CN114030480B - Unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning - Google Patents
Unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning Download PDFInfo
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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
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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
- 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
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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
- 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
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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
- 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
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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
- B60W60/0015—Planning or execution of driving tasks specially adapted for safety
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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
- 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
Abstract
The application discloses an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, which belongs to the field of automatic driving and comprises the following steps of: calibrating a driving field and an obstacle of the unmanned vehicle, and defining an unmanned vehicle control point and a solution space; the turning process can be divided into a straight driving stage and a turning stage, and the turning process of the unmanned vehicle is divided into three stages; providing a control algorithm; calculating a turning path planning track of the unmanned vehicle by using an Euler method; and carrying out an analog simulation experiment of the turning running path of the unmanned vehicle by using Matlab. According to the application, two function variables are introduced to restrict the rotation angle of the front wheel of the unmanned aerial vehicle; constraining the speed change of the unmanned vehicle in the driving process, and providing an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning; the method can avoid the obstacle by the unmanned vehicle in the automatic driving field, has better expressive force in completing the turning task, and proves the feasibility and the practicability of the method disclosed by the application.
Description
Technical Field
The application belongs to the field of automated driving, and particularly relates to an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning.
Background
The artificial intelligence technology opens up a new era, and automatic driving is the extension and application of artificial intelligence in the automobile industry and the traffic field. Research and development design of intelligent vehicles are actively conducted in a plurality of countries in the world, however, potential safety hazards caused by unmanned vehicles are not small.
In the automatic driving field, the autonomous obstacle avoidance technology of the unmanned vehicle has a large development space, the path planning problem is a most basic and key problem in the obstacle avoidance research of the unmanned vehicle, in the numerous path planning tasks of the unmanned vehicle, the completion of the obstacle avoidance and turning tasks is only a part of the tasks, the obstacle avoidance path planning of the static obstacle with known environmental information according to the difference of geographic data and the obstacle mastered by the unmanned vehicle becomes a research hotspot of each researcher, and particularly, the safety problem brought by the operations such as turning, turning and the like of the unmanned vehicle also excites the thinking of researchers in each relevant field, and certain difficulty still exists in the problems of not pressing lane lines and completing the turning tasks while avoiding the obstacle, so that the problem is solved, so that the unmanned vehicle is enabled to travel to the target field and has great significance to the safety problem of the unmanned vehicle.
To ensure safe driving of the unmanned vehicle, it is particularly important that the safe and gentle track generated by the steering angle and the vehicle speed thereof is particularly important to enable the following of the lane lines and the avoidance of the obstacle. Therefore, in combination with key parameters such as position coordinates, direction angles, curvature change rate, speed, acceleration and time when the unmanned vehicle moves to the point, it is important to predict a safe driving track by using an adaptive vehicle turning control algorithm based on unmanned vehicle obstacle avoidance path planning.
Disclosure of Invention
Aiming at the defects of the prior art: the application provides an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning to realize safe running of the unmanned vehicle for avoiding obstacles in the turning process, and the unmanned vehicle is not pressed against lane lines and the turning task is completed while avoiding the obstacles.
The application provides the following technical scheme:
an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning comprises the following steps:
s1: calibrating a driving field and an obstacle of the unmanned vehicle, and defining an unmanned vehicle control point and a solution space;
s2: dividing the unmanned vehicle turning process into a straight driving stage and a turning stage, and dividing the unmanned vehicle turning process into three stages to simplify the model;
s3: an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning is provided;
s4: combining an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, and calculating a unmanned vehicle turning path planning track by using an Euler method in a straight driving stage and a turning stage of the unmanned vehicle;
s5: and (5) performing an analog simulation experiment.
