CN110103956A - Automatic overtaking track planning method for unmanned vehicle - Google Patents
Automatic overtaking track planning method for unmanned vehicle Download PDFInfo
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Classifications
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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
- B60W30/10—Path keeping
- B60W30/12—Lane keeping
-
- 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
- B60W30/18—Propelling the vehicle
- B60W30/18009—Propelling the vehicle related to particular drive situations
- B60W30/18163—Lane change; Overtaking manoeuvres
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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
- B60W40/10—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 vehicle motion
- B60W40/105—Speed
-
- 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
- B60W40/10—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 vehicle motion
- B60W40/107—Longitudinal acceleration
-
- 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
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
-
- 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
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
- B60W2050/146—Display means
-
- 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
- B60W2554/00—Input parameters relating to objects
- B60W2554/80—Spatial relation or speed relative to objects
-
- 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
- B60W2554/00—Input parameters relating to objects
- B60W2554/80—Spatial relation or speed relative to objects
- B60W2554/801—Lateral distance
Abstract
The invention provides an automatic overtaking track planning method for an unmanned vehicle, which comprises the following steps: selecting historical overtaking data in a manual driving state, and constructing an overtaking intention model according with habits of human drivers; confirming whether overtaking intention is generated or not according to information acquired by a vehicle-mounted three-dimensional laser radar and a wheel speed sensor in real time in an unmanned state; judging whether the overtaking condition is met or not according to the collision time; manually confirming whether overtaking operation is executed or not; automatically planning overtaking tracks meeting safety and comfort constraints; and dynamically updating the overtaking track and displaying the overtaking track on a display screen of the cockpit. Compared with the prior art, the method is based on the overtaking habit of a human driver, the influence of the geometric dimension and the motion state of the front vehicle on the overtaking intention and the trajectory planning of the vehicle is fully considered, the optimal overtaking trajectory is selected, the occurrence of overtaking accidents is effectively avoided, and the method is suitable for popularization and use.
Description
Technical field
The present invention relates to intelligent drivings and active safety field, more particularly, to a kind of unmanned vehicle automatic overtaking system trajectory planning side
Method.
Background technique
Overtaking other vehicles is driving behavior common in vehicle travel process, and ASSOCIATE STATISTICS is shown, every year because of the road traffic for initiation of overtaking other vehicles
Accident accounts for about the 20% of total number of accident, wherein most of accidents are all that human factor causes.In overtaking process, human driver by
It is difficult to accurately obtain surrounding environment information in the limitation of itself sensing capability, fails reasonably to plan track of overtaking other vehicles, from
And cause traffic accident.Unmanned vehicle can obtain environmental information abundant by vehicle-mounted detecting sensor, and combine Ben Che and week
It encloses traveling state of vehicle variation and cooks up safe wheelpath in real time.
Application No. is 201810337901.8, invention and created name is a kind of " intelligent vehicle smooth track rule of structured road
The patent of invention of the method for drawing " detects in front of this vehicle current driving lane whether have vehicle by sensor, is super with collision time
Spoke part detects the driving status of target lane vehicle under the premise of meeting and overtaking other vehicles condition, establishes local grid map and advise
All possible track is drawn, track evaluation and optimal trajectory screening are finally carried out；Application No. is 201410815266.1, invention is created
The patent of invention for making entitled " a kind of automobile intelligent method of overtaking and system " passes through millimetre-wave radar and detects surrounding vehicles situation
Judge whether to meet and overtake other vehicles condition, the track of front truck to be surmounted is predicted using on-line prediction algorithm, generates this vehicle and initially overtake other vehicles rail
Mark, and track correct of overtaking other vehicles is carried out according to the front vehicle position signal to be surmounted obtained in real time.
However, although above-mentioned two patent of invention has formulated the condition of overtaking other vehicles, and can dynamic generation overtake other vehicles track, but have ignored
Overtake other vehicles habit and the driving intention of human driver, while not considering influence of the front truck geometric dimension to trajectory planning of overtaking other vehicles.
