CN108536149A - A kind of automatic driving vehicle avoidance obstacle device and control method based on the paths Dubins - Google Patents
A kind of automatic driving vehicle avoidance obstacle device and control method based on the paths Dubins Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
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- 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Abstract
The present invention provides a kind of automatic driving vehicle avoidance obstacle device and control method based on the paths Dubins, device includes that camera outside A columns and a camera being arranged on the right side of automatic driving vehicle outside A columns and a laser radar for being set to automatic driving vehicle roof is arranged on the left of the automatic driving vehicle；Method is：Radar carries out positioning-speed-measuring to the barrier entered within the scope of camera head monitor；The barrier sequence that will be collided with intelligent vehicle based on obstacle avoidance algorithm determination；Intelligent vehicle is planned again according to the new current avoidance path of barrier sequence pair, to complete avoidance operation；Camera is set in the middle part of two A columns of automatic driving vehicle by the present invention, efficiently solves the problems, such as automatic driving vehicle blind area, while improving perfect, the order of accuarcy of acquisition information；Unmanned middle different barrier is judged into algorithm using different avoidances, improves accuracy and the precision of automatic driving vehicle avoidance.
Description
Technical field
The invention belongs to automotive field, be related to a kind of automatic driving vehicle avoidance obstacle device based on the paths Dubins and
Control method.
Background technology
With automotive engineering continuous development with it is perfect, unmanned technology is seasonable and gives birth to, unmanned to rely on artificial intelligence
Energy, vision calculating, radar, monitoring device and global positioning system cooperative cooperating allow computer can be in nobody class active
Operation under, operate motor vehicles to automatic safe.Its cardinal principle is by vehicle-mounted sensor-based system perception road environment, certainly
Dynamic planning travelling line simultaneously controls vehicle arrival predeterminated target；Ambient enviroment is perceived by onboard sensor simultaneously, and according to sense
Know obtained road, vehicle location and obstacle information, control steering and the speed of vehicle, to enable the vehicle to safety,
Reliably travelled on road.
However unmanned technology at this stage the problem of being primarily present this following two aspect：1. there is identification in sensor
Obstacle, radar, camera are influenced the perception of ambient enviroment by weather, environment, and sensor technology is not perfect and often exists
Dead angle is monitored, obstacle information nearby can not be accurately obtained；2. intelligent vehicle processor cannot as human brain correctly recognize vehicle,
The behavior of pedestrian has cognitive defect；3. people do not trust for unmanned technology.
The first two main problem, which has resulted in automatic driving vehicle, can not accurately carry out avoidance, also exacerbate third and ask
The deterioration of topic, and also there is no solve the problems, such as automatic driving vehicle avoidance well for many patents at this stage.
A kind of laser barrier-avoiding method of pilotless automobile is disclosed application No. is 201610782894.3 patent and is
System, the system include Driving control module, laser assembly, automatic obstacle avoiding module, wherein, Driving control module is by independently keeping away
Barrier module instructs to control the traveling of pilotless automobile, and laser emitter outwardly sends laser and receives extraneous barrier
Reflected laser, the automatic obstacle avoiding module that laser signal is sent to pilotless automobile carry out avoidance, which can
By receiving to realize the automatic obstacle-avoiding of pilotless automobile by the laser signal of external reflection come disturbance in judgement object；Application No. is
201610749321.0 patent discloses a kind of barrier-avoiding method and system of pilotless automobile, which includes information collection
Module, message processing module, traveling control module, information acquisition module is using laser ranging array before pilotless automobile
Stereo scene information collection is carried out on into direction, message processing module is according to collected stereo scene information, to unmanned
The front of automobile carries out barrier point detecting, determines avoidance path, and control pilotless automobile is according to the avoidance path into every trade
It sails；But although above two patent can accurately avoid static-obstacle thing, dynamic barrier cannot be played well
Avoidance acts on.
Invention content
The technical problem to be solved by the present invention is to overcome problem of the existing technology, provides one kind and be based on
The automatic driving vehicle avoidance obstacle device and control method in the paths Dubins.
Described device can predict other vehicles, pedestrian driving path, and itself vehicle is controlled according to its driving path
Transport condition, the present invention can improve the safety of automatic driving vehicle driving, and specific purposes are：
1. automatic driving vehicle is helped to carry out the identification of barrier, the integrity of unmanned technology is improved, solves existing rank
Section a series of problems caused by sensor technology is not perfect；
2. solving the problems, such as the cognitive defect of automatic driving vehicle processor, the path anticipation for carrying out moving obstacle is helped,
To reduce the generation of unmanned traffic accident.
The present invention adopts the following technical scheme that realization：
The present invention provides a kind of automatic driving vehicle avoidance obstacle device based on the paths Dubins, which is characterized in that
It is arranged on the right side of automatic driving vehicle outside A columns including a camera being arranged on the left of the automatic driving vehicle outside A columns, one
The camera in portion and a laser radar for being set to automatic driving vehicle roof, two cameras are in the A columns of place
Portion and in the same horizontal line, the barycenter of laser radar and automatic driving vehicle is on same straight line, and the straight line and water
Plane is perpendicular, and two cameras and laser radar are connect with the ECU of automatic driving vehicle.