Further, in S1, the method includes the steps of:
calibrating a unmanned vehicle driving field and an obstacle, measuring the distance of the unmanned vehicle driving field, and determining four coordinate points of the field 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 origin;
selecting a control point, namely taking two front wheels of the unmanned vehicle as a whole, connecting the axes of the two front wheels, taking the central point of the two points as a whole, connecting the axes of the two rear wheels, taking the central point of the two points as a B point, taking the middle point of the symmetrical axis direction of the AB two points as a C point, and taking the C point 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 obstacle and boundary constraint, and dividing the space into three rectangular parts S 1 ,s 2 ,s 3 The solution space S satisfies:
s i ＝{(x,y)|a i <x<b i ,c i <y<d i }。
further: in S2, the following steps are included:
the unmanned vehicle runs at an acceleration of not more than 3m/s during straight running;
the turning process of the unmanned vehicle is regarded as U-shaped, and the unmanned vehicle is divided into I, I and I phases in total in the turning process;
in stage I, the unmanned vehicle runs straight to reach the speed v 0 Beginning proceeding prescriptionRotation of the disk;
in the I stage, the front wheel of the unmanned vehicle runs 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 in I stage, namely the steering wheel is returned, the vehicle body rotates to a specified angle to finish turning.
Further: in S3, the following steps are included:
in the first stage of the unmanned vehicle turning process, the turning track of the unmanned vehicle presents a U shape after the unmanned vehicle turning is simplified, and the change of two angles is considered in the process, wherein delta is calculated in the process fmax Represents the maximum angle delta reached by the deflection angle of the front wheel of the unmanned aerial vehicle f Indicating the variation of the front wheel deflection angle, ψ i (i=1, 2, 3) represents the offset angle of ψ in the i-th stage of the unmanned vehicle, i.e. the offset angle of the vehicle body;
the sine rule can be represented by the following equation:
after being unfolded, the device comprises:
the combination is as follows:
because 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 providedFinally, the method can obtain:
let the angular velocity of the steering wheel be omega D Since the transmission ratio of steering wheel to front wheel angle is 16:1, the angular velocity ω=ω of front wheel oscillation D Because the smaller the speed of the steering wheel is, the larger the radian of the turning is, namely the larger the radius of the curve of the unmanned vehicle in the turning process is, under the precondition that the speed is kept constant, the variable function for controlling the angular speed of the front wheel of the unmanned vehicle is introducedVariable function of controlling acceleration of unmanned vehicle +.>The two functions are used for realizing the autonomous change direction and acceleration of the unmanned vehicle in the turning process to realize path planning to complete the turning task;
obtaining an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, wherein (x n ,y n ) The turn track of the unmanned vehicle is represented:
in the II stage of the unmanned vehicle turning process, since the maximum steering wheel angle is 470 degrees and the transmission ratio of the steering wheel to the front wheel angle is 16:1, the maximum angle of the front wheel angle is 29.375 degrees, and when the front wheel angle reaches the maximum, delta is the maximum angle f ＝δ fmax Then enter the second stage where delta f ＝δ max , The phase II model is as follows:
in a III stage in the unmanned vehicle turning process, course angle offset of the I stage, the II stage and the III stage is defined as psi 1 、ψ 2 、ψ 3 In order to control the unmanned vehicle to vertically drive out after the curve, the steering wheel steering angle offset is controlled to be 180 degrees after the steering wheel is returned in the third stage, namely:
ψ 1 +ψ 2 +ψ 3 ＝180°
the first and third phases can be derived from the constant angular velocity of the front wheel angle and the constant velocity v:
ψ 2 ＝180°-(ψ 1 +ψ 3 )
i.e. guarantee psi during second-stage simulation 2 When the value is reached, the iteration is stopped, a third stage is entered, and a II-stage model is as follows:
the deflection angle of the front wheel of the initial unmanned vehicle in the stage I is delta f0 =0, the yaw angle of the front wheels of the unmanned aerial vehicle in phase II remains δ all the time f1 ＝δ fmax Starting to return to the steering wheel in the III stage, wherein the deflection angle of the front wheel of the unmanned aerial vehicle is represented by delta fmax When the angle is 0, the body of the unmanned vehicle rotates 180 degrees at the end of the III stage, namely the course angleAt this time the steering wheel has been turned back to delta f ＝0。
Further: in S4, the method mainly comprises the following steps:
and combining an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, and solving the driving track of the unmanned vehicle by using an Euler formula to obtain the following steps:
then there is an initial value condition v 0 ＝0，δ f,0 ＝0，x 0 ＝0，y 0 ＝0，Two constraints are:
constraint 1:
constraint 2:
wherein the method comprises the steps ofS is the solution space.
