CN114030480A - Unmanned vehicle self-adaptive head-adaptive control algorithm based on obstacle avoidance path planning - Google Patents

Unmanned vehicle self-adaptive head-adaptive control algorithm based on obstacle avoidance path planning Download PDF

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CN114030480A
CN114030480A CN202111292716.XA CN202111292716A CN114030480A CN 114030480 A CN114030480 A CN 114030480A CN 202111292716 A CN202111292716 A CN 202111292716A CN 114030480 A CN114030480 A CN 114030480A
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unmanned vehicle
stage
turning
angle
path planning
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CN114030480B (en
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闫河
王潇棠
张烨
南浩宇
张洋
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Chongqing Wangshan Industrial Co ltd
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Chongqing University of Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0015—Planning or execution of driving tasks specially adapted for safety
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters

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Abstract

The invention discloses an unmanned vehicle self-adaptive steering control algorithm based on obstacle avoidance path planning, which belongs to the field of automatic driving and comprises the following steps: calibrating an unmanned vehicle driving field and an obstacle, and defining an unmanned vehicle control point and a solution space; the turning process can be divided into a straight line driving stage and a turning stage, and the turning process of the unmanned vehicle is divided into three stages; a control algorithm is proposed; calculating a planned trajectory of the U-turn path of the unmanned vehicle by using an Euler method; a simulation experiment of the turnaround running path of the unmanned vehicle was performed using Matlab. The invention introduces two function variables to restrain the rotation angle of the front wheel of the unmanned vehicle; the speed change of the unmanned vehicle in the driving process is restrained, and an unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning is provided; the method has the advantages that the barrier avoidance can be carried out on an unmanned vehicle in the field of automatic driving, the good expressive force is realized in the process of completing a turn-around task, and the feasibility and the practicability of the method are proved.

Description

Unmanned vehicle self-adaptive head-adaptive control algorithm based on obstacle avoidance path planning
Technical Field
The invention belongs to the field of automatic driving, and particularly relates to an unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning.
Background
The artificial intelligence technology develops a new era, and the automatic driving is the extension and the application of the artificial intelligence in the automobile industry and the traffic field. Research and development design of intelligent vehicles is actively carried out in many countries in the world today, however, the potential safety hazard brought by unmanned vehicles is not inconsiderable.
In the field of automatic driving, the autonomous obstacle avoidance technology of the unmanned vehicle has a large development space, and the path planning problem is one of the most basic and key problems in the research of obstacle avoidance of the unmanned vehicle, among the numerous path planning tasks of the unmanned vehicle, the tasks of obstacle avoidance and turning around are only part of the tasks, and according to the difference between the geographical data mastered by the unmanned vehicle and the obstacles, obstacle avoidance path planning for static obstacles with known environmental information has become a research hotspot of researchers, especially, the safety problem brought about when the unmanned vehicle performs operations such as turning, turning around and the like has motivated the thinking of researchers in various related fields, the problem that the lane line is not pressed and the turn-around task is still finished while the obstacle is avoided still has certain difficulty, therefore, solving the problem makes the unmanned vehicle drive to the target field has great significance for the safety problem and the path planning problem of the unmanned vehicle.
To ensure safe driving of the unmanned vehicle, enabling the following of the lane line and the avoidance of obstacles, a safe and gentle driving trajectory generated by its steering angle and vehicle speed is particularly important. Therefore, it is very important to use an adaptive vehicle turning control algorithm based on unmanned vehicle obstacle avoidance path planning to predict a safe driving track by combining key parameters such as position coordinates, direction angles, curvatures, curvature change rates, speeds, accelerations and time when the unmanned vehicle moves to the point.
Disclosure of Invention
Aiming at the defects of the prior art: the invention provides an unmanned vehicle self-adaptive heading control algorithm based on obstacle avoidance path planning to realize safe driving of an unmanned vehicle for avoiding obstacles in the process of turning around, and solves the problems that the obstacle avoidance is realized, the lane line is not pressed and the turning task is finished at the same time.