Summary of the invention
The purpose of the present invention is to solve the deficiencies in the prior art, provide a kind of unmanned vehicle automatic overtaking system method for planning track, root
It is raw according to this vehicle movement state information, the front truck status information for overtaking other vehicles intention and three-dimensional laser radar perceives of human driver
At the optimal track of overtaking other vehicles of high reliablity, guarantee driving safety.
To realize the above-mentioned technical purpose, the present invention is realised by adopting the following technical scheme:
A kind of unmanned vehicle automatic overtaking system method for planning track, comprising the following steps:
Step 1: recording and analyzing overtaking process data under pilot steering state, the overtaking process data include vehicle-mounted three-dimensional sharp
Relative velocity, relative distance and the front truck geometry information of the collected front truck of optical radar and this workshop, wheel speed sensors
Collected vehicle speed and acceleration；
Step 2: under unmanned state, being judged whether to generate intention of overtaking other vehicles according to intent model of overtaking other vehicles；
If not generating intention of overtaking other vehicles, lane keeping operation is executed；
The intention if generation is overtaken other vehicles, judges whether current time front truck and the relative motion state of this vehicle meet the condition of overtaking other vehicles；Such as
Fruit meets condition of overtaking other vehicles, then shows screen display " current road conditions are suitable for overtaking other vehicles " in cockpit, if human driver's selection is " really
Recognize ", 3 are thened follow the steps, lane keeping operation is otherwise executed；If being unsatisfactory for the condition of overtaking other vehicles, shown on cockpit display screen
Show " current road conditions should not overtake other vehicles ", executes lane keeping operation；
Step 3: raw according to collected vehicle speed information of wheel speed sensors and the collected front truck information of three-dimensional laser radar
The track of overtaking other vehicles constrained at anti-constraint of breakking away, lateral position constraint, the constraint of parallel transcending time and passenger comfort is met, and root
It overtakes other vehicles track according to front truck state change real-time update.
Preferably, the process of the intent model foundation of overtaking other vehicles are as follows:
(1) data acquisition and pretreatment
Acquire in real time longitudinally opposed distance between this vehicle speed, preceding vehicle-width, front truck length, Ben Che and front truck, it is laterally opposed away from
From, preceding vehicle speed, and this vehicle acceleration, this vehicle rate of acceleration change, front truck acceleration and front truck is calculated through processing and accelerates
Spend change rate.
(2) characteristic parameter is chosen
Construct the feature vector for intent model of overtaking other vehicles:
X=[vego,aego,jego,Wf,dlon,dlat,vfront,afront,jfront]
Wherein, vegoFor this vehicle speed, aegoFor acceleration, jegoFor rate of acceleration change, WfFor preceding vehicle-width, dlonFor Ben Che with
Longitudinally opposed distance, d between front trucklatFor laterally opposed distance, vfrontFor preceding vehicle speed, afrontFor acceleration, jfrontTo add
Percentage speed variation；
(3) intent model of overtaking other vehicles is established and training
It chooses follow the bus process data under pilot steering state to be normalized, constructs history passing behavior sample database, use
Radial basis function is supported vector machine modeling as kernel function, determines penalty factor c and kernel functional parameter using grid optimizing
γ establishes the intent model of overtaking other vehicles based on SVM；In sample database 60% sample is randomly selected as training set, 40% sample
As test set.
Preferably, the judgment method of the condition of overtaking other vehicles are as follows:
According to the position and speed of front truck, the collision time TTC of this spacing front truck is calculated:
In formula: dlonLongitudinally opposed distance between Ben Che and front truck；
TTC is compared with preset threshold value, if TTC is greater than or equal to threshold value, meets condition of overtaking other vehicles；Otherwise, it is unsatisfactory for
It overtakes other vehicles condition.