Further: in step S5, in order to use Matlab software to carry out simulation experiments, the simulation is carried out by taking different initial speeds and angular speeds of the unmanned vehicle as characteristics.
Compared with the prior art, the application has the following beneficial results:
the application firstly introduces two function variables based on the traditional bicycle motion algorithm and considering the parameters for controlling the running of the bicycle, including the variable function of the angular speed of the front wheel of the unmanned bicycleAnd a variable function for controlling the acceleration of the unmanned vehicle +.>The application discloses an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, solves the driving track and related parameters of unmanned vehicle turning meeting the conditions of avoiding obstacles and boundary constraint by combining an Euler differential iteration method, and finally uses Matlab software to perform simulation and visualization, wherein the simulation experiment shows that the application is disclosedThe method can effectively complete the avoidance of the obstacle in the known environment and complete the turning task under the condition of not pressing the lane lines, and proves that the application improves the driving safety of the unmanned vehicle in the automatic driving field and the reliability and the practicability in the turning task for avoiding the planning of the obstacle path.
Drawings
FIG. 1 is a flow chart of a variable angle vehicle control turn model of the present disclosure;
FIG. 2 is a schematic diagram illustrating selection of control points;
FIG. 3 is a schematic diagram of a solution space;
FIG. 4 is a scene diagram of a U-shaped turn-around process of the unmanned vehicle;
FIG. 5 is a schematic view of a variable angle vehicle control turn model of an unmanned vehicle;
fig. 6 (a) to 6 (d) are Matlab simulation diagrams.
Detailed Description
The present application will be described in further detail with reference to the accompanying drawings.
Referring to fig. 1, a flow chart of a variable angle vehicle control u-turn model disclosed by the application specifically comprises the following steps:
S1：
calibrating a driving field and an obstacle of the unmanned vehicle, and defining an unmanned vehicle control point and a solution space;
in this step, the following steps are included:
in this step S1, the following specific steps are included:
s100: calibrating a driving place of the unmanned vehicle and an obstacle, ranging the driving place of the unmanned vehicle, taking a control point of the unmanned vehicle as an original point, wherein four coordinate points (x, y) of a place range are respectively (1.5024, -4.9270), (1.5024,26.5489), (-13.5194, 27.6157), (-13.4342, -5.3108), four coordinate points of the obstacle are respectively (-1.5024, -5.0730), (-1.4853,10.9527), (-3.0210,10.7992), (-2.9785, -5.6640), two coordinate points of an outer lane are respectively (-9.9915,11.0347), (-9.9489, -5.4286), two coordinate points of an inner lane are respectively (-6.5063,10.9170), (-6.4637, -5.5463), and the unmanned vehicle runs on the basis, and the obstacle is turned around.
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, taking the center point of the two points as a whole, connecting the axes of the two rear wheels as a whole, taking the center point of the two points as a point B, taking the middle point of the symmetry axis directions of the two points as a point A and a point B, and taking the middle point as a point C as the control point of the unmanned vehicle, as shown in fig. 2. Since the selected control points need to conform to the center point of the conventional bicycle model, it is desirable to select the control points according to the above method.