The invention provides the following technical scheme:
an unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning comprises the following steps:
s1: calibrating an unmanned vehicle driving field and an obstacle, and defining an unmanned vehicle control point and a solution space;
s2: dividing the turning process of the unmanned vehicle into a straight-line driving stage and a turning stage, and dividing the turning process of the unmanned vehicle into three stages to simplify the model;
s3: providing an unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning;
s4: combining an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, and calculating a turning path planning track of the unmanned vehicle in a straight line driving stage and a turning stage of the unmanned vehicle by using an Euler method;
s5: and carrying out simulation experiments.
Further, in S1, the method includes the following steps:
calibrating an unmanned vehicle driving site and an obstacle, measuring distance of the unmanned vehicle driving site, and determining four coordinate points of a site range, four coordinate points of the obstacle, two coordinate points of an outer lane line and two coordinate points of an inner lane line by taking a control point of the unmanned vehicle as an original point;
selecting a control point, regarding two front wheels of the unmanned vehicle as a whole, connecting the axes of the two front wheels, then taking the central points of the two points to be positioned at a point A, regarding the two rear wheels as a whole, connecting the axes of the two rear wheels, taking the central points of the two points to be positioned at a point B, taking the middle point in the direction of the symmetric axis of the two points AB, and setting the middle point as a point C to be used as the control point of the unmanned vehicle;
defining a solution space, and limiting the safety track of the unmanned vehicle in a space set according to the barriers and boundary constraintsIn S, the space is divided into three rectangular sections S1,s2,s3The solution space S satisfies:
Figure BDA0003335198840000021
si＝{(x,y)|ai<x<bi,ci<y<di}。
further: in S2, the method includes the steps of:
during the straight line driving process, the unmanned vehicle drives at the acceleration not exceeding 3 m/s;
the turning process of the unmanned vehicle is regarded as U type, and totally divided into stages I, I and I in the turning process;
at stage I, the unmanned vehicle travels straight to reach the speed v0Starting to rotate the steering wheel;
at the stage I, the front wheels of the unmanned vehicle run at a variable angle until the rotatable angle of the steering wheel of the unmanned vehicle reaches a condition state;
when the rotating speed of the steering wheel reaches the limit state at the stage of I/I, the steering wheel is aligned, and the vehicle body rotates to the specified angle to complete the turning.
Further: in S3, the method includes the steps of:
in the stage I of the turning process of the unmanned vehicle, the turning track of the unmanned vehicle is in a U shape after the turning running of the unmanned vehicle is simplified, and the change of two angles is considered in the process, wherein deltafmaxRepresenting the maximum angle, delta, attained by the lean angle of the front wheels of the unmanned vehiclefIndicating the amount of change, ψ, in the toe angle of the front wheeli(i ═ 1,2,3) represents the offset angle of ψ of the unmanned vehicle at the i-th stage, i.e., the offset angle of the vehicle body;
from the sine rule, the following equation can be given:
Figure BDA0003335198840000031
after deployment there are:
Figure BDA0003335198840000032
after the combination, the following steps are carried out:
Figure BDA0003335198840000033
since the unmanned vehicle runs at a constant speed in the whole process of turning around, the direction change rate of the unmanned vehicle is equal to the angular speed of the vehicle, and the angular speed of the vehicle is
Figure BDA0003335198840000034
Finally, the following can be obtained:
Figure BDA0003335198840000035
let the angular velocity of the steering wheel be ωDSince the transmission ratio of the steering wheel to the front wheel rotation angle is 16:1, the angular velocity ω of the front wheel swing is ωD16/180 phi, the smaller the speed of the steering wheel is, the larger the radian of the turn is, namely the larger the radius of the curve of the unmanned vehicle in the turning process is, the variable function for controlling the angular speed of the front wheel of the unmanned vehicle is introduced
Figure BDA0003335198840000036
Variable function for controlling acceleration of unmanned vehicle
Figure BDA0003335198840000037
The two functions are used for realizing that the unmanned vehicle autonomously changes the direction and the acceleration in the turning process to realize path planning and complete the turning task;
obtaining an unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning, wherein (x)n,yn) Represents the turning track of the unmanned vehicle:
Figure BDA0003335198840000038