The automatic driving vehicle avoidance obstacle method based on the paths Dubins that the present invention also provides a kind of, feature exist
In being as follows：
Step (1) radar carries out positioning-speed-measuring to the barrier entered within the scope of camera head monitor；
The barrier sequence that step (2) will be collided based on obstacle avoidance algorithm determination with intelligent vehicle；
Step (3) intelligent vehicle is planned again according to the new current avoidance path of barrier sequence pair, to complete avoidance
Operation；
Wherein,
Step (1) detailed process is：
The laser radar detection that automatic driving vehicle passes through two cameras and roof in the middle part of the A columns of the left and right sides
Obstacle information under residing multi obstacles environment；
Establish automatic driving vehicle search model, it is assumed that the region of search of automatic driving vehicle be radius be R, angle of release is 2 θ
Region, θ determines by camera visibility angle, and R is determined by camera head monitor distance；
Laser radar detects the number of the barrier of the region of search in automatic driving vehicle, the traveling of barrier speed
Degree, the position of barrier and the distance between automatic driving vehicle barycenter and barrier observation point, and exercise data is transmitted
Into automatic driving vehicle central processing unit；
Step (2) detailed process is：
Range of definition circle is using automatic driving vehicle barycenter as the center of circle, with R1For the circle of radius, and the range circle should surround
Automatic driving vehicle contour line and make l ' >=l, the shortest distances of the l ' between range circle and automatic driving vehicle contour line, l
Most short safe distance between two vehicles；
After barrier enters region of search, then avoidance judgement is proceeded by；
Automatic driving vehicle is typically under multi obstacles environment in the process of moving, in order to more accurately execute avoidance
Operation, is divided into two kinds by the barrier that automatic driving vehicle encounters：Stationary obstruction and moving obstacle；
Judgment method is：Laser radar obtains speed, the position letter of the barrier in radar monitoring range every 0.05s
Breath, if the speed of each moment barrier is 0, which is stationary obstruction, if depositing the speed of at a time barrier
Degree is not 0, then the barrier is moving obstacle；
Assuming that automatic driving vehicle moves in a straight line, two dimensional surface xoy is built, is original with the barycenter of automatic driving vehicle
Point, using automatic driving vehicle direction of advance as y-axis, y-axis is rotated in a clockwise direction the positive direction that 90 degree are x-axis；
(1) avoidance judgement is carried out to stationary obstruction：
Because the speed of stationary obstruction is 0, i.e., stationary obstruction observation point coordinates is constant, if stationary obstruction observation point
Coordinate is (x0,y0), so the shortest distance of the automatic driving vehicle and stationary obstruction that move in a straight line is exactly stationary obstruction
Length of perpendicular of the observation point to y-axis；Understand that the length of perpendicular is exactly the absolute value of stationary obstruction observation point abscissa, i.e., | x0
|；When | x0| it is more than range radius of circle R1When, it can determine whether that the stationary obstruction will not collide with automatic driving vehicle；When | x0|
Less than or equal to range radius of circle R1When, judge that the stationary obstruction can collide with automatic driving vehicle, will determine that can send out
The stationary obstruction of raw collision is added in barrier sequence；
(2) avoidance judgement is carried out to moving obstacle：
First, trajectory predictions are carried out to the moving obstacle observation locus of points using Kalman filtering algorithm, concrete operations are：
A, system prediction equation is built
Current time is indicated with k-1, if the k-1 moment moving obstacle observation points that lidar measurement arrives are in two dimensional surface
The position of xoy is (x (k-1), y (k-1))；If the k-1 moment moving obstacle observation points that lidar measurement arrives are flat in two dimension
The speed of face xoy is (vx(k-1),vy(k-1))；If the time interval at each moment is sampling interval duration t, t=is taken
0.15s；If Qx(k-1),Qy(k-1) be mean value be zero, variance σ0 22 of white Gaussian noise Q (k-1) of the k-1 moment just
Hand over vector, Qx(k-1),Qy(k-1) any time is mutual indepedent, and e is that natural constant is also referred to as Euler's numbers, then according to physical motion public affairs
It is as follows to obtain position and speed equation of the k moment moving obstacle observation points in two dimensional surface xoy for formula：
In formula,For the predicted value of k moment moving obstacle observation points position in two dimensional surface xoy,For the predicted value of k moment moving obstacle observation points speed in two dimensional surface xoy；
Arrangement obtains system prediction equation：
Wherein, it enables
X (k-1)=(x (k-1) vx(k-1)y(k-1)vy(k-1))T