S102: defining a solution space, referring to fig. 3, the unmanned vehicle safety trajectory is limited in a space set S due to obstacles and boundary constraints, and a blue box represents a boundary, dividing the space into three rectangular parts S 1 ,s 2 ,s 3 Table 1 is the boundary coordinates of the solution space rectangle, and the solution space S satisfies:
s i ＝{(x,y)|a i <x<b i ,c i <y<d i }
wherein a is i ,b i ,c i ,d i Four points representing the ith rectangle, andhas (x) l ,y l )∈S,(x r ,y r )∈S
TABLE 1 boundary coordinates of solution space rectangle
S2：
Dividing the turning process of the unmanned vehicle into a straight running stage and a turning stage, wherein the unmanned vehicle runs at an acceleration of not more than 3m/s in the straight running process, and is U-shaped and divided into stages I, II and III in the turning process of the unmanned vehicle;
in step S2, the following steps are included:
s200: the running process of the unmanned vehicle is divided into a straight running stage and a turning stage. The unmanned vehicle runs at the acceleration of not more than 3m/s in the straight running process, the turning process of the unmanned vehicle is regarded as U-shaped, the unmanned vehicle is divided into I, I and I phases in total in the turning process, as shown in fig. 4, and in the I phase, the unmanned vehicle runs straight to reach the speed v 0 And starting to rotate the steering wheel, driving the front wheel of the unmanned vehicle at a variable angle in the I/I stage until the rotatable angle of the steering wheel of the unmanned vehicle reaches a conditional state, and turning the steering wheel to a specified angle to finish turning when the rotating speed of the steering wheel reaches a limit state in the I/I stage, namely, the steering wheel is turned back, so that the unmanned vehicle realizes a turning process.
S201: consider two variable angle variations. Simplifying a variable-angle vehicle control model, and enabling a turning track of the unmanned vehicle to be U-shaped, wherein two angle changes need to be considered in the process, wherein delta is calculated fmax Represents the maximum angle delta reached by the deflection angle of the front wheel of the unmanned aerial vehicle f Indicating the variation of the front wheel deflection angle, ψ i (i=1, 2, 3) represents the offset angle of ψ in the i-th stage of the unmanned vehicle, that is, the offset angle of the vehicle body.
S3：
The unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning is provided, namely, an angular speed variable function of a front wheel of the unmanned vehicle is added on the basis of a bicycle motion algorithmAnd acceleration variable function->
In specific implementation, in step S3, the method includes the following specific steps:
s300: in the first stage of the unmanned vehicle turning process, the heading angle psi is the angle rotated by the steering wheel based on the control point as shown in fig. 5The degree is controlled, the angular speed of the rotation of the front wheels of the unmanned aerial vehicle is omega, and beta is a slip angle. Set at t 0 The trolley is taken as a starting position at the moment, and the trolley is driven to t in a straight line 1 The point starts to rotate the steering wheel, and the bending speed at the moment is v 0 Because the unmanned vehicle belongs to front wheel steering and rear wheel driving, delta is set in the turning process of the unmanned vehicle r Constant 0.
S301: the conventional bicycle motion model does not consider the controllability of steering wheel rotation and the acceleration of the unmanned vehicle, and on the basis, a function f (t) for controlling the change of the steering wheel angle of the unmanned vehicle along with time is introduced 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 to restrain the speed change of the unmanned vehicle during running.
S302: the sine rule can be represented by the following equation:
the unfolding can be obtained:
simultaneous availability:
s303: if the unmanned vehicle runs at a constant speed in the whole process of turning, 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 as follows:
then there are:
s304: let the angular velocity of the steering wheel be omega D Since the transmission ratio of steering wheel to front wheel angle is 16:1, the angular velocity ω=ω of front wheel oscillation D Because the smaller the speed of the steering wheel is, the larger the radian of the turning is, namely the larger the radius of the curve of the unmanned vehicle in the turning process is, under the precondition that the speed is kept constant, the variable function for controlling the angular speed of the front wheel of the unmanned vehicle is introducedVariable function of controlling acceleration of unmanned vehicle +.>Then there is a variable angle vehicle control turn model:
s305: in the II stage 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 16:1, so that the maximum angle of the rotation angle of the front wheel is 29.375 degrees, namely delta when the rotation angle of the front wheel reaches the maximum f ＝δ fmax Then enter phase II where delta f ＝δ max , The phase II model has:
s306: and in the III stage of turning around and turning around of the unmanned vehicle. Defining a first phase, a second phase and a third phase, wherein the course angle offset of the first phase is phi 1 ,ψ 2 ,ψ 3 In order to control the vertical driving out of the unmanned vehicle after the curve, we have to control the steering wheel to be turned back at the third stage, the course angle offset is just 180 DEG, namely psi 1 +ψ 2 +ψ 3 Because the angular velocity of the front wheel rotation angle is constant and the velocity v is constant in the first stage and the third stage =180°, ψ can be directly calculated by simulation 1 ,ψ 3 And because of the constraint conditions, the psi can be solved 2 ＝180°-(ψ 1 +ψ 3 ) I.e. guarantee psi during second-stage simulation 2 When the value is reached, the iteration is stopped and the phase III is entered. The phase III model has:
s307: delta in OXY coordinate System f Representing the included angle formed by the deflection angle of the front wheel of the unmanned aerial vehicle and the vehicle body, so that the deflection angle of the front wheel of the unmanned aerial vehicle is delta at the beginning of the stage I f0 =0, the yaw angle of the front wheels of the unmanned aerial vehicle in stage II is always kept to beStarting to return to the steering wheel in the III stage according to the variable-angle vehicle turning model, wherein the deflection angle of the front wheels of the unmanned aerial vehicle is represented by delta fmax When the heading angle is 0, the body of the unmanned vehicle rotates 180 DEG at the end of the III stage, namely, the heading angle is +.>At this point the steering wheel has been returned to delta f And (4) the vehicle runs straight at last.