Preferably, described that anti-sideslip constraint, lateral position are met about according to the generation of the relative motion status information of front truck and this vehicle
The track of overtaking other vehicles that beam, the constraint of parallel transcending time and passenger comfort constrain, method particularly includes:
Assuming that it is initial time t that intention of overtaking other vehicles, which generates the moment,0, with t0The truck position Shi Keben is that origin establishes cartesian coordinate system,
By t0The direction of motion of Shi Keben vehicle is as positive direction of the x-axis, and x-axis normal direction is set as y-axis, and it is vertical that setting vehicle is moved along x-axis
To movement, move along y-axis as transverse movement, yaw angle α is this vehicle direction of motion and positive direction of the x-axis angle；Building is based on three ranks
The trajectory parameters equation of overtaking other vehicles of Bezier:
In formula: P0For starting point of overtaking other vehicles, P1And P2For Bezier control point, P3For front half section lane-change terminating point, tmFor this vehicle
Move to P3The time required to point, t ∈ (0, tm)；
By above-mentioned 4 coordinate P0(0,0)、P1(a1, 0), P2(a2, a3)、P3(a4, d) and it substitutes into above-mentioned trajectory parameters equation, it obtains
To this vehicle overtake other vehicles track longitudinal direction and lateral expression formula:
It constructs cost function and solves time tmWith length travel a4:
In formula: axFor the longitudinal acceleration of this vehicle of any moment.
The cost function of trajectory planning of overtaking other vehicles should meet the constraint of anti-sideslip, lateral position constraint, the constraint of parallel transcending time and multiply
Objective comfort constraint, specific as follows:
(1) anti-sideslip constraint:
In formula: vmax(k) maximum speed for allowing to travel for this vehicle, k are the curvature of vehicle driving trace, and μ is the friction of this wheel tire
Coefficient, L be this axle away from；
(2) lateral position constrains:
In formula: y (t) is this vehicle lateral displacement, and d is lane width, and α is this vehicle yaw angle, LeFor this vehicle commander degree；
(3) parallel transcending time constraint:
In formula: LeFor this vehicle commander degree, LfFor front truck length；
(4) passenger comfort constrains:
In formula: axFor this vehicle longitudinal acceleration, axmaxFor maximum longitudinal acceleration；ayFor this vehicle transverse acceleration, aymaxFor maximum
Transverse acceleration；jxFor this vehicle longitudinal acceleration change rate, jxmaxFor maximum longitudinal acceleration change rate；jyLaterally add for this vehicle
Percentage speed variation, jymaxFor maximum lateral acceleration change rate；
Using differential evolution algorithm to time tmWith length travel a4It is solved respectively, by variation, intersection, selection, thus
Determine unknown parameter tm、a4Value, obtain optimal expectation and overtake other vehicles track.
Beneficial effects of the present invention: compared with conventional art, the present invention using human driver's history overtake other vehicles data building overtake other vehicles
Intent model can make overtake other vehicles operation of the unmanned vehicle under true road conditions well close to the habit of overtaking other vehicles of human driver；Not
In the case where relying on any vehicular communication equipment, three-dimensional laser radar sensor is selected accurately to obtain front truck dimension information and movement
Status information, and consider in the constraint condition for trajectory planning of overtaking other vehicles the influence of front truck size factor, construct the constraint of anti-sideslips, cross
To position constraint, the constraint of parallel transcending time and passenger comfort constraint, the optimal track of overtaking other vehicles of dynamic real-time update is fully ensured that
The safety and reliability of overtaking process.
Detailed description of the invention
Fig. 1 is system structure diagram of the invention；
Fig. 2 is technology path flow chart of the invention；
Fig. 3 is track schematic diagram of overtaking other vehicles of the invention；
Fig. 4 is critical collision moment schematic diagram of overtaking other vehicles of the invention；
Specific embodiment
The following describes the present invention in detail with reference to the accompanying drawings and specific embodiments.
The present embodiment uses the automatic driving vehicle equipped with Velodyne16 line three-dimensional laser radar, W221 wheel speed sensors.