For predicted value of the k moment moving obstacle observation points in two dimensional surface xoy, X (k-1) is to transport at the k-1 moment
Dynamic lidar measurement value of the barrier observation point in two dimensional surface xoy；
It enables
Then the system prediction equation being simplified：
B, system measuring equation is built
Similarly, if the k moment moving obstacle observation points that arrive of lidar measurement in the position of two dimensional surface xoy are (x
(k),y(k))；If the k moment moving obstacle observation points that lidar measurement arrives are (v in the speed of two dimensional surface xoyx(k),
vy(k))；If Rx(k),Ry(k) be mean value be zero, variance σ1 2The k moment white Gaussian noise R (k) 2 orthogonal vectors, Rx
(k),Ry(k) any time is mutual indepedent, then k moment moving obstacle observation points are in two dimensional surface xoy internal coordinates and speed
Measuring equation is：
Wherein, it enables
X (k)=(x (k) vx(k)y(k)vy(k))T
X (k) is lidar measurement value of the k moment moving obstacle observation points in two dimensional surface xoy；
The system measuring equation being simplified：
Y (k)=HX (k)+IR (k)
C, the error covariance P at k moment is calculatedk
D, kalman gain K is calculatedk, and obtain predicted value of the k+1 moment moving obstacle observation points under two dimensional surface
Kk=PkHT(HPkHT+R(k))-1
E, predicted value of the k+1 moment moving obstacle observation points in two dimensional surface xoy is calculatedAnd laser radar
Covariance matrix P between measured value X (k+1)k+1, prepare for next recursion
Pk+1=(I-KkH)Pk
Predicted position of each moment moving obstacle observation point at two dimensional surface xoy can be obtained as a result, by each
Predicted position line can be obtained barrier observation point position prediction track.
Secondly, moving obstacle observation point under synchronization is calculated according to distance between two points formula at two dimensional surface xoy
The distance between automatic driving vehicle barycenter L, if L≤R1, then prove that moving obstacle can be in the moment and automatic driving car
It collides, will determine that the moving obstacle that can be collided is added to barrier sequence；
Step (3) detailed process is：
(1) may usually exist in automatic driving vehicle barrier sequence multiple may touch with automatic driving vehicle
The barrier hit, when there are when multiple barriers, being pressed in automatic driving vehicle barrier sequence and automatic driving vehicle distance
Distance carries out avoidance successively, and the nearest barrier of automatic driving vehicle of first adjusting the distance carries out avoidance, and so on, stationary obstruction
With moving obstacle avoidance processing is carried out by respective obstacle avoidance algorithm；
(2) stationary obstruction obstacle avoidance algorithm is as follows：
Since the stationary obstruction position in barrier sequence is constant, directly according to monitoring the case where to automatic driving vehicle
The direction of travel speed is adjusted, you can effective avoidance；
I.e. so that automatic driving vehicle steering wheel to stationary obstruction negative direction turn over certain angle θ can effective avoidance, θ
Meet：
(3) moving obstacle obstacle avoidance algorithm is as follows：
It is the R using moving obstacle barycenter as the center of circle to define obstacle circle2For the circle of radius, and obstacle circle answers envelope of motion
Barrier contour line；
A, the position of starting circle Cs, failure circle D and target circle Cf are determined：
On two dimensional surface trajectory diagram, T is taken1=TtThe range circle at-nt moment is starting circle Cs, takes TtThe obstacle at moment is justified
Justify D as failure, takes T1=TtRange circle when the+nt moment successfully avoids obstacle circle D and returns to original route is target circle
Cf；
Tt=L/vx
vx=| v-vz|
Wherein, TtCorresponding time, v when bumping against with automatic driving vehicle for moving obstaclexFor moving obstacle and nobody
The relative velocity between vehicle is driven, v is the speed of automatic driving vehicle, vzFor the speed of moving obstacle, in order to make nobody drive
Sailing vehicle has enough reflecting times, takes n >=3 and is positive integer；
B, the paths Dubins between starting circle Cs and failure circle D are determined
Justify the travel direction of D according to failure, you can obtain two effective paths Dubins, i.e. two automatic driving vehicles
Range circle is driven towards the paths Dubins for justifying D tangency locations with failure, respectively SD-1 and SD-2 by the positions starting circle Cs；
C, the paths Dubins between failure circle D and target circle Cf are determined
The paths Dubins are done to failure circle D and target circle Cf, similarly, 2 the effective paths Dubins, i.e., two can be obtained
Automatic driving vehicle range circle is by driving towards the paths Dubins of the positions target circle Cf, respectively Df- with failure circle D tangency locations
1 and Df-2；
The path that path SD-1 and path Df-1 is constituted is known as path SD1F,
The path that path SD-2 and path Df-2 is constituted is known as path SD2f；
D, the paths Dubins between starting circle Cs and target circle Cf are determined
The travel direction for justifying D according to obstacle is analyzed it is found that path SD2F justifies D with obstacle