in the phase II of the turning process of the unmanned vehicle, the maximum rotation angle of the steering wheel is 470 degrees, the transmission ratio of the steering wheel to the rotation angle of the front wheel is 16:1, so that the maximum rotation angle of the front wheel is 29.375 degrees, and delta is the maximum rotation angle of the front wheelf＝δfmaxThen a second phase is entered, at which point deltaf＝δmax,
Figure BDA0003335198840000039
Figure BDA00033351988400000310
The phase II model is:
Figure BDA0003335198840000041
in the third stage of the unmanned vehicle turning process, the heading angle offset of the first stage, the second stage and the third stage is defined to be psi1、ψ2、ψ3In order to control the unmanned vehicle to vertically drive out after the curve, the course angle offset of the steering wheel is controlled to be just 180 degrees after the steering wheel returns to the positive state in the third stage, namely:
ψ1+ψ2+ψ3＝180°
the first and third phases, due to the constant angular velocity of the front wheel turning angle, and the constant velocity v, can yield:
ψ2＝180°-(ψ1+ψ3)
i.e. ensuring psi during the second stage simulation2When the value is reached, stopping iteration, and entering a third stage, wherein the model of the second stage is as follows:
Figure BDA0003335198840000042
the deflection angle of the front wheels of the unmanned vehicle at the beginning of the I stage is delta f00, at stage II, the slip angle of the front wheel of the unmanned vehicle beginsFinal hold is deltaf1＝δfmaxStarting to return to the steering wheel in stage III, the slip angle of the front wheels of the unmanned vehicle is deltafmaxBecomes 0, and the body of the unmanned vehicle rotates 180 degrees at the end of the III phase, namely the course angle
Figure BDA0003335198840000043
At this time, the steering wheel has already returned to normal, deltaf＝0。
Further: in S4, the method mainly includes the steps of:
combining an unmanned vehicle self-adaptive head control algorithm based on obstacle avoidance path planning, and solving the driving track of the unmanned vehicle by using an Euler formula to obtain:
Figure BDA0003335198840000051
then there is an initial value condition v0＝0，δf,0＝0，x0＝0，y0＝0，
Figure BDA0003335198840000052
Two constraints are:
constraint 1:
Figure BDA0003335198840000053
constraint 2:
Figure BDA0003335198840000054
wherein
Figure BDA0003335198840000055
And S is a solution space.
Further: in step S5, in order to perform simulation experiments using Matlab software, simulation is performed using different initial speeds and angular speeds of the unmanned vehicle as characteristics.
Compared with the prior art, the invention has the following beneficial results:
the invention firstly introduces two function variables including a variable function of the angular velocity of the front wheel of the unmanned vehicle on the basis of the traditional bicycle motion algorithm and in consideration of the parameters for controlling the vehicle to run
Figure BDA0003335198840000056
And a variable function for controlling acceleration of the unmanned vehicle
Figure BDA0003335198840000057
The invention discloses an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, which is combined with an Euler differential iteration method to solve the driving track and related parameters of unmanned vehicle turning meeting obstacle avoidance and boundary constraint conditions, and finally Matlab software is used for simulation and visualization.
Drawings
FIG. 1 is a flow chart of a variable angle vehicle control turn-around model disclosed herein;
FIG. 2 is a schematic diagram of control point selection;
FIG. 3 is a schematic illustration of a solution space;
FIG. 4 is a view of a U-shaped U-turn process scene of the unmanned vehicle;
FIG. 5 is a schematic view of a vehicle control turning model of the unmanned vehicle with variable angles;
fig. 6(a) to 6(d) are Matlab simulation diagrams.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
Fig. 1 is a flowchart of a variable angle vehicle control turning model disclosed in the present invention, which specifically includes the following steps:
S1：
calibrating an unmanned vehicle driving field and an obstacle, and defining an unmanned vehicle control point and a solution space;
in this step, the following steps are included:
in step S1, the method includes the following steps:
s100: the method comprises the steps of calibrating an unmanned vehicle driving site and an obstacle, measuring distance of the unmanned vehicle driving site, taking a control point of the unmanned vehicle as an origin, setting four coordinate points (x and y) of a site range as (1.5024, -4.9270), (1.5024,26.5489), (-13.5194, 27.6157), (-13.4342, -5.3108), setting four coordinate points of the obstacle as (-1.5024, -5.0730), (-1.4853,10.9527), (-3.0210,10.7992), (-2.9785, -5.6640), setting two coordinate points of an outer lane line as (-9.9915,11.0347), (-9.9489, -5.4286), setting two coordinate points of an inner lane line as (-6.5063,10.9170), (-6.4637, -5.5463), driving the unmanned vehicle on the basis, avoiding the obstacle and completing a turn-around task.