As shown in Figure 1, environment sensing unit acquires this vehicle surrounding traffic environmental information, speed acquiring unit acquires this vehicle speed letter
Breath, data processing unit is processed collected vehicle with front truck status information, true through passing behavior decision package
Ding Benche execution is overtaken other vehicles after operation, and by overtaking other vehicles, trajectory planning unit generates in real time and update track of overtaking other vehicles, and is eventually displayed in driving
On the display screen of cabin.
The Trajectory Planning System as shown in Fig. 2, a kind of unmanned vehicle based on three-dimensional laser radar is independently overtaken other vehicles, includes the following steps:
Step 1: recording and analyzing history overtaking process data under pilot steering state, including vehicle-mounted three-dimensional laser radar collects
Front truck and this workshop relative velocity, relative distance and front truck geometry information, collected vehicle of wheel speed sensors
Velocity and acceleration, building meet the intent model of overtaking other vehicles of human driver's driving habit.The present invention is to guarantee that safety was overtaken other vehicles
Journey only considers that there are situations for the noiseless vehicle in target lane；
Step 1.1: data prediction: wheel speed sensors acquire this vehicle speed v in real timeego, calculate this vehicle acceleration aego
And rate of acceleration change jego；
Points cloud processing module is from three-dimensional laser radar sensor in real time collected environment point cloud data, before cluster segmentation obtains
Vehicle point cloud cluster carries out rectangle fitting to front truck point cloud cluster using stochastical sampling consistency algorithm, vehicle-width W before obtainingf, preceding vehicle commander
Spend Lf, front truck center (Xf,Yf), calculate the longitudinally opposed distance d of front truck Yu this workshoplon, laterally opposed distance
dlat, preceding vehicle speed vfront, front truck acceleration afront, rate of acceleration change jfront。
Step 1.2: characteristic parameter is chosen: choosing this vehicle speed vego, acceleration aego, rate of acceleration change jego, preceding vehicle width
Spend Wf, longitudinally opposed distance d between Ben Che and front trucklon, laterally opposed distance dlat, the speed v of front truckfront, acceleration
afront, rate of acceleration change jfrontTotally 9 characteristic parameters construct the feature vector for intent model of overtaking other vehicles:
X=[vego,aego,jego,Wf,dlon,dlat,vfront,afront,jfront]
Step 1.3: intent model of overtaking other vehicles is established and training: choosing and overtakes other vehicles and 1000 groups for 500 groups of driver under pilot steering state
Follow the bus process data is normalized, and history passing behavior sample database is constructed, using radial basis function RBF as kernel function
Carry out SVM modeling, using grid optimizing determine penalty factor c and kernel functional parameter γ (choose c=3 after many tests, γ=
0.08) intent model of overtaking other vehicles based on SVM, is finally established.In sample database 60% sample is randomly selected as training set, 40%
Sample as test set, in the case where current target lane is noiseless vehicle, Ruo Benche driving status opposite with front truck
Meet human driver to overtake other vehicles habit, then model output 1, confirmation generates intention of overtaking other vehicles；On the contrary then model output 0, does not generate super
Vehicle is intended to.