S4：
The method comprises the steps of calculating a turning path planning track of the unmanned vehicle by combining an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning through an Euler method in a straight driving stage and a turning stage of the unmanned vehicle;
in the specific implementation, in step S4, the method includes the following specific steps:
s400: and solving the running track 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. The model of the control turn of the vehicle with the variable angle is obtained by an Euler method:
s401: with initial condition v 0 ＝0，δ f,0 ＝0，x 0 ＝0，y 0 ＝0，Constraint 1:
constraint 2:
wherein, the liquid crystal display device comprises a liquid crystal display device,s is the solution space.
S402: solving in a straight driving stage. Because the curvature constrains the bending speed, when the curvature is not higher than 0.205 and the bending speed is larger than 1.63m/s, the curvature is not higher than 0.21 and the bending speed is larger than 1.585m/s, and finally the minimum bending speed v meeting the curvature is set 0 =1.63 m/s. Let the acceleration of the unmanned vehicle be a=3m/s 2 The vehicle is uniformly accelerated to meet the requirements of not touching the obstacle and the boundary, and the maximum running speed v of the unmanned vehicle 0 = 10.0519m/s, so v 0 The final value range was (1.63,10.0519). If the trolley passes through the obstacle, it is presumed from the figure that the trolley is required to travel straight to the minimum displacement x. The current 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 DEG/s (the maximum radius of the over-bending rate of the trolley is minimum at the moment)>10.0150m, the trolley can wipe the edge to pass through the obstacle. Suppose that when the trolleyThe maximum straight-line driving distance x= 21.6913m of the trolley is calculated to be x= 21.6913m when the minimum bending speed 1.63m/s passes through the straight-line driving road section and the maximum rotation speed 400 DEG/s of the steering wheel is in bending critical contact with the upper boundary of the outer frame A, so that 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 unmanned vehicle body just passes over the obstacle and presses the lane line, so that the unmanned vehicle cannot reach the boundary of the target area from the inner lane, and the possible turning track can only be on the middle lane and the outer lane. Let the direction of steering wheel left by the unmanned vehicle be the positive direction of acceleration, and the direction of steering wheel right be the opposite direction of acceleration, let Δt=0.01, when t= [0,1,2,3,4,5,6,6.18 ]]The locus point is (x) i ,y i )(i＝[1:8]Rounding). When the bending speed v 0 =6m/s, steering wheel angular velocity ω D Partial results of the middle lane trace of the unmanned vehicle at=200 are shown in table 2; when the bending speed v 0 Steering wheel angular velocity ω=6m/s D The partial results of the outer lane trace at=400 are shown in table 3.
TABLE 2 Medium lane trajectory results for unmanned vehicles
TABLE 3 exterior lane trajectory results for unmanned vehicles
S5：
And carrying out an analog simulation experiment of the turning running path of the unmanned vehicle by using Matlab.
