CN111679667A - Path and vehicle speed collaborative planning method for unmanned racing vehicle - Google Patents

Path and vehicle speed collaborative planning method for unmanned racing vehicle Download PDF

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CN111679667A
CN111679667A CN202010428882.7A CN202010428882A CN111679667A CN 111679667 A CN111679667 A CN 111679667A CN 202010428882 A CN202010428882 A CN 202010428882A CN 111679667 A CN111679667 A CN 111679667A
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CN111679667B (en
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庄伟超
李荣粲
刘昊吉
殷国栋
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Southeast University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0217—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with energy consumption, time reduction or distance reduction criteria
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract

The invention relates to a path and vehicle speed collaborative planning method facing an unmanned racing car, which not only considers feasible route and kinematics, but also considers vehicle dynamics in the planning process, plans a feasible path which is theoretically the shortest circle speed through the data of the racing car and a track map, and provides the reference speed and the reference front wheel corner at each position, thereby facilitating the control during the following tracking; the method can be applied to different vehicles and tracks, has better real-time performance, and provides a feasible and controllable fastest route for the racing cars on the tracks.

Description

Path and vehicle speed collaborative planning method for unmanned racing vehicle
Technical Field
The invention relates to a route and vehicle speed collaborative planning method for an unmanned racing vehicle, and belongs to the field of intelligent motion planning.
Background
With the development of the unmanned technology and the deep research of various intelligent algorithms, the application scenes of the unmanned system are more and more abundant. The racing car motion is taken as a platform for the development and innovation of automobile science and technology, and a compass of the automobile industry also follows the trend of the times, so that the intelligent road starts to be developed; the path planning is located at an upper position in the unmanned system and is one of the most important parts of the unmanned system, so the path planning aiming at the track is important for the unmanned event.
As an important technology, intelligent vehicle path planning can be divided into global path planning and local path planning, for which, scholars at home and abroad have already carried out a great deal of research work; from the perspective of the search algorithm of the visibility map, there are mainly Dijkstra algorithm, a algorithm, and RRT algorithm (e.g., j.c. latombe, Robot motion Planning,1991, Dordrecht: Kluwer Academic, ISBN 0-7923-; however, these algorithms are most suitable for flexible and easily controlled mechanical structures (such as mechanical arms and robots) mainly from the viewpoint of node positions, and the planned path is not necessarily suitable for a vehicle in extreme maneuvering.
The side emphasis of the planned path in the track is different from that of the planned path on the daily road; the race track has the characteristics of wide road, single road surface condition and multiple feasible routes, so that the path planning on the race track is not only for finding a feasible route, but also for finding a fastest route; for this purpose, it is necessary to consider the dynamics of the vehicle, that is, besides planning a route, information such as speed and rotation angle of the vehicle at each moment should be planned, so that research work on this is not abundant in China, and people in the same tao and the like at Liaoning university of industry obtain a smooth feasible route by identifying pile barrels and fitting a curve (in the same tao, Ligang, Wangmen, Zhang Xu, unmanned electric racing car route planning algorithm research [ J ]. car practical technology, 2019 (16)). In foreign countries, based on the basis of motion planning, some planning methods under the track environment are proposed, such as jeong hwan Jeon et al (Jeon J H, Cowlagi R V, pets S C, et al, optimal motion planning with the half-car dynamic model for automatic high-speed driving [ J ].2013.) to simplify the vehicle into a point model by transferring the ground-to-tire constraint to the vibration center point in front of the vehicle, and to plan the path in the track by using RRT algorithm; often, the path planning problem is converted into an optimal problem to be solved, and a large number of scholars are studied, such as those of the qian army of the university of the fertile industry (qian army, wubing, fogdrify, huvianlong, the autonomous parking path planning [ J/OL ] based on the hp adaptive pseudo-spectral method and the mechanical engineering declaration) to solve the optimal path problem of autonomous parking through the hp adaptive pseudo-spectral method; step c.pets solves the optimal path problem of single obstacle Avoidance by using a hamilton function (step c.peters. optimal Planning and Control for Hazard availance of Front-wheel stepped Ground Vehicles [ D ]. Massachusetts Institute of technology.2012).