S101: selecting an unmanned vehicle control point, regarding two front wheels of the unmanned vehicle as a whole, connecting the axes of the two front wheels, then taking the central points of the two points to be positioned at the point A, regarding the two rear wheels as a whole, connecting the axes of the two rear wheels, taking the central points of the two points to be positioned at the point B, taking the middle point of the symmetrical axes of the two points of the point A and the point B, and setting the middle point as the point C to be used as the control point of the unmanned vehicle, as shown in fig. 2. Since the selected control point needs to be in accordance with the center point of the conventional bicycle model, it is in accordance with the above method to select the control point.
S102: defining a solution space, referring to fig. 3, the unmanned vehicle safety trajectory is confined to a set of spaces S due to obstacles and boundary constraints, the blue boxes represent boundaries, and the space is divided into three rectangular portions S1,s2,s3Table 1 is the boundary coordinates of the solution space rectangle, and the solution space S satisfies:
Figure BDA0003335198840000061
si＝{(x,y)|ai<x<bi,ci<y<di}
wherein, ai,bi,ci,diFour points of the ith rectangle are represented, an
Figure BDA0003335198840000074
Is (x)l,yl)∈S,(xr,yr)∈S
TABLE 1 boundary coordinates of solution space rectangles
Figure BDA0003335198840000071
S2：
Dividing the process of turning around the unmanned vehicle into a straight line driving stage and a turning stage, driving the unmanned vehicle at an acceleration not more than 3m/s in the straight line driving process, and dividing the turning process of the unmanned vehicle into a U-shaped stage I, a stage II and a stage III;
in step S2, the method includes the following steps:
s200: the driving process of the unmanned vehicle is divided into a straight line driving stage and a turning stage. During the straight line driving process, the unmanned vehicle drives at an acceleration not exceeding 3m/s, the turning process of the unmanned vehicle is regarded as U-shaped, and the turning process is totally divided into stages I, I and I in the turning process, as shown in fig. 4, at stage I, the unmanned vehicle linearly drives to reach the speed v0The method comprises the following steps that rotation of a steering wheel is started, at the stage I, front wheels of the unmanned vehicle run at a variable angle until the rotatable angle of the steering wheel of the unmanned vehicle reaches a condition state, and when the rotating speed of the steering wheel reaches a limit state at the stage I, the steering wheel is aligned, and the vehicle body rotates to a specified angle to complete turning, so that the unmanned vehicle realizes a turning process.
S201: two variable angle variations are considered. The U-shaped turning track of the unmanned vehicle after the variable-angle vehicle control model is simplified needs to consider the change of two angles in the process, wherein deltafmaxRepresenting the maximum angle, delta, attained by the lean angle of the front wheels of the unmanned vehiclefIndicating the amount of change, ψ, in the toe angle of the front wheeli(i-1, 2,3) representsAnd the offset angle of psi of the i-th stage of the unmanned vehicle is the offset angle of the vehicle body.
S3：
An unmanned vehicle self-adaptive head control algorithm based on obstacle avoidance path planning is provided, namely, an angular speed variable function of the front wheel of the unmanned vehicle is added on the basis of a single vehicle motion algorithm
Figure BDA0003335198840000072
And variable function of acceleration
Figure BDA0003335198840000073
In a specific implementation, step S3 includes the following specific steps:
s300: in phase I of the u-turn process of the unmanned vehicle, based on the control point, as shown in fig. 5, the heading angle ψ is controlled by the angle of rotation of the steering wheel, and the angular velocity of rotation of the front wheels of the unmanned vehicle is ω and β is the slip angle. Is provided at t0At the moment, the trolley is at the initial position, and the trolley is driven to t straight line1The point begins to turn the steering wheel at a kick-in speed v0Because the unmanned vehicle belongs to front wheel steering and rear wheel driving, delta is set in the turning process of the unmanned vehiclerIs always 0.