In the specific implementation, in step S5, the following specific steps are included:
s500: fig. 6 (a) to 6 (d) show simulation results of the turn track completed by the unmanned vehicle. Wherein 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 the dotted line), the purple frame represents the obstacle, the track line is black, red, green and deep blue, and the blue frame represents the I, I and I stages of the turning and turning stages of the unmanned vehicle in the straight driving stage of the unmanned vehicle respectively. Wherein the solid line represents the trajectory of the unmanned control point travel and the dotted line represents the travel trajectory after the condition that the vehicle body and the obstacle must be spaced 30cm apart.
FIG. 6 (a) is when v 0 ＝6m/s，ω D When 200 is expressed as v, fig. 6 (b) shows a trajectory of the unmanned vehicle from the lane line to the lane target area 0 ＝6m/s，ω D When=400, the turning track of the unmanned vehicle runs from the lane line to the track target area, and fig. 6 (c) shows v 0 ＝3.4m/s，ω D In the limit case when the straight travel distance x=11, =100, the turn-around is completed from the outer lane without touching the boundary, and fig. 6 (d) shows v 0 ＝0.7m/s，ω D The limit case when the straight travel distance x=11, i.e. just pressing the inner lane line, completes the turn from the middle lane, =400.
From the track and the simulation result, it can be seen that for the vehicle control turning model with a variable angle in the method disclosed by the application, under the conditions that the initial speed is 6m/s,6m/s,3.4m/s and 0.7m/s and the angular speed is 200,400,100 and 400 respectively, the unmanned vehicle can effectively avoid the obstacle and complete turning task running without touching the lane line, and obviously, the method disclosed by the application has better expressive force in completing the turning task while the unmanned vehicle avoids the obstacle in the automatic driving field.
Finally, it is pointed out that the above is only a preferred embodiment of the application, it being pointed out that several variants and modifications can be made by a person skilled in the art without departing from the present technical solution, which variants and modifications shall likewise be regarded as falling within the scope of the application as claimed.
Claims (5)
1. An unmanned vehicle self-adaptive turn-around control algorithm based on obstacle avoidance path planning is characterized in that: the method comprises the following steps:
s1: calibrating a driving field and an obstacle of the unmanned vehicle, and defining an unmanned vehicle control point and a solution space;
s2: dividing the unmanned vehicle turning process into a straight driving stage and a turning stage, and dividing the unmanned vehicle turning process into three stages to simplify the model;
s3: an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning is provided;
s4: combining an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, and calculating a unmanned vehicle turning path planning track by using an Euler method in a straight driving stage and a turning stage of the unmanned vehicle;
s5: performing an analog simulation experiment;
in S3, the following steps are included:
in the first stage of the unmanned vehicle turning process, the turning track of the unmanned vehicle presents a U shape after the unmanned vehicle turning is simplified, and the change of two angles is considered in the process, wherein delta is calculated in the process fmax Represents the maximum angle delta reached by the deflection angle of the front wheel of the unmanned aerial vehicle f Indicating the variation of the front wheel deflection angle, ψ i (i=1, 2, 3) represents the offset angle of ψ in the i-th stage of the unmanned vehicle, i.e. the offset angle of the vehicle body;
the sine rule can be represented by the following equation:
after being unfolded, the device comprises:
the combination is as follows:
because 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 providedFinally, the method can obtain:
let the angular velocity of the steering wheel be omega D Since the transmission ratio of steering wheel to front wheel angle is 16:1, the angular velocity ω=ω of front wheel oscillation D Because the smaller the speed of the steering wheel is, the larger the radian of the turning is, namely the larger the radius of the curve of the unmanned vehicle in the turning process is, under the precondition that the speed is kept constant, the variable function for controlling the angular speed of the front wheel of the unmanned vehicle is introducedVariable function of controlling acceleration of unmanned vehicle +.>The two functions are used for realizing the autonomous change direction and acceleration of the unmanned vehicle in the turning process to realize path planning to complete the turning task;