Step 2: under unmanned state, being judged whether to generate intention of overtaking other vehicles according to intent model of overtaking other vehicles.If not generating meaning of overtaking other vehicles
Figure, then execute lane keeping operation.The intention if generation is overtaken other vehicles, when judging current according to the collision time TTC of this spacing front truck
Whether the relative motion state for carving front truck and this vehicle meets the condition of overtaking other vehicles:
In formula: dlonLongitudinally opposed distance between Ben Che and front truck, vegoFor this vehicle speed, vfrontFor preceding vehicle speed；
If TTC is greater than or equal to 6s, meets condition of overtaking other vehicles and be otherwise unsatisfactory for the condition of overtaking other vehicles；
The condition if satisfaction is overtaken other vehicles shows screen display " current road conditions are suitable for overtaking other vehicles " in cockpit, if the mankind drive at this time
Member's selection " confirmation ", thens follow the steps 3, otherwise executes lane keeping operation；It is aobvious in cockpit if being unsatisfactory for the condition of overtaking other vehicles
Show screen display " current road conditions should not overtake other vehicles ", executes lane keeping operation；
Lane keeping operation uses ACC model, for controlling this vehicle longitudinal velocity during follow the bus, protects Ben Che always with front truck
Safe distance is held, ACC Model Calculating Method is as follows:
Wherein: dminThe minimum safe distance between Ben Che and front truck takes 5m, h in the present embodimentdesiredFor the vehicle of Ben Che and front truck
Away from v when headfrontFor front truck speed, dlonFor Ben Che and front truck longitudinally opposed distance, vegoFor this vehicle speed, acc is this vehicle target
Acceleration, μd、μvFor weight coefficient, 0.5 is taken in the present embodiment.
Step 3: track formulation of overtaking other vehicles: as shown in Figure 3, it is assumed that intention of the overtaking other vehicles generation moment is denoted as initial time t0, with t0Moment
This parking stall is set to origin and establishes cartesian coordinate system, by t0The Shi Keben vehicle direction of motion is as positive direction of the x-axis, x-axis normal direction
It is set as y-axis, setting vehicle is moved along x-axis as longitudinal movement, is moved along y-axis as transverse movement, yaw angle α is this vehicle direction of motion
With positive direction of the x-axis angle, lane width d.This vehicle of building based on three rank Beziers is overtaken other vehicles trajectory parameters equation:
In formula: P0For starting point of overtaking other vehicles, P1And P2For Bezier control point, P3It overtakes other vehicles terminating point for front half section, tmFor this vehicle
Move to P3The time required to point, t ∈ (0, tm)；
By 4 coordinate P0(0,0)、P1(a1, 0), P2(a2, a3)、P3(a4, d) and it substitutes into above-mentioned trajectory parameters equation, obtain this
Vehicle overtake other vehicles track longitudinal direction and lateral expression formula:
First derivative is sought in longitudinal direction and lateral expression formula to track of overtaking other vehicles, respectively obtains longitudinal desired speed of overtaking process
With lateral desired speed
Assuming that overtake other vehicles under original state, this vehicle longitudinal velocity vx(0)=v, lateral movement velocity vy(0)=0, then initial time
This vehicle motion state expression formula are as follows:
Original state is substituted into overtaking process desired speed and desired acceleration expression formula solve:
In formula: vxIt (0) is this vehicle longitudinal velocity under original state of overtaking other vehicles, ax(0) longitudinally accelerate for this vehicle under original state of overtaking other vehicles
Degree；
Pass through a known to above formula1、a2With tmRelationship, therefore only demand solution time tmWith length travel a4；
It constructs cost function and solves time tmWith length travel a4:
To guarantee that vehicle safety and comfort, the cost function for trajectory planning of overtaking other vehicles should meet anti-sideslip and constrain, laterally
Position constraint, the constraint of parallel transcending time and passenger comfort constraint, specific as follows:
(1) anti-sideslip constraint:
In formula: vmax(k) maximum speed for allowing to travel for this vehicle, k are the curvature of vehicle driving trace, and μ is the friction of this wheel tire