Disclosure of Invention
The invention provides a path and vehicle speed collaborative planning method for an unmanned racing car, which plans a feasible path with theoretically the shortest turn number through the data of the racing car and a track map, and provides the reference speed and the reference front wheel corner at each position, thereby facilitating the control during the subsequent tracking.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a path and vehicle speed collaborative planning method for an unmanned racing vehicle comprises the following steps:
the first step is as follows: obtaining a map file of a lane of a racing car and a starting point state of the racing car, and calculating a discrete vehicle dynamic model under a combination of an offline operation;
the second step is that: calculating the possible pose of the next step according to the determined time step;
the third step: performing collision detection and track constraint detection, and recording paths meeting conditions after removing paths which do not meet the conditions;
the fourth step: planning times;
the fifth step: if the path does not accord with the times planning, the end of the path is taken as a starting point, and the second step is returned to for operation again; if the number of times of planning is met, finding a local optimal path, and detecting the number of turns;
and a sixth step: if one circle is finished, directly outputting the result; if the circle is not finished, the end point of the local optimal path is taken as a starting point, and the second step is returned to for operation again;
as a further preferred aspect of the present invention, the vehicle dynamics model calculation process is divided into two parts, one part is a set of racing constant speed operating points, and the other part is a transfer relationship between the racing operating points, and specifically includes the following steps:
and 11, step 11: loading parameters required for calculating the model, wherein the parameters comprise the mass m of the vehicle and the distance l between the center of mass and the front axlefDistance l of center of mass from rear axlerAnd parameters B, C and D in the tire model defined with magic formulas;
step 12: listing an equation of working points, and obtaining the distance r between the circle center of a turning circle and a front wheel kingpin under the determined speed and the front wheel turning anglefAnd an included angle A between the connecting line of the turning circle center and the front wheel kingpin and the longitudinal plane of the vehicle,
since the constant velocity condition is that the speed and the front wheel steering angle are constant, the longitudinal acceleration and the angular acceleration of the racing car are 0, and the vehicle dynamics equation, the tire model and the geometrical relationship are combined to obtain:
Figure BDA0002499762720000031
Figure BDA0002499762720000032
Figure BDA0002499762720000033
ygc＝(lr+lf-xgc)×tanA
Figure BDA0002499762720000034
Figure BDA0002499762720000035
Figure BDA0002499762720000036
Figure BDA0002499762720000037
Figure BDA0002499762720000038
wherein is the steering wheel angle, αfα for front wheel side slip anglerIs a rear wheel side slip angle lfIs the distance of the center of mass from the front axle,/rIs the distance of the center of mass from the rear axle, xgcIs the longitudinal distance of the centre of steering from the centre of mass, ygcIs the transverse distance of the centre of steering from the centre of mass, FfyTransverse forces acting on the front wheels, Df、Cf、BfAs parameters of a vehicle model under a magic formula, vxIs the longitudinal velocity;
and 13, solving the equation, wherein the solved process is to simulate the process that the vehicle runs at a constant speed and then slowly increases the corner of the front wheel, specifically discretizing the corner increasing process, iterating on the basis of the previous moment, and easily converging to a desired point, wherein according to the equation, the slip angle can be expressed as:
(αf，αr)＝f()
discretizing the wheel angle input can obtain:
(0)＝αf(0)＝αr(0)＝0
(k+1)-(k)＝Δ
(αf(k+1)，αr(k+1))＝K(k+1)，αf(k)，αr(k))
wherein, is the front wheel corner, αfα for front wheel side slip anglerIs a rear wheel side slip angle, k is an index of the count,
performing iterative calculation by using the method, numbering each operating point K, and if the number of the numbers is n, then K (n) ═ vx，，rf，A)；
And step 14, calculating the relation between the working condition points, wherein in the model, if the current working condition point is K (i), the relation between the maximum acceleration and the maximum deceleration of the vehicle along with the change of the speed and the steering wheel angle response condition are as follows:
aacc＝f(vx)；abrake＝g(vx)；Δ＝s(t)
wherein v isxThe speed of the vehicle, the steering wheel angle,
the constraint for the operating point k (j) to which the transition can be made is:
Figure BDA0002499762720000041
Figure BDA0002499762720000042
j-i∈[-s(T)，s(T)]∩[-max，-max]
wherein v isxjLongitudinal velocity, v, at condition point jxiIs the longitudinal velocity at condition point i,jis the front wheel rotating angle of the working condition point of the number j,ithe front wheel corner is the working condition point I;