obtaining an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, wherein (x n ,y n ) The turn track of the unmanned vehicle is represented:
in the II stage of the unmanned vehicle turning process, the maximum rotation of the steering wheel is regulatedThe angle is 470 degrees, and the transmission ratio of the steering wheel to the front wheel rotation angle is 16:1, so the maximum angle of the front wheel rotation angle is 29.375 degrees, namely delta when the front wheel rotation angle reaches the maximum f ＝δ fmax Then enter the second stage where delta f ＝δ max ,The phase II model is as follows:
in a III stage in the unmanned vehicle turning process, course angle offset of the I stage, the II stage and the III stage is defined as psi 1 、ψ 2 、ψ 3 In order to control the unmanned vehicle to vertically run out after the curve, the steering wheel steering angle offset is controlled to be 180 exactly after the steering wheel is corrected in the third stage 0 The method comprises the following steps:
ψ 1 +ψ 2 +ψ 3 ＝180°
the first and third phases can be derived from the constant angular velocity of the front wheel angle and the constant velocity v:
ψ 2 ＝180°-(ψ 1 +ψ 3 )
i.e. guarantee psi during second-stage simulation 2 When the value is reached, the iteration is stopped, a third stage is entered, and a II-stage model is as follows:
the deflection angle of the front wheel of the initial unmanned vehicle in the stage I isThe deflection angle of the front wheels of the unmanned aerial vehicle in stage II is always kept as +.>Starting to return to the steering wheel in the III stage, wherein the deflection angle of the front wheel of the unmanned aerial vehicle is represented by delta fmax When the heading angle is 0, the body of the unmanned vehicle rotates 180 DEG at the end of the III stage, namely, the heading angle is +.>At this time the steering wheel has been turned back to delta f ＝0。
2. The unmanned vehicle self-adaptive turn-around control algorithm based on obstacle avoidance path planning according to claim 1, wherein the algorithm is characterized in that: in S1, the following steps are included:
calibrating a unmanned vehicle driving field and an obstacle, measuring the distance of the unmanned vehicle driving field, and determining four coordinate points of the field 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 origin;
selecting a control point, namely taking two front wheels of the unmanned vehicle as a whole, connecting the axes of the two front wheels, taking the central point of the two points as a whole, connecting the axes of the two rear wheels, taking the central point of the two points as a B point, taking the middle point of the symmetrical axis direction of the AB two points as a C point, and taking the C point 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 obstacle and boundary constraint, and dividing the space into three rectangular parts S 1 ,s 2 ,s 3 The solution space S satisfies:
s i ＝{(x,y)|a i <x<b i ,c i <y<d i }。
3. the unmanned vehicle self-adaptive turn-around control algorithm based on obstacle avoidance path planning according to claim 1, wherein the algorithm is characterized in that: in S2, the following steps are included:
the unmanned vehicle runs at an acceleration of not more than 3m/s during straight running;
the turning process of the unmanned vehicle is regarded as U-shaped, and the unmanned vehicle is divided into I, II and III stages in total in the turning process;
in the stage I, the unmanned vehicle runs straight to reach the speed v 0 Starting to rotate the steering wheel;
in the stage II, the front wheel of the unmanned vehicle runs 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 the limit state in stage III, namely, the steering wheel is returned to be normal, the vehicle body rotates to a specified angle to finish turning.
4. The unmanned vehicle self-adaptive turn-around control algorithm based on obstacle avoidance path planning according to claim 1, wherein the algorithm is characterized in that: in S4, the method mainly comprises the following steps:
and combining an unmanned vehicle self-adaptive turning control algorithm based on obstacle avoidance path planning, and solving the driving track of the unmanned vehicle by using an Euler formula to obtain the following steps:
then there is an initial value condition v 0 ＝0，δ f,0 ＝0，x 0 ＝0，y 0 ＝0，Two constraints are:
constraint 1:
constraint 2:
wherein the method comprises the steps ofS is the solution space.
5. The unmanned vehicle self-adaptive turn-around control algorithm based on path planning according to claim 1, wherein the algorithm is characterized in that: in step S5, in order to use Matlab software to carry out simulation experiments, the simulation is carried out by taking different initial speeds and angular speeds of the unmanned vehicle as characteristics.
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