S301: the traditional bicycle motion model does not consider the controllability of the rotation of a steering wheel and the acceleration of the unmanned vehicle, and on the basis of the model, a function f (t) for controlling the change of the angle of the steering wheel of the unmanned vehicle along with time is introduced so as to restrain the rotation angle of the front wheel of the unmanned vehicle, and a controllable function g (t) for controlling the change of the acceleration of the unmanned vehicle along with time is introduced so as to restrain the speed change of the unmanned vehicle during the driving process.
S302: from the sine rule, the following equation can be given:
Figure BDA0003335198840000081
unfolding to obtain:
Figure BDA0003335198840000082
the following can be obtained in a simultaneous manner:
Figure BDA0003335198840000083
s303: if the unmanned vehicle runs at a constant speed in the whole process of turning around, then the direction change rate of the unmanned vehicle is equal to the angular velocity of the vehicle, and then the angular velocity of the vehicle has:
Figure BDA0003335198840000084
then there are:
Figure BDA0003335198840000085
s304: let the angular velocity of the steering wheel be ωDSince the transmission ratio of the steering wheel to the front wheel rotation angle is 16:1, the angular velocity ω of the front wheel swing is ωD16/180 phi, the smaller the speed of the steering wheel is, the larger the radian of the turn is, namely the larger the radius of the curve of the unmanned vehicle in the turning process is, the variable function for controlling the angular speed of the front wheel of the unmanned vehicle is introduced
Figure BDA0003335198840000086
Variable function for controlling acceleration of unmanned vehicle
Figure BDA0003335198840000087
Then there is a variable angle vehicle control turn around model:
Figure BDA0003335198840000088
s305: in the second phase of turning around, the maximum rotation angle of the steering wheel is 470 degrees, and the transmission ratio of the steering wheel to the rotation angle of the front wheel is 161, so that the maximum angle of rotation of the front wheel is 29.375 DEG, delta being the maximum angle of rotation of the front wheelf＝δfmaxThen proceed to stage II where deltaf＝δmax,
Figure BDA0003335198840000091
Figure BDA0003335198840000092
Then the phase II model has:
Figure BDA0003335198840000093
s306: in phase III in the u-turn of the drone. Defining a phase I, a phase II, and a phase III course angle offset of psi1,ψ2,ψ3To control the unmanned vehicle to drive out vertically after a curve, we must control the heading angle offset to be exactly 180 °, ψ, after the steering wheel is turned back to the positive in the third stage1+ψ2+ψ3Since the angular velocity of the front wheel angle is constant and the velocity v is constant in the first stage and the third stage at 180 °, ψ can be directly calculated by simulation1,ψ3And psi can be solved according to the constraint conditions2＝180°-(ψ1+ψ3) I.e. ensuring psi during the second stage simulation2When the value is reached, the iteration is stopped and stage III is entered. Then the phase III model has:
Figure BDA0003335198840000094
s307: delta in the OXY coordinate systemfThe included angle formed by the deflection angle of the front wheel of the unmanned vehicle and the vehicle body is shown, so that the deflection angle of the front wheel of the unmanned vehicle is delta at the beginning of the I stagef0When the deflection angle of the front wheel of the unmanned vehicle is kept to be 0 in the II stage
Figure BDA0003335198840000096
According to the angle-variable vehicle turningThe model starts to return to the steering wheel in the stage III, and the deflection angle of the front wheels of the unmanned vehicle is deltafmaxBecomes 0, and the body of the unmanned vehicle rotates 180 degrees at the end of the III phase, namely the course angle
Figure BDA0003335198840000095
At this time the steering wheel has returned to positive deltafAnd (5) when the vehicle runs in a straight line, the vehicle can run in a straight line.