and calculating the constraint offline, and storing the serial numbers of all the working condition points which can be reached by each working condition point at the next moment by using R: r (n) ═ n1,n2,…,ni)；
As a further preferred aspect of the present invention, the constant speed operating point is a turning radius of the racing car under a condition that a front wheel corner is determined at a constant speed and a position of a turning circle center relative to the car, and if the tire breaks through an adhesion limit in this state, the operating point is removed;
the transfer relationship among the working condition points is obtained according to a vehicle acceleration curve, a vehicle deceleration curve and a vehicle corner response curve, and the speed and the vehicle corner which can be reached by each working condition point at the next moment in a certain unit time are a new working condition point set;
as a further preferred aspect of the present invention, the map file of the racing car lane includes a track boundary, a track safety boundary, and a set of track center points;
the track boundary is the boundary of the track, namely the junction of the pavement with the track adhesion grade and the pavement with other adhesion grades;
the track safety boundary is a reference track boundary in the plan, and the boundary is closer to the center of the track than the actual track boundary, so that a safety margin is provided for the plan.
The track center point set is a set of center points of the track, and in the planning, the position of the vehicle in the track or the completion progress of the vehicle in the current circle is represented by the track center point closest to the vehicle;
as a further preferred embodiment of the present invention, the aforementioned time step is a time interval between the pose distance of the next step and the current pose, and is a fixed value Ts；
The position and posture are the position, course angle, speed, acceleration and father node information of the racing car, if the current information point is
Figure BDA0002499762720000043
The next operating point that can be transitioned is k (n) ═ vx,,rfAnd A), the calculation method of the next information point is as follows:
order to
Figure BDA0002499762720000051
Figure BDA0002499762720000052
Figure BDA0002499762720000053
Figure BDA0002499762720000054
Wherein theta is the course angle change, XjIn order to obtain the abscissa of the last step,
Figure BDA0002499762720000055
for the course angle of the previous step, YjIs the ordinate of the previous step, rfIn order to obtain a turning radius,
Figure BDA0002499762720000056
the course angle in the step;
the collision detection means detecting whether the route touches the obstacle or not, and rejecting a path touching the obstacle;
the track constraint detection means detecting whether a vehicle will be driven away from the track in the step and removing a path beyond the track;
the number of turns detection means that whether one turn of planning is finished is judged according to the position of the vehicle in the track;
as a further preferable aspect of the present invention, in the fourth step, when the last planning in the number planning is performed, the distance to the farthest point is found through the center point of the track, and the path is traced back.
Through the technical scheme, compared with the prior art, the invention has the following beneficial effects:
1. the invention combines the characteristics of the track, improves a two-degree-of-freedom vehicle model, and provides a vehicle model for path planning;
2. after a new vehicle model for path planning is provided, the planning process is discretized, so that the final planning result is the geometry of a group of working condition points, each working condition point comprises the theoretical speed, the theoretical rotation angle and the theoretical course angle of the racing vehicle besides basic coordinate information, and a reference value is provided for vehicle tracking;
3. the planning process of the invention considers the vehicle dynamics, and the finally obtained path can reach the shortest single-turn time;
4. the invention simplifies the dynamic model and has better real-time performance.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a schematic diagram of a preferred embodiment of the present invention;
FIG. 2 is a two degree of freedom vehicle dynamics model, which is a vehicle dynamics model, according to a preferred embodiment of the present invention;
FIG. 3 is a schematic view of a preferred embodiment of the present invention of operating points allowing for transfer;
FIG. 4 is a schematic representation of a racetrack of a preferred embodiment of the invention;
FIG. 5 is a diagram illustrating the preferred embodiment of the present invention for eliminating non-compliant paths, i.e., finding and deleting points beyond the track;
FIG. 6 is a schematic illustration of a preferred embodiment of the present invention after multiple planning;
FIG. 7 is a block diagram of a preferred embodiment of the present invention for times planning, plan NsA feasible path after the step;
fig. 8 is a complete single turn of the planned path for the preferred embodiment of the present invention.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.