Travel direction generate interference, i.e., justify the close path SD of travel direction of D with obstacle2F, path SD1F and obstacle
The travel direction of circle D justifies the separate path SD of the travel direction of D without interference with obstacle1F, can obtain effective avoidance path is
SD1f。
Compared with prior art the beneficial effects of the invention are as follows：
A kind of automatic driving vehicle avoidance obstacle method based on the paths Dubins provided by the invention, by by barrier
Classify, generates interference using whether obstacle avoidance algorithm disturbance in judgement object can move with automatic driving vehicle, interference will be generated
Barrier is added into barrier sequence, and plans driving path again.Following advantageous effect can be reached：
1. acquisition camera is set in the middle part of two A columns of automatic driving vehicle, efficiently solves automatic driving vehicle and regard
The problem of wild blind area, while improving perfect, the order of accuarcy of acquisition information；
2. the barrier encountered in will be unmanned is classified, different barriers is judged using different avoidances
Algorithm, and the obstacle information under residing obstacle environment is acquired in real time, and real-time update barrier sequence, improve nobody
Drive accuracy and the precision of vehicle obstacle-avoidance；
3. the control system is observed moving obstacle using Kalman filtering algorithm the anticipation of movement locus,
Path planning is carried out using the paths Dubins, barrier behavior anticipation accuracy is carried out by in-vehicle processor compared to previous
Higher, improves the safety of automatic driving vehicle driving, while can effectively avoid and hinder because automatic driving vehicle processor identifies
Traffic accident caused by hindering；
Description of the drawings
The present invention will be further described below with reference to the drawings：
Fig. 1 is that a kind of structure of the automatic driving vehicle avoidance obstacle device based on the paths Dubins of the present invention is shown
It is intended to；
Fig. 2 is a kind of flow of the automatic driving vehicle avoidance obstacle method based on the paths Dubins of the present invention
Figure；
Fig. 3 is automatic driving vehicle search model；
Fig. 4 is Dubins path schematic diagrams；
In figure：1, automatic driving vehicle roof, 2, laser radar, 3, A columns, 4, camera.
Specific implementation mode
The present invention is explained in detail below in conjunction with the accompanying drawings：
A kind of automatic driving vehicle avoidance obstacle device based on the paths Dubins, which is characterized in that be arranged including one
4, camera shootings being arranged on the right side of automatic driving vehicle outside A columns 3 of camera on the left of the automatic driving vehicle outside A columns 3
First 4 and a laser radar 2 for being set to automatic driving vehicle roof 1, the middle part of A columns 3 where two cameras 4 are in and
In same horizontal line, laser radar 2 and the barycenter of automatic driving vehicle are on same straight line, and the straight line and horizontal plane
It is perpendicular.As shown in Figure 1；
The camera 4 is set to outside automatic driving vehicle on left and right A columns 3, is advantageously accounted for automatic driving vehicle and is deposited
Blind area problem；
A kind of automatic driving vehicle avoidance obstacle method based on the paths Dubins, which is characterized in that be as follows：
Step (1) radar carries out positioning-speed-measuring to the barrier entered within the scope of camera head monitor；
The barrier sequence that step (2) will be collided based on obstacle avoidance algorithm determination with intelligent vehicle；
Step (3) intelligent vehicle is planned again according to the new current avoidance path of barrier sequence pair, to complete avoidance
Operation；
Avoidance obstacle method flow diagram is as shown in Figure 2.
Wherein, step (1) detailed process is：
The laser radar 2 that automatic driving vehicle passes through two cameras 4 and roof 1 positioned at 3 middle part of left and right sides A columns
Obstacle information under the residing multi obstacles environment of detection；
Establish automatic driving vehicle search model, it is assumed that the region of search of automatic driving vehicle be radius be R, angle of release is 2 θ
Region, θ determines by camera visibility angle, and R is determined by camera head monitor distance.Automatic driving vehicle search model such as Fig. 3
It is shown；
Laser radar 2 detects the number of the barrier of the region of search in automatic driving vehicle, the traveling of barrier
Speed, the position of barrier and the distance between automatic driving vehicle barycenter and barrier observation point, and exercise data is passed
It send into automatic driving vehicle central processing unit；
Step (2) detailed process is：
Range of definition circle is using automatic driving vehicle barycenter as the center of circle, with R1For the circle of radius, and the range circle should surround
Automatic driving vehicle contour line and make l ' >=l, the shortest distances of the l ' between range circle and automatic driving vehicle contour line, l