S4：
Calculating the planned trajectory of the turning path of the unmanned vehicle in a straight line driving stage and a turning stage of the unmanned vehicle by using an Euler method in combination with an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning;
in a specific implementation, step S4 includes the following specific steps:
s400: and solving the driving track of the unmanned vehicle by using an Euler method in combination with an unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning. The model of the vehicle control turning round with variable angles is obtained by the Euler method:
Figure BDA0003335198840000101
s401: with an initial condition v0＝0，δf,0＝0，x0＝0，y0＝0，
Figure BDA0003335198840000102
Constraint 1:
Figure BDA0003335198840000103
constraint 2:
Figure BDA0003335198840000104
wherein the content of the first and second substances,
Figure BDA0003335198840000105
s is solutionA space.
S402: and solving a straight line driving stage. Because the curvature constrains the in-bending speed, when the curvature is not higher than 0.205 corresponding to the in-bending speed being more than 1.63m/s, and the curvature is not higher than 0.21 corresponding to the in-bending speed being more than 1.585m/s, the minimum in-bending speed v satisfying the curvature is finally set01.63 m/s. Let the acceleration of the unmanned vehicle be a ═ 3m/s2Making uniform acceleration movement, meeting the requirements of not touching obstacles and boundaries and ensuring the maximum running speed v of the unmanned vehicle010.0519m/s, so v0The final value range is (1.63, 10.0519). If the vehicle is to be driven past an obstacle, it is assumed from the figure that it is to be ensured that the vehicle is first driven straight to a minimum displacement x. The x is calculated by substituting the minimum bending speed of the trolley of 1.63m/s and the maximum rotating speed of the steering wheel of 400 degrees/s (the maximum radius of the over-bending rate of the trolley is minimum at the moment)>10.0150m, the trolley can scrape the edge and pass through the obstacle. Assuming that when the trolley passes through a straight line driving road section at the minimum in-bending speed of 1.63m/s, the maximum rotation speed of the steering wheel of 400 degrees/s in-bending critical contact with the upper boundary of the outer frame A, the x is 21.6913m at the moment, namely the maximum straight line driving distance x of the trolley is 21.6913m, so the final value range of x is (10.0150,21.6913)
S403: the lane near the starting point of the unmanned vehicle is called an inner lane, the left boundary near the boundary is called an outer lane, and the middle lane is called a middle lane. Under the limit condition, the left boundary of the body of the unmanned vehicle just crosses the obstacle and also presses the lane line, so that the unmanned vehicle cannot reach the boundary of the target area from the inner lane, and the turning track can only be in the middle lane and the outer lane. Let Δ t be 0.01, and when t is [0,1,2,3,4,5,6,6.18 ], let us say that the direction in which the unmanned vehicle turns the steering wheel to the left is the positive direction of the acceleration, and the direction to the right is the negative direction of the acceleration, and let us say that t is 0,1,2,3,4,5,6,6.18]Then, its tracing point is (x)i,yi)(i＝[1:8]Rounding). When bending speed v06m/s, steering wheel angular velocity ωDPartial results for the middle lane trace of the unmanned vehicle at 200 are shown in table 2; when bending speed v06m/s, steering wheel angular velocity ωDPartial results for the outer lane trace at 400 hours are shown in table 3.
TABLE 2 center lane trace results for unmanned vehicles
Figure BDA0003335198840000111
TABLE 3 unmanned vehicle outside lane trajectory results
Figure BDA0003335198840000112
Figure BDA0003335198840000121
S5：
A simulation experiment of the turnaround running path of the unmanned vehicle was performed using Matlab.
In a specific implementation, step S5 includes the following specific steps:
s500: as shown in fig. 6(a) to 6(d), the simulation results of the turning trajectory of the unmanned vehicle are shown. The blue frame represents the turning boundary of the unmanned vehicle, the orange and yellow lines represent the outer lane line and the inner lane line (both represent dotted lines), the purple frame represents obstacles, the track lines are composed of black, red, green and dark blue, and respectively represent the stages of straight driving of the unmanned vehicle and the stages of I, I and I of the turning stage. The solid line represents the travel locus of the unmanned vehicle control point, and the dotted line represents the travel locus after the condition that the vehicle body and the obstacle must be spaced by 30cm is added.