The side key points of the planned path in the track are different from those of the planned path on a daily road, and the track has the characteristics of wide road, single road surface condition and multiple feasible routes, so that the path planning on the track is not only for finding a feasible route, but also for finding a fastest route; for this purpose, it is necessary to take into account the dynamics of the vehicle, i.e. in addition to the route planning, information about the speed, the turning angle, etc. of the vehicle at each time should be planned.
Fig. 1 is a schematic diagram illustrating a principle of a collaborative path and vehicle speed planning method for an unmanned racing vehicle according to the present application, and specifically includes the following steps:
the first step is as follows: obtaining a map file of a lane of a racing car and a starting point state of the racing car, and calculating a discrete vehicle dynamic model under a combination line, namely a two-degree-of-freedom vehicle dynamic model;
FIG. 4 illustrates a map file of a race car lane including a race track boundary, a race track safety boundary, and a set of race track center points;
the border of the track is the border of the track, namely the junction of the pavement with the track adhesion grade and the pavement with other adhesion grades;
the track safety boundary is a reference track boundary in the plan, and the boundary is closer to the center of the track than the actual track boundary, so that a safety margin is provided for the plan.
The track center point set is a set of the center points of the tracks, and the position of the vehicle in the track or the completion progress of the vehicle in the circle is represented by the track center point closest to the vehicle in the planning;
the calculation process of the vehicle dynamic model is divided into two parts, one part is a set of constant-speed working condition points of the racing vehicles, the other part is a transfer relation between the working condition points of the racing vehicles, wherein the constant-speed working condition points are turning radii and turning circle centers of the racing vehicles under the working condition that the front wheels turn at a constant speed relative to the positions of the vehicles, and if the tires break through the adhesive force limit under the state, the working condition points are removed;
the transfer relationship among the working condition points is obtained according to a vehicle acceleration curve, a vehicle deceleration curve and a vehicle corner response curve, and the speed and the vehicle corner which can be reached by each working condition point at the next moment in a certain unit time are a new working condition point set;
the method comprises the following specific steps:
and 11, step 11: loading parameters required for calculating the model, wherein the parameters comprise the mass m of the vehicle and the distance l between the center of mass and the front axlefDistance l of center of mass from rear axlerAnd parameters B, C and D in the tire model defined with magic formulas;
step 12: equations listing operating points, at certain speeds andat the front wheel steering angle, a constant velocity operating point has information including: the turning radius and the position of the turning circle center relative to the vehicle, specifically, the distance r from the turning circle center to the front wheel kingpin is obtained as shown in FIG. 2fAnd an included angle A between the connecting line of the turning circle center and the front wheel kingpin and the longitudinal plane of the vehicle,
since the constant velocity condition is that the speed and the front wheel steering angle are constant, the longitudinal acceleration and the angular acceleration of the racing car are 0, and the vehicle dynamics equation, the tire model and the geometrical relationship are combined to obtain:
Figure BDA0002499762720000071
Figure BDA0002499762720000072
Figure BDA0002499762720000073
ygc＝(lr+lf-xgc)×tanA
Figure BDA0002499762720000074
Figure BDA0002499762720000075
Figure BDA0002499762720000076
Figure BDA0002499762720000077