Coefficient, L be this axle away from；
(2) as shown in figure 4, needing to fully consider that front truck is several to guarantee that this vehicle E does not collide in overtaking process with front truck F
What influence of the size to track of overtaking other vehicles, therefore lateral position constraint should be met in overtaking process:
In formula: y (t) is this vehicle lateral displacement, WfFor preceding vehicle-width, d is lane width, and α is this vehicle yaw angle, LeFor this vehicle commander
Degree；
(3) the parallel transcending time t of this vehicle in overtaking processpCalculation formula is as follows:
In formula: LeFor this vehicle commander degree, LfFor front truck length, vegoFor this vehicle speed, vfrontFor front truck speed；
In overtaking process under the premise of guaranteeing not collide with front truck, this vehicle and front truck driving alongside should be shortened as far as possible
Time, therefore parallel transcending time is constrained:
tp≤5s
(4) passenger comfort constrains:
In formula: axFor this vehicle longitudinal acceleration, axmaxFor maximum longitudinal acceleration；ayFor this vehicle transverse acceleration, aymaxFor maximum
Transverse acceleration；jxFor this vehicle longitudinal acceleration change rate, jxmaxFor maximum longitudinal acceleration change rate；jyLaterally add for this vehicle
Percentage speed variation, jymaxFor maximum lateral acceleration change rate.In view of the comfort of passenger, a in the present embodimentxmaxTake 4m/
s2, aymaxTake 2m/s2, jxmaxTake 0.5m/s3, jymaxTake 0.5m/s3；
Track of overtaking other vehicles should meet aforementioned four constraint condition, therefore the trajectory planning problem that will overtake other vehicles is converted into constrained optimization solution and asks
Topic.Using differential evolution algorithm to time tmWith length travel a4Solved respectively, differential evolution algorithm mainly include variation,
Intersect, three kinds of operations of selection, circular is as follows:
(1) initialization population: by unknown parameter tm、a4Solution space random initializtion obtain comprising NpIndividual is initial
Population, initial population individual are denoted asThe dimension of solution space is denoted as D；
(2) to i-th of initial population individualDifferential variation operation is carried out, is constructed first by the differential vector between parent individuality
Mutation operator:
In formula: i is the search space that parameter vector (i=1,2,3 ...) constitutes population；G is the number of iterations；For construction
Mutation operator；Three Different Individuals chosen for parent；F is scale factor, value range
For (0,1.2], 0.5 is taken in the present embodiment；
(3) according to predetermined probabilities CR, to G for population xi,j,GAnd its intermediate v of variationi,j,G+1Crossover operation is carried out, is generated
One test individual μi,j,G:
In formula: randj generates a random number, and the value range of the random number is [0,1], is used to and crossover probability CR (this reality
It applies to take in example and 0.6) compares the selection judgement of carry out condition；J is j-th of variable j ∈ { 1, D } in solution space D dimension variable；
It (4), will be by making a variation and the test individual after crossover operation according to the value of adaptive response function fWith initial population
BodyCarry out optimum selecting:
Individual after optimum selecting is denoted asAbove-mentioned variation, intersection, selection operation are repeated, constantly approaches optimal solution, directly
To termination condition is met, the individual of final output is optimum individual, so that it is determined that unknown parameter tm、a4Value, obtain the optimal phase
Prestige is overtaken other vehicles track.
The track of overtaking other vehicles of generation is transmitted to cockpit display screen and shown by trajectory planning unit, it is expected that track of overtaking other vehicles is every
100ms updates primary.
Although being described above in conjunction with specific embodiment of the attached drawing to the invention patent, the invention is not limited to
Above-mentioned specific embodiments and applications field, above-mentioned specific embodiment are only schematical, directiveness, rather than
It is restrictive.Those skilled in the art can also make many improvement not departing from scope of the invention, these belong to
In the column of protection of the invention.