Most short safe distance between two vehicles；
After barrier enters region of search, then avoidance judgement is proceeded by；
Automatic driving vehicle is typically under multi obstacles environment in the process of moving, in order to more accurately execute avoidance
Operation, is divided into two kinds by the barrier that automatic driving vehicle encounters：Stationary obstruction and moving obstacle；
Judgment method is：Laser radar obtains speed, the position letter of the barrier in radar monitoring range every 0.05s
Breath, if the speed of each moment barrier is 0, which is stationary obstruction, if depositing the speed of at a time barrier
Degree is not 0, then the barrier is moving obstacle；
Assuming that automatic driving vehicle moves in a straight line, two dimensional surface xoy is built, is original with the barycenter of automatic driving vehicle
Point, using automatic driving vehicle direction of advance as y-axis, y-axis is rotated in a clockwise direction the positive direction that 90 degree are x-axis；
(1) avoidance judgement is carried out to stationary obstruction：
Because the speed of stationary obstruction is 0, i.e., stationary obstruction observation point coordinates is constant, if stationary obstruction observation point
Coordinate is (x0,y0), so the shortest distance of the automatic driving vehicle and stationary obstruction that move in a straight line is exactly stationary obstruction
Length of perpendicular of the observation point to y-axis；Understand that the length of perpendicular is exactly the absolute value of stationary obstruction observation point abscissa, i.e., | x0
|；When | x0| it is more than range radius of circle R1When, it can determine whether that the stationary obstruction will not collide with automatic driving vehicle；When | x0|
Less than or equal to range radius of circle R1When, judge that the stationary obstruction can collide with automatic driving vehicle, will determine that can send out
The stationary obstruction of raw collision is added in barrier sequence；
(2) avoidance judgement is carried out to moving obstacle：
First, trajectory predictions are carried out to the moving obstacle observation locus of points using Kalman filtering algorithm, concrete operations are：
A, system prediction equation is built
Current time is indicated with k-1, if the k-1 moment moving obstacle observation points that lidar measurement arrives are in two dimensional surface
The position of xoy is (x (k-1), y (k-1))；If the k-1 moment moving obstacle observation points that lidar measurement arrives are flat in two dimension
The speed of face xoy is (vx(k-1),vy(k-1))；If the time interval at each moment is sampling interval duration t, t=is taken
0.15s；If Qx(k-1),Qy(k-1) be mean value be zero, variance σ0 22 of white Gaussian noise Q (k-1) of the k-1 moment just
Hand over vector, Qx(k-1),Qy(k-1) any time is mutual indepedent, and e is that natural constant is also referred to as Euler's numbers, then according to physical motion public affairs
It is as follows to obtain position and speed equation of the k moment moving obstacle observation points in two dimensional surface xoy for formula：
In formula,For the predicted value of k moment moving obstacle observation points position in two dimensional surface xoy,For the predicted value of k moment moving obstacle observation points speed in two dimensional surface xoy；
Arrangement obtains system prediction equation：
Wherein, it enables
X (k-1)=(x (k-1) vx(k-1)y(k-1)vy(k-1))T
For predicted value of the k moment moving obstacle observation points in two dimensional surface xoy, X (k-1) is to transport at the k-1 moment
Dynamic lidar measurement value of the barrier observation point in two dimensional surface xoy；
It enables
Then the system prediction equation being simplified：
B, system measuring equation is built
Similarly, if the k moment moving obstacle observation points that arrive of lidar measurement in the position of two dimensional surface xoy are (x
(k),y(k))；If the k moment moving obstacle observation points that lidar measurement arrives are (v in the speed of two dimensional surface xoyx(k),
vy(k))；If Rx(k),Ry(k) be mean value be zero, variance σ1 2The k moment white Gaussian noise R (k) 2 orthogonal vectors, Rx
(k),Ry(k) any time is mutual indepedent, then k moment moving obstacle observation points are in two dimensional surface xoy internal coordinates and speed
Measuring equation is：
Wherein, it enables
X (k)=(x (k) vx(k)y(k)vy(k))T
X (k) is lidar measurement value of the k moment moving obstacle observation points in two dimensional surface xoy；
The system measuring equation being simplified：
Y (k)=HX (k)+IR (k)
C, the error covariance P at k moment is calculatedk
D, kalman gain K is calculatedk, and obtain predicted value of the k+1 moment moving obstacle observation points under two dimensional surface
Kk=PkHT(HPkHT+R(k))-1
E, predicted value of the k+1 moment moving obstacle observation points in two dimensional surface xoy is calculatedAnd laser radar
Covariance matrix P between measured value X (k+1)k+1, prepare for next recursion
Pk+1=(I-KkH)Pk
Predicted position of each moment moving obstacle observation point at two dimensional surface xoy can be obtained as a result, by each
Predicted position line can be obtained barrier observation point position prediction track.