Figure BDA0002499762720000078
wherein is the steering wheel angle, αfα for front wheel side slip anglerIs a rear wheel side slip angle lfIs the distance of the center of mass from the front axle,/rIs the distance of the center of mass from the rear axle, xgcIs the longitudinal distance of the centre of steering from the centre of mass, ygcIs the transverse distance of the centre of steering from the centre of mass, FfyTransverse forces, S, to which the front wheels are subjectedf、Cf、BfAs parameters of a vehicle model under a magic formula, vxIs the longitudinal velocity;
step 13, solving the equation, wherein an inverse trigonometric function is required to be solved when the slip angle is calculated in the equation group in the step 12, so that complex solution is easy to occur in the iterative process, which is not the expected solution; however, the observation of the calculation process shows that the complex solution is originated from Fy/D >1, that is, Fy > D, which means that the adhesion force of the tire is smaller than the lateral force from the practical viewpoint, and the vehicle has the condition of 'drifting' or 'pushing head'; from the iteration angle, the generation source of the complex solution is the too small front wheel side deflection angle during iteration, and then the too large lateral force is calculated; in the algorithm, the solved process is to simulate the process that a vehicle runs at a constant speed and then the corner of a front wheel is slowly increased; specifically, the process of increasing the rotation angle is discretized, iteration is performed on the basis of the previous moment, and convergence to a desired point is easy to achieve, and according to the equation, the slip angle can be expressed as:
(αf，αr)＝f()
discretizing the wheel angle input can obtain:
(0)＝αf(0)＝αr(0)＝0
(k+1)-(k)＝Δ
(αf(k+1)，αr(k+1))＝K(k+1)，αf(k)，αr(k))
wherein, is the front wheel corner, αfα for front wheel side slip anglerIs a rear wheel side slip angle, k is an index of the count,
the method is used for iterative calculation, and the front wheel steering angle is slowly increased at a certain speed. Once a plurality of solutions are presented, it is stated that at that speed and angle of rotation the vehicle has broken through the adhesion limit, at which point the vehicle is able to drive the vehicleIn actual racing, this does not necessarily mean complete runaway, but is not within the consideration of the present path planning; calculating according to the steps, numbering each operating point K, and if the number of the operating points K is n, then K (n) ═ vx，，rf，A)；
And step 14, calculating the relation between the working condition points, wherein in the model, the discontinuous working condition points are ensured to be 'real', namely, the working condition points which can be reached by the vehicle at the next moment are restrained so as to ensure that the step length T (T < T) of the working condition point A in a certain hour is ensureds) Transferring the state to a B working condition point; the constraint should conform to the power curve, deceleration curve and steering wheel angle response curve of the vehicle; if the current working condition point is K (i), the relationship between the maximum acceleration and the maximum deceleration of the vehicle and the change of the speed and the steering wheel angle response condition are as follows:
aacc＝f(vx)；abrake＝g(vx)；Δ＝s(t)
wherein v isxThe speed of the vehicle, the steering wheel angle,
the constraint for the operating point k (j) to which the transition can be made is:
Figure BDA0002499762720000081
Figure BDA0002499762720000082
j-i∈[-s(T)，s(T)]∩[-max，-max]
wherein v isxjLongitudinal velocity, v, at condition point jxiIs the longitudinal velocity at condition point i,jis the front wheel rotating angle of the working condition point of the number j,ithe front wheel corner is the working condition point I;
and calculating the constraint offline, and storing the serial numbers of all the working condition points which can be reached by each working condition point at the next moment by using R: r (n) ═ n1，n2，...，ni) And is shown in fig. 3.