FIG. 6(a) is a graph showing that when v0＝6m/s，ωDWhen the turnaround trajectory of the unmanned vehicle travels from the center lane line to the target lane area at 200, fig. 6(b) shows the trajectory when v is0＝6m/s，ωDWhen the turnaround trajectory of the unmanned vehicle is 400 hours, the trajectory line of the turnaround trajectory of the unmanned vehicle traveling from the center lane to the target lane area is shown in fig. 6(c) as v0＝3.4m/s，ωDWhen the straight-line travel distance x is equal to 11, the turnaround is completed from the outer lane without touching the boundary, and v is shown in fig. 6(d)0＝0.7m/s，ωD400, limit of the straight-line travel distance x of 11, i.e. just pressing the inner lane line fromAnd the middle lane completes turning around.
From the above-mentioned track and simulation results, it can be seen that, for the variable-angle vehicle control turning model of the method disclosed by the invention, under the conditions that the initial speeds are respectively 6m/s, 6m/s, 3.4m/s and 0.7m/s and the angular speeds are respectively 200,400,100 and 400, the unmanned vehicle can effectively avoid obstacles and can complete the turning task without touching lane lines, obviously, the method disclosed by the invention can complete the turning task with better expressive force while avoiding obstacles by the unmanned vehicle in the field of automatic driving.
Finally, it should be noted that the above is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, many variations and modifications may be made without departing from the technical solution, and the technical solution of the variations and modifications should also be considered as falling within the scope of the claims of the present application.

Claims (6)

1. An unmanned vehicle self-adaptive head control algorithm based on obstacle avoidance path planning is characterized in that: the method comprises the following steps:
s1: calibrating an unmanned vehicle driving field and an obstacle, and defining an unmanned vehicle control point and a solution space;
s2: dividing the turning process of the unmanned vehicle into a straight-line driving stage and a turning stage, and dividing the turning process of the unmanned vehicle into three stages to simplify the model;
s3: providing an unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning;
s4: combining an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, and calculating a turning path planning track of the unmanned vehicle in a straight line driving stage and a turning stage of the unmanned vehicle by using an Euler method;
s5: and carrying out simulation experiments.
2. The unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning as claimed in claim 1, wherein: in S1, the method includes the steps of:
calibrating an unmanned vehicle driving site and an obstacle, measuring distance of the unmanned vehicle driving site, and determining four coordinate points of a site range, four coordinate points of the obstacle, two coordinate points of an outer lane line and two coordinate points of an inner lane line by taking a control point of the unmanned vehicle as an original point;
selecting a control point, regarding two front wheels of the unmanned vehicle as a whole, connecting the axes of the two front wheels, then taking the central points of the two points to be positioned at a point A, regarding the two rear wheels as a whole, connecting the axes of the two rear wheels, taking the central points of the two points to be positioned at a point B, taking the middle point in the direction of the symmetric axis of the two points AB, and setting the middle point as a point C to be used as the control point of the unmanned vehicle;
defining a solution space, limiting the safety track of the unmanned vehicle in a space set S according to the obstacles and boundary constraints, and dividing the space into three rectangular parts S1,s2,s3The solution space S satisfies:
Figure FDA0003335198830000011
si＝{(x,y)|ai<x<bi,ci<y<di}。
3. the unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning as claimed in claim 1, wherein: in S2, the method includes the steps of:
during the straight line driving process, the unmanned vehicle drives at the acceleration not exceeding 3 m/s;
the turning process of the unmanned vehicle is regarded as U type, and totally divided into stages I, I and I in the turning process;
at stage I, the unmanned vehicle travels straight to reach the speed v0Starting to rotate the steering wheel;
at the stage I, the front wheels of the unmanned vehicle run at a variable angle until the rotatable angle of the steering wheel of the unmanned vehicle reaches a condition state;
when the rotating speed of the steering wheel reaches the limit state at the stage of I/I, the steering wheel is aligned, and the vehicle body rotates to the specified angle to complete the turning.