Secondly, moving obstacle observation point under synchronization is calculated according to distance between two points formula at two dimensional surface xoy
The distance between automatic driving vehicle barycenter L, if L≤R1, then prove that moving obstacle can be in the moment and automatic driving car
It collides, will determine that the moving obstacle that can be collided is added to barrier sequence；
Step (3) detailed process is：
(1) may usually exist in automatic driving vehicle barrier sequence multiple may touch with automatic driving vehicle
The barrier hit, when there are when multiple barriers, being pressed in automatic driving vehicle barrier sequence and automatic driving vehicle distance
Distance carries out avoidance successively, and the nearest barrier of automatic driving vehicle of first adjusting the distance carries out avoidance, and so on, stationary obstruction
With moving obstacle avoidance processing is carried out by respective obstacle avoidance algorithm；
(2) stationary obstruction obstacle avoidance algorithm is as follows：
Since the stationary obstruction position in barrier sequence is constant, directly according to monitoring the case where to automatic driving vehicle
The direction of travel speed is adjusted, you can effective avoidance；
I.e. so that automatic driving vehicle steering wheel to stationary obstruction negative direction turn over certain angle θ can effective avoidance, θ
Meet：
(3) moving obstacle obstacle avoidance algorithm is as follows：
It is the R using moving obstacle barycenter as the center of circle to define obstacle circle2For the circle of radius, and obstacle circle answers envelope of motion
Barrier contour line；
A, the position of starting circle Cs, failure circle D and target circle Cf are determined：
On two dimensional surface trajectory diagram, T is taken1=TtThe range circle at-nt moment is starting circle Cs, takes TtThe obstacle at moment is justified
Justify D as failure, takes T1=TtRange circle when the+nt moment successfully avoids obstacle circle D and returns to original route is target circle
Cf；
Tt=L/vx
vx=| v-vz|
Wherein, TtCorresponding time, v when bumping against with automatic driving vehicle for moving obstaclexFor moving obstacle and nobody
The relative velocity between vehicle is driven, v is the speed of automatic driving vehicle, vzFor the speed of moving obstacle, in order to make nobody drive
Sailing vehicle has enough reflecting times, takes n >=3 and is positive integer；
B, the paths Dubins between starting circle Cs and failure circle D are determined
Justify the travel direction of D according to failure, you can obtain two effective paths Dubins, i.e. two automatic driving vehicles
Range circle is driven towards the paths Dubins for justifying D tangency locations with failure, respectively SD-1 and SD-2. by the positions starting circle Cs
C, the paths Dubins between failure circle D and target circle Cf are determined
The paths Dubins are done to failure circle D and target circle Cf, similarly, 2 the effective paths Dubins, i.e., two can be obtained
Automatic driving vehicle range circle is by driving towards the paths Dubins of the positions target circle Cf, respectively Df- with failure circle D tangency locations
1 and Df-2；
The path that path SD-1 and path Df-1 is constituted is known as path SD1F,
The path that path SD-2 and path Df-2 is constituted is known as path SD2f；
D, the paths Dubins between starting circle Cs and target circle Cf are determined
The travel direction for justifying D according to obstacle is analyzed it is found that path SD2The travel direction of f and obstacle circle D generate interference, i.e.,
Justify the close path SD of the travel direction of D with obstacle2F, path SD1The travel direction of f and obstacle circle D is justified without interference with obstacle
The separate path SD of the travel direction of D1F, it is SD that can obtain effective avoidance path1f；
The paths Dubins are as shown in Figure 4.
Claims (2)
1. a kind of automatic driving vehicle avoidance obstacle device based on the paths Dubins, which is characterized in that exist including a setting
The external camera (4) of A columns (3), a setting A columns (3) outside on the right side of automatic driving vehicle on the left of automatic driving vehicle
Camera (4) and a laser radar (2) for being set to automatic driving vehicle roof (1), where two cameras (4) are in
The middle part of A columns (3) and in the same horizontal line, laser radar (2) and the barycenter of automatic driving vehicle are on same straight line,
And the straight line and horizontal plane are perpendicular, two cameras (4) and laser radar (2) are connect with the ECU of automatic driving vehicle.
2. a kind of automatic driving vehicle avoidance obstacle method based on the paths Dubins, which is characterized in that be as follows：
Step (1) radar carries out positioning-speed-measuring to the barrier entered within the scope of camera head monitor；
The barrier sequence that step (2) will be collided based on obstacle avoidance algorithm determination with intelligent vehicle；
Step (3) intelligent vehicle is planned again according to the new current avoidance path of barrier sequence pair, to complete avoidance behaviour
Make；
Wherein,
Step (1) detailed process is：
Automatic driving vehicle is by being located at two cameras (4) in the middle part of left and right sides A columns (3) and the laser thunder of roof (1)
The obstacle information under residing multi obstacles environment is detected up to (2)；
Establish automatic driving vehicle search model, it is assumed that the region of search of automatic driving vehicle is the area that radius is R, angle of release is 2 θ