The second step is that: calculating the possible pose of the next step according to the determined time step;
the time step is the time interval between the pose distance of the next step and the current pose, and is a fixed value Ts；
The position and posture are the position, course angle, speed, acceleration and father node information of the racing car, if the current information point is
Figure BDA0002499762720000083
The next operating point that can be transitioned is k (n) ═ vx，，rfAnd A), the calculation method of the next information point is as follows:
order to
Figure BDA0002499762720000091
Figure BDA0002499762720000092
Figure BDA0002499762720000093
Figure BDA0002499762720000094
Wherein theta is the course angle change, XjIn order to obtain the abscissa of the last step,
Figure BDA0002499762720000095
for the course angle of the previous step, YjIs the ordinate of the previous step, rfIn order to obtain a turning radius,
Figure BDA0002499762720000096
the course angle in the step;
the third step: performing collision detection and track constraint detection, and recording paths meeting conditions after removing paths which do not meet the conditions;
the collision detection means detecting whether the route touches the obstacle or not, and rejecting a path touching the obstacle;
as shown in fig. 5, the track constraint detection means detecting whether the vehicle will be driven off the track in this step, and removing the path beyond the track;
the number of turns detection means that whether one turn of planning is finished is judged according to the position of the vehicle in the track;
the fourth step: planning times;
as shown in fig. 6 and 7, the number of times planning is mainly to find a local optimal path (i.e. the fastest path) every certain number of steps, specifically, repeat NsSecondly, after the last planning, finding the farthest point through the center point of the track, and backtracking the path;
the fifth step: if the path does not accord with the times planning, the end of the path is taken as a starting point, and the second step is returned to for operation again; if the number of times of planning is met, finding a local optimal path, and detecting the number of turns;
and a sixth step: if one circle is finished, directly outputting the result to obtain a complete route as shown in figure 8; if the loop is not finished, the local optimal path end point is taken as a starting point, and the second step is returned to for operation again.
The method comprises the steps of firstly, calculating a racing car dynamic model, secondly, combining the racing car dynamic model, proposing a feasible path in a racing track environment, and thirdly, finding an optimal path in the feasible path, a reference speed and a reference corner; through the research contents, the path within the shortest single-circle time can be obtained finally, the reference value containing the position information, the speed and the rotation angle is given, convenience is provided for the tracking control of the racing car, the dynamic model is simplified, and meanwhile the real-time performance is better.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The meaning of "and/or" as used herein is intended to include both the individual components or both.
The term "connected" as used herein may mean either a direct connection between components or an indirect connection between components via other components.
In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.

Claims (6)

1. A path and vehicle speed collaborative planning method for an unmanned racing vehicle is characterized by comprising the following steps: the method comprises the following steps:
the first step is as follows: obtaining a map file of a lane of a racing car and a starting point state of the racing car, and calculating a discrete vehicle dynamic model under a combination of an offline operation;
the second step is that: calculating the possible pose of the next step according to the determined time step;
the third step: performing collision detection and track constraint detection, and recording paths meeting conditions after removing paths which do not meet the conditions;
the fourth step: planning times;
the fifth step: if the path does not accord with the times planning, the end of the path is taken as a starting point, and the second step is returned to for operation again; if the number of times of planning is met, finding a local optimal path, and detecting the number of turns;
and a sixth step: if one circle is finished, directly outputting the result; if the loop is not finished, the local optimal path end point is taken as a starting point, and the second step is returned to for operation again.
