data required for the simulation, further comprising:
and performing difference processing on the track points of the center line of the lane so as to ensure that the processed uniform difference value ensures that the interval between the front point and the rear point meets the preset distance.
4. The method of claim 1, wherein,
the calculation formula of the collision cost is as follows:
the calculation formula of the transition cost is as follows:
r 3 ＝f((x t ,y t ),(x t-1 ,y t-1 ))＝(y t -y t-1 )d，
the maximum lateral acceleration cost calculation formula is as follows:
r 4 ＝f(κ)＝v 2 /r，
wherein r is 2 At a cost of collision, r 3 At a transition cost of r 4 At the maximum lateral acceleration penalty, x t 、y t For the t moment corresponding to the position point coordinate, x, on the local planning track c 、y c Is the position of an obstacle, d c For planning the lateral distance of the trajectory from the obstacle,/ c For planning the longitudinal distance, x, of the trajectory from the obstacle t-1 、y t-1 And (3) corresponding to the coordinates of the position points on the planned track at the time t-1, wherein r is the curvature radius, v is the speed, and d is the track density.
5. The method according to claim 1, wherein the comparing the optimal curve obtained by fitting the position points based on the optimal local path in the whole process with the vehicle position in the actual tracking process to obtain the evaluation result comprises:
obtaining a longitudinal deviation and/or curvature index range according to a plurality of reference values obtained by the collision cost and the maximum lateral acceleration cost;
and obtaining a result of evaluating whether the lane change meets the requirement by comparing whether the error between the reference value of the middle position of the plurality of reference values and the actual value of the real vehicle meets the index range.
6. A simulation evaluation device for vehicle trajectory planning is characterized by comprising:
the acquisition module is used for acquiring planning data required by simulation;
the re-planning module is used for matching the current position of the vehicle with the optimal track of the previous period based on the planning data, determining a planning starting point, selecting the length of the lane changing process according to the speed by taking the central line of the road as a reference line according to the requirements of the lane changing boundary in the transverse direction and the longitudinal direction for point scattering to obtain a plurality of groups of local planning tracks, and re-planning at intervals of preset time; and
and the evaluation module is used for calculating the priority cost, the collision cost, the transition cost and the maximum transverse acceleration cost of each track to obtain the total track cost of each track, taking the track with the minimum total track cost as an optimal local path, and comparing an optimal curve obtained by fitting the position point based on the optimal local path in the whole process with the vehicle position in the actual tracking process to obtain an evaluation result.
7. The apparatus of claim 6, wherein,
the calculation formula of the collision cost is as follows:
the calculation formula of the transition cost is as follows:
r 3 ＝f((x t ,y t ),(x t-1 ,y t-1 ))＝(y t -y t-1 )d，
the calculation formula of the maximum lateral acceleration cost is as follows:
r 4 ＝f(k)＝v 2 /r，
wherein r is 2 At the cost of collision, r 3 At a transition cost of r 4 At the maximum lateral acceleration penalty, x t 、y t For the time t corresponding to the position point coordinate, x, on the local planning track c 、y c Is the position of an obstacle, d c For planning the lateral distance of the trajectory from the obstacle,/ c For planning the longitudinal distance, x, of the trajectory from the obstacle t-1 、y t-1 And (3) corresponding to the coordinates of the position points on the planned track at the time t-1, wherein r is the curvature radius, v is the speed, and d is the track density.
8. The apparatus of claim 6, wherein the evaluation module:
the calculation unit is used for obtaining the index range of the longitudinal deviation and/or the curvature according to a plurality of reference values obtained by the collision cost and the maximum lateral acceleration cost;
and the evaluation unit is used for obtaining a result of evaluating whether the lane change meets the requirement by comparing whether the error between the reference value of the middle position of the plurality of reference values and the actual value of the real vehicle meets the index range.
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 method for simulation evaluation of vehicle trajectory planning according to any one of claims 1 to 5.
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 simulation evaluation method of a vehicle trajectory plan according to any one of claims 1 to 5.
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