Domain, θ are determined that R is determined by camera head monitor distance by camera visibility angle；
Laser radar (2) detects the number of the barrier of the region of search in automatic driving vehicle, the traveling of barrier speed
Degree, the position of barrier and the distance between automatic driving vehicle barycenter and barrier observation point, and exercise data is transmitted
Into automatic driving vehicle central processing unit；
Step (2) detailed process is：
Range of definition circle is using automatic driving vehicle barycenter as the center of circle, with R1For the circle of radius, and the range circle should surround nobody and drive
It sails vehicle wheel profile and makes l ' >=l, the shortest distances of the l ' between range circle and automatic driving vehicle contour line, l is two
Most short safe distance between vehicle；
After barrier enters region of search, then avoidance judgement is proceeded by；
Automatic driving vehicle is typically under multi obstacles environment in the process of moving, in order to more accurately execute avoidance behaviour
Make, the barrier that automatic driving vehicle encounters is divided into two kinds：Stationary obstruction and moving obstacle；
Judgment method is：Laser radar obtains speed, the location information of the barrier in radar monitoring range every 0.05s, if
The speed of each moment barrier is 0, then the barrier is stationary obstruction, if the speed for depositing at a time barrier is not
0, then the barrier is moving obstacle；
Assuming that automatic driving vehicle moves in a straight line, two dimensional surface xoy is built, using the barycenter of automatic driving vehicle as origin, with
Automatic driving vehicle direction of advance is y-axis, and y-axis is rotated in a clockwise direction the positive direction that 90 degree are x-axis；
(1) avoidance judgement is carried out to stationary obstruction：
Because the speed of stationary obstruction is 0, i.e., stationary obstruction observation point coordinates is constant, if stationary obstruction observes point coordinates
For (x0,y0), so the shortest distance of the automatic driving vehicle and stationary obstruction that move in a straight line is exactly stationary obstruction observation
Length of perpendicular of the point to y-axis；Understand that the length of perpendicular is exactly the absolute value of stationary obstruction observation point abscissa, i.e., | x0|；When |
x0| it is more than range radius of circle R1When, it can determine whether that the stationary obstruction will not collide with automatic driving vehicle；When | x0| it is less than
Or it is equal to range radius of circle R1When, judge that the stationary obstruction can collide with automatic driving vehicle, will determine that can touch
The stationary obstruction hit is added in barrier sequence；
(2) avoidance judgement is carried out to moving obstacle：
First, trajectory predictions are carried out to the moving obstacle observation locus of points using Kalman filtering algorithm, concrete operations are：
A, system prediction equation is built
Current time is indicated with k-1, if the k-1 moment moving obstacle observation points that lidar measurement arrives are in two dimensional surface xoy
Position be (x (k-1), y (k-1))；If the k-1 moment moving obstacle observation points that lidar measurement arrives are in two dimensional surface
The speed of xoy is (vx(k-1),vy(k-1))；If the time interval at each moment is sampling interval duration t, t=is taken
0.15s；If Qx(k-1),Qy(k-1) be mean value be zero, variance σ0 22 of white Gaussian noise Q (k-1) of the k-1 moment just
Hand over vector, Qx(k-1),Qy(k-1) any time is mutual indepedent, and e is that natural constant is also referred to as Euler's numbers, then according to physical motion public affairs
It is as follows to obtain position and speed equation of the k moment moving obstacle observation points in two dimensional surface xoy for formula：
In formula,For the predicted value of k moment moving obstacle observation points position in two dimensional surface xoy,For the predicted value of k moment moving obstacle observation points speed in two dimensional surface xoy；
Arrangement obtains system prediction equation：
Wherein, it enables
X (k-1)=(x (k-1) vx(k-1) y(k-1) vy(k-1))T
For predicted value of the k moment moving obstacle observation points in two dimensional surface xoy, X (k-1) is to move barrier at the k-1 moment
Hinder lidar measurement value of the object observation point in two dimensional surface xoy；
It enables
Then the system prediction equation being simplified：
B, system measuring equation is built
Similarly, if the k moment moving obstacle observation points that arrive of lidar measurement in the position of two dimensional surface xoy are (x (k), y
(k))；If the k moment moving obstacle observation points that lidar measurement arrives are (v in the speed of two dimensional surface xoyx(k),vy
(k))；If Rx(k),Ry(k) be mean value be zero, variance σ1 2The k moment white Gaussian noise R (k) 2 orthogonal vectors, Rx
(k),Ry(k) any time is mutual indepedent, then k moment moving obstacle observation points are in two dimensional surface xoy internal coordinates and speed
Measuring equation is：
Wherein, it enables
X (k)=(x (k) vx(k) y(k) vy(k))T
X (k) is lidar measurement value of the k moment moving obstacle observation points in two dimensional surface xoy；
The system measuring equation being simplified：
Y (k)=HX (k)+IR (k)
C, the error covariance P at k moment is calculatedk
D, kalman gain K is calculatedk, and obtain predicted value of the k+1 moment moving obstacle observation points under two dimensional surface
Kk=PkHT(HPkHT+R(k))-1