2. The unmanned racing car-oriented path and vehicle speed collaborative planning method of claim 1, wherein: the vehicle dynamics model calculation process is divided into two parts, wherein one part is a set of constant-speed working points of the racing car, and the other part is a transfer relation between the working points of the racing car, and the method specifically comprises the following steps:
and 11, step 11: loading parameters required for calculating the model, wherein the parameters comprise the mass m of the vehicle and the distance l between the center of mass and the front axlef、Center of mass distance l from rear axlerAnd parameters B, C and D in the tire model defined with magic formulas;
step 12: listing an equation of working points, and obtaining the distance r between the circle center of a turning circle and a front wheel kingpin under the determined speed and the front wheel turning anglefAnd an included angle A between the connecting line of the turning circle center and the front wheel kingpin and the longitudinal plane of the vehicle,
since the constant velocity condition is that the speed and the front wheel steering angle are constant, the longitudinal acceleration and the angular acceleration of the racing car are 0, and the vehicle dynamics equation, the tire model and the geometrical relationship are combined to obtain:
Figure FDA0002499762710000011
Figure FDA0002499762710000012
Figure FDA0002499762710000013
ygc＝(lr+lf-xgc)×tanA
Figure FDA0002499762710000014
Figure FDA0002499762710000015
Figure FDA0002499762710000016
Figure FDA0002499762710000021
Figure FDA0002499762710000022
wherein is the steering wheel angle, αfα for front wheel side slip anglerIs a rear wheel side slip angle lfIs the distance of the center of mass from the front axle,/rIs the distance of the center of mass from the rear axle, xgcIs the longitudinal distance of the centre of steering from the centre of mass, ygcIs the transverse distance of the centre of steering from the centre of mass, FfyTransverse forces acting on the front wheels, Df、Cf、BfAs parameters of a vehicle model under a magic formula, vxIs the longitudinal velocity;
and 13, solving the equation, wherein the solved process is to simulate the process that the vehicle runs at a constant speed and then slowly increases the corner of the front wheel, specifically discretizing the corner increasing process, iterating on the basis of the previous moment, and easily converging to a desired point, wherein according to the equation, the slip angle can be expressed as:
(αf，αr)＝f()
discretizing the wheel angle input can obtain:
(0)＝αf(0)＝αr(0)＝0
(k+1)-(k)＝Δ
(αf(k+1)，αr(k+1))＝f((k+1)，αf(k)，αr(k))
wherein, is the front wheel corner, αfα for front wheel side slip anglerIs a rear wheel side slip angle, k is an index of the count,
performing iterative calculation by using the method, numbering each operating point K, and if the number of the numbers is n, then K (n) ═ vx，，rf，A)；
And step 14, calculating the relation between the working condition points, wherein in the model, if the current working condition point is K (i), the relation between the maximum acceleration and the maximum deceleration of the vehicle along with the change of the speed and the steering wheel angle response condition are as follows:
aacc＝f(vx)；abrake＝g(vx)；Δ＝s(t)
wherein v isxThe speed of the vehicle, the steering wheel angle,
the constraint for the operating point k (j) to which the transition can be made is:
Figure FDA0002499762710000023
Figure FDA0002499762710000024
j-i∈[-s(T)，s(T)]∩[-max，-max]
wherein v isxjLongitudinal velocity, v, at condition point jxiIs the longitudinal velocity at condition point i,jis the front wheel rotating angle of the working condition point of the number j,ithe front wheel corner is the working condition point I;
and calculating the constraint offline, and storing the serial numbers of all the working condition points which can be reached by each working condition point at the next moment by using R: r (n) ═ n1，n2，...，ni)。
3. The unmanned racing car-oriented path and vehicle speed collaborative planning method according to claim 2, wherein:
the constant-speed working point is the turning radius of the racing car under the working condition of constant-speed fixed front wheel turning angle and the position of the turning circle center relative to the car, and if the tyre breaks through the adhesive force limit under the state, the working point is removed;
the transfer relationship among the working condition points is obtained according to a vehicle acceleration curve, a vehicle deceleration curve and a steering angle response curve, and the speed and the steering angle which can be reached by each working condition point at the next moment in a certain unit time are a new working condition point set.
4. The unmanned racing car-oriented path and vehicle speed collaborative planning method of claim 1, wherein: the map file of the racing lane comprises a racing track boundary, a racing track safety boundary and a racing track center point set;
the track boundary is the boundary of the track, namely the junction of the pavement with the track adhesion grade and the pavement with other adhesion grades;
the track safety boundary is a reference track boundary in the plan, and the boundary is closer to the center of the track than the actual track boundary, so that a safety margin is provided for the plan.
The set of the track center points is a set of center points of the track, and in the planning, the position of the vehicle in the track or the completion progress of the vehicle in the current circle is represented by the track center point closest to the vehicle.