4. The unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning as claimed in claim 1, wherein: in S3, the method includes the steps of:
in the stage I of the turning process of the unmanned vehicle, the turning track of the unmanned vehicle is in a U shape after the turning running of the unmanned vehicle is simplified, and the change of two angles is considered in the process, wherein deltafmaxRepresenting the maximum angle, delta, attained by the lean angle of the front wheels of the unmanned vehiclefIndicating the amount of change, ψ, in the toe angle of the front wheeli(i ═ 1,2,3) represents the offset angle of ψ of the unmanned vehicle at the i-th stage, i.e., the offset angle of the vehicle body;
from the sine rule, the following equation can be given:
Figure FDA0003335198830000021
after deployment there are:
Figure FDA0003335198830000022
after the combination, the following steps are carried out:
Figure FDA0003335198830000023
since the unmanned vehicle runs at a constant speed in the whole process of turning around, the direction change rate of the unmanned vehicle is equal to the angular speed of the vehicle, and the angular speed of the vehicle is
Figure FDA0003335198830000024
Finally, the following can be obtained:
Figure FDA0003335198830000025
let the angular velocity of the steering wheel be ωDSince the transmission ratio of the steering wheel to the front wheel rotation angle is 16:1, the angular velocity ω of the front wheel swing is ωD16/180 phi, the smaller the speed of the steering wheel is, the larger the radian of the turn is, namely the larger the radius of the curve of the unmanned vehicle in the turning process is, the variable function for controlling the angular speed of the front wheel of the unmanned vehicle is introduced
Figure FDA0003335198830000026
Variable function for controlling acceleration of unmanned vehicle
Figure FDA0003335198830000027
The two functions are used for realizing that the unmanned vehicle autonomously changes the direction and the acceleration in the turning process to realize path planning and complete the turning task;
obtaining an unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning, wherein (x)n,yn) Represents the turning track of the unmanned vehicle:
Figure FDA0003335198830000031
in the phase II of the turning process of the unmanned vehicle, the maximum rotation angle of the steering wheel is 470 degrees, the transmission ratio of the steering wheel to the rotation angle of the front wheel is 16:1, so that the maximum rotation angle of the front wheel is 29.375 degrees, and delta is the maximum rotation angle of the front wheelf＝δfmaxA second phase is entered, at which point
Figure FDA0003335198830000032
The phase II model is:
Figure FDA0003335198830000033
in the III stage of the turning process of the unmanned vehicle, course angles of the I stage, the II stage and the III stage are definedOffset is psi1、ψ2、ψ3In order to control the unmanned vehicle to vertically drive out after the curve, the course angle offset of the steering wheel is controlled to be just 180 degrees after the steering wheel returns to the positive state in the third stage, namely:
ψ1+ψ2+ψ3＝180°
the first and third phases, due to the constant angular velocity of the front wheel turning angle, and the constant velocity v, can yield:
ψ2＝180°-(ψ1+ψ3)
i.e. ensuring psi during the second stage simulation2When the value is reached, stopping iteration, and entering a third stage, wherein the model of the second stage is as follows:
Figure FDA0003335198830000041
at the beginning of stage I the slip angle of the front wheels of the unmanned vehicle is
Figure FDA0003335198830000042
The slip angle of the front wheels of the unmanned vehicle is always kept at
Figure FDA0003335198830000043
Starting to return to the steering wheel in stage III, the slip angle of the front wheels of the unmanned vehicle is deltafmaxBecomes 0, and the body of the unmanned vehicle rotates 180 degrees at the end of the III phase, namely the course angle
Figure FDA0003335198830000044
At this time, the steering wheel has already returned to normal, deltaf＝0。
5. The unmanned vehicle adaptive head control algorithm based on obstacle avoidance path planning as claimed in claim 1, wherein: in S4, the method mainly includes the steps of:
combining an unmanned vehicle self-adaptive head control algorithm based on obstacle avoidance path planning, and solving the driving track of the unmanned vehicle by using an Euler formula to obtain:
Figure FDA0003335198830000045
then there is an initial value condition v0＝0，δf,0＝0，x0＝0，y0＝0，
Figure FDA0003335198830000046
Two constraints are:
constraint 1:
Figure FDA0003335198830000047
constraint 2:
Figure FDA0003335198830000051
wherein
Figure FDA0003335198830000052
And S is a solution space.
6. The unmanned vehicle adaptive steering control algorithm based on path planning as claimed in claim 1, wherein: in step S5, in order to perform simulation experiments using Matlab software, simulation is performed using different initial speeds and angular speeds of the unmanned vehicle as characteristics.
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