E, predicted value of the k+1 moment moving obstacle observation points in two dimensional surface xoy is calculatedAnd lidar measurement
Covariance matrix P between value X (k+1)k+1, prepare for next recursion
Pk+1=(I-KkH)Pk
Predicted position of each moment moving obstacle observation point at two dimensional surface xoy can be obtained as a result, each is predicted
Position line can be obtained barrier observation point position prediction track；
Secondly, moving obstacle observation point and nothing under synchronization are calculated according to distance between two points formula at two dimensional surface xoy
People drives the distance between vehicle centroid L, if L≤R1, then prove that moving obstacle can be sent out at the moment and automatic driving vehicle
Raw collision, will determine that the moving obstacle that can be collided is added to barrier sequence；
Step (3) detailed process is：
(1) may usually exist in automatic driving vehicle barrier sequence multiple may collide with automatic driving vehicle
Barrier, when in automatic driving vehicle barrier sequence there are when multiple barriers, by the distance with automatic driving vehicle distance
Avoidance is carried out successively, the nearest barrier of automatic driving vehicle of first adjusting the distance carries out avoidance, and so on, stationary obstruction and fortune
Dynamic barrier carries out avoidance processing by respective obstacle avoidance algorithm；
(2) stationary obstruction obstacle avoidance algorithm is as follows：
Since the stationary obstruction position in barrier sequence is constant, directly automatic driving vehicle is travelled according to the case where monitoring
The direction of speed is adjusted, you can effective avoidance；
I.e. so that automatic driving vehicle steering wheel to stationary obstruction negative direction turn over certain angle θ can effective avoidance, θ is full
Foot：
(3) moving obstacle obstacle avoidance algorithm is as follows：
It is the R using moving obstacle barycenter as the center of circle to define obstacle circle2For the circle of radius, and obstacle circle answers envelope of motion barrier
Contour line；
A, the position of starting circle Cs, failure circle D and target circle Cf are determined：
On two dimensional surface trajectory diagram, T is taken1=TtThe range circle at-nt moment is starting circle Cs, takes TtThe obstacle at moment justifies conduct
Failure justifies D, takes T1=TtRange circle when the+nt moment successfully avoids obstacle circle D and returns to original route is target circle Cf；
Tt=L/vx
vx=| v-vz|
Wherein, TtCorresponding time, v when bumping against with automatic driving vehicle for moving obstaclexFor moving obstacle with it is unmanned
Relative velocity between vehicle, v are the speed of automatic driving vehicle, vzFor the speed of moving obstacle, in order to make automatic driving car
There are enough reflecting times, takes n >=3 and be positive integer；
B, the paths Dubins between starting circle Cs and failure circle D are determined
Justify the travel direction of D according to failure, you can obtain two effective paths Dubins, i.e. two automatic driving vehicle ranges
Circle is driven towards the paths Dubins for justifying D tangency locations with failure, respectively SD-1 and SD-2 by the positions starting circle Cs；
C, the paths Dubins between failure circle D and target circle Cf are determined
The paths Dubins are done to failure circle D and target circle Cf, similarly, 2 effective paths Dubins, i.e. two nothings can be obtained
People drives vehicle range circle by driving towards the paths Dubins of the positions target circle Cf with failure circle D tangency locations, respectively Df-1 and
Df-2；
The path that path SD-1 and path Df-1 is constituted is known as path SD1F,
The path that path SD-2 and path Df-2 is constituted is known as path SD2f；
D, the paths Dubins between starting circle Cs and target circle Cf are determined
The travel direction for justifying D according to obstacle is analyzed it is found that path SD2And obstacle the travel direction of f and obstacle circle D generate interference, i.e.,
Justify the close path SD of the travel direction of D2F, path SD1The travel direction of f and obstacle circle D justifies the row of D without interference with obstacle
Sail the separate path SD in direction1F, it is SD that can obtain effective avoidance path1f。
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| CN113643568A (en) * | 2021-07-22 | 2021-11-12 | 吉林大学 | Vehicle intersection collision avoidance system and method based on unmanned aerial vehicle |
| CN113589830B (en) * | 2021-10-08 | 2022-01-07 | 创泽智能机器人集团股份有限公司 | Robot walking direction prediction method and equipment |
| CN113589830A (en) * | 2021-10-08 | 2021-11-02 | 创泽智能机器人集团股份有限公司 | Robot walking direction prediction method and equipment |
| CN114103893A (en) * | 2021-11-26 | 2022-03-01 | 河北春玖智能科技有限公司 | Unmanned vehicle trajectory prediction anti-collision method |
| CN114428504A (en) * | 2022-01-18 | 2022-05-03 | 上汽通用五菱汽车股份有限公司 | Unmanned vehicle obstacle avoidance method, system, electronic device and storage medium |
| CN114489087A (en) * | 2022-04-18 | 2022-05-13 | 北京理工大学 | Multi-unmanned vehicle path collaborative planning method and system |
| CN114489087B (en) * | 2022-04-18 | 2022-07-05 | 北京理工大学 | Multi-unmanned vehicle path collaborative planning method and system |
| CN117148848A (en) * | 2023-10-27 | 2023-12-01 | 上海伯镭智能科技有限公司 | Intelligent obstacle avoidance method and system for unmanned vehicle |
| CN117148848B (en) * | 2023-10-27 | 2024-01-26 | 上海伯镭智能科技有限公司 | Intelligent obstacle avoidance method and system for unmanned vehicle |
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