5. The unmanned racing car-oriented path and vehicle speed collaborative planning method of claim 1, wherein:
the time step is the time interval between the pose distance of the next step and the current pose, and is a fixed value Ts；
The position and posture are the position, course angle, speed, acceleration and father node information of the racing car, if the current information point is
Figure FDA0002499762710000031
The next operating point that can be transitioned is k (n) ═ vx，，rfAnd A), the calculation method of the next information point is as follows:
order to
Figure FDA0002499762710000032
Figure FDA0002499762710000033
Figure FDA0002499762710000034
Figure FDA0002499762710000035
Wherein theta is the course angle change, XjIn order to obtain the abscissa of the last step,
Figure FDA0002499762710000036
for the course angle of the previous step, YjIs the ordinate of the previous step, rfIn order to obtain a turning radius,
Figure FDA0002499762710000037
the course angle in the step;
the collision detection means detecting whether the route touches the obstacle or not, and rejecting a path touching the obstacle;
the track constraint detection means detecting whether a vehicle will be driven away from the track in the step and removing a path beyond the track;
the aforementioned lap number detection means that whether a lap planning is completed is judged according to the position of the vehicle in the track.
6. The unmanned racing car-oriented path and vehicle speed collaborative planning method of claim 1, wherein: and when the last planning in the times planning is carried out in the fourth step, the distance to the farthest point is found through the center point of the track, and the path is traced back.
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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112433531A (en) * 2021-01-27 2021-03-02 国汽智控(北京)科技有限公司 Trajectory tracking method and device for automatic driving vehicle and computer equipment
CN113467480A (en) * 2021-08-09 2021-10-01 广东工业大学 Global path planning algorithm for unmanned equation
CN114564012A (en) * 2022-02-16 2022-05-31 华南理工大学 Unmanned racing car path planning method, system, device and storage medium
CN117590856A (en) * 2024-01-18 2024-02-23 北京航空航天大学 Automatic driving method based on single scene and multiple scenes

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106649983A (en) * 2016-11-09 2017-05-10 吉林大学 Vehicle dynamics model modeling method used in unmanned vehicle high-velocity motion planning
CN107315411A (en) * 2017-07-04 2017-11-03 合肥工业大学 A kind of lane-change method for planning track based on automatic driving vehicle under collaborative truck
CN107340772A (en) * 2017-07-11 2017-11-10 清华大学 It is a kind of towards the unpiloted reference locus planing method that personalizes
CN108088456A (en) * 2017-12-21 2018-05-29 北京工业大学 A kind of automatic driving vehicle local paths planning method with time consistency
CN110018689A (en) * 2019-05-15 2019-07-16 福州大学 A kind of more virtual target point overall situation active path planning algorithms based on dynamic window

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106649983A (en) * 2016-11-09 2017-05-10 吉林大学 Vehicle dynamics model modeling method used in unmanned vehicle high-velocity motion planning
CN107315411A (en) * 2017-07-04 2017-11-03 合肥工业大学 A kind of lane-change method for planning track based on automatic driving vehicle under collaborative truck
CN107340772A (en) * 2017-07-11 2017-11-10 清华大学 It is a kind of towards the unpiloted reference locus planing method that personalizes
CN108088456A (en) * 2017-12-21 2018-05-29 北京工业大学 A kind of automatic driving vehicle local paths planning method with time consistency
CN110018689A (en) * 2019-05-15 2019-07-16 福州大学 A kind of more virtual target point overall situation active path planning algorithms based on dynamic window

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112433531A (en) * 2021-01-27 2021-03-02 国汽智控(北京)科技有限公司 Trajectory tracking method and device for automatic driving vehicle and computer equipment
CN113467480A (en) * 2021-08-09 2021-10-01 广东工业大学 Global path planning algorithm for unmanned equation
CN113467480B (en) * 2021-08-09 2024-02-13 广东工业大学 Global path planning algorithm for unmanned equation
CN114564012A (en) * 2022-02-16 2022-05-31 华南理工大学 Unmanned racing car path planning method, system, device and storage medium
CN117590856A (en) * 2024-01-18 2024-02-23 北京航空航天大学 Automatic driving method based on single scene and multiple scenes
CN117590856B (en) * 2024-01-18 2024-03-26 北京航空航天大学 Automatic driving method based on single scene and multiple scenes

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