Claims (4)
1. a kind of unmanned vehicle automatic overtaking system method for planning track, which comprises the following steps:
Step 1: recording and analyzing overtaking process data under pilot steering state, the overtaking process data include vehicle-mounted three-dimensional sharp
Relative velocity, relative distance and the front truck geometry information of the collected front truck of optical radar and this workshop, wheel speed sensors
Collected vehicle speed and acceleration；
Step 2: under unmanned state, being judged whether to generate intention of overtaking other vehicles according to intent model of overtaking other vehicles；
If not generating intention of overtaking other vehicles, lane keeping operation is executed；
The intention if generation is overtaken other vehicles, judges whether current time front truck and the relative motion state of this vehicle meet the condition of overtaking other vehicles；Such as
Fruit meets condition of overtaking other vehicles, then shows screen display " current road conditions are suitable for overtaking other vehicles " in cockpit, if human driver's selection is " really
Recognize ", 3 are thened follow the steps, lane keeping operation is otherwise executed；If being unsatisfactory for the condition of overtaking other vehicles, shown on cockpit display screen
Show " current road conditions should not overtake other vehicles ", executes lane keeping operation；
Step 3: raw according to collected vehicle speed information of wheel speed sensors and the collected front truck information of three-dimensional laser radar
The track of overtaking other vehicles constrained at anti-constraint of breakking away, lateral position constraint, the constraint of parallel transcending time and passenger comfort is met, and root
It overtakes other vehicles track according to front truck state change real-time update.
2. unmanned vehicle automatic overtaking system method for planning track according to claim 1, which is characterized in that described overtake other vehicles is intended to mould
The process that type is established are as follows:
(1) data acquisition and pretreatment
Acquire in real time longitudinally opposed distance between this vehicle speed, preceding vehicle-width, front truck length, Ben Che and front truck, it is laterally opposed away from
From, preceding vehicle speed, and this vehicle acceleration, this vehicle rate of acceleration change, front truck acceleration and front truck is calculated through processing and accelerates
Spend change rate.
(2) characteristic parameter is chosen
Construct the feature vector for intent model of overtaking other vehicles:
X=[vego,aego,jego,Wf,dlon,dlat,vfront,afront,jfront]
Wherein, vegoFor this vehicle speed, aegoFor acceleration, jegoFor rate of acceleration change, WfFor preceding vehicle-width, dlonFor Ben Che with
Longitudinally opposed distance, d between front trucklatFor laterally opposed distance, vfrontFor preceding vehicle speed, afrontFor acceleration, jfrontTo add
Percentage speed variation；
(3) intent model of overtaking other vehicles is established and training
It chooses follow the bus process data under pilot steering state to be normalized, constructs history passing behavior sample database, use
Radial basis function is supported vector machine modeling as kernel function, determines penalty factor c and kernel functional parameter using grid optimizing
γ establishes the intent model of overtaking other vehicles based on SVM；In sample database 60% sample is randomly selected as training set, 40% sample
As test set.
3. unmanned vehicle automatic overtaking system method for planning track according to claim 1, which is characterized in that the condition of overtaking other vehicles
Judgment method are as follows:
According to the position and speed of front truck, the collision time TTC of this spacing front truck is calculated:
In formula: dlonLongitudinally opposed distance between Ben Che and front truck；
TTC is compared with preset threshold value, if TTC is greater than or equal to threshold value, meets condition of overtaking other vehicles；Otherwise, it is unsatisfactory for
It overtakes other vehicles condition.
4. unmanned vehicle automatic overtaking system method for planning track according to claim 1, which is characterized in that described according to front truck
Relative motion status information generation with this vehicle meets anti-sideslip constraint, lateral position constraint, the constraint of parallel transcending time and multiplies
The track of overtaking other vehicles of objective comfort constraint, method particularly includes:
Assuming that it is initial time t that intention of overtaking other vehicles, which generates the moment,0, with t0The truck position Shi Keben is that origin establishes cartesian coordinate system, will
t0For the direction of motion of Shi Keben vehicle as positive direction of the x-axis, x-axis normal direction is set as y-axis, and setting vehicle is moved along x-axis as longitudinal direction
Movement is moved along y-axis as transverse movement, and yaw angle α is this vehicle direction of motion and positive direction of the x-axis angle；Building is based on three rank shellfishes
The trajectory parameters equation of overtaking other vehicles of Sai Er curve:
In formula: P0For starting point of overtaking other vehicles, P1And P2For Bezier control point, P3For front half section lane-change terminating point, tmFor this vehicle
Move to P3The time required to point, t ∈ (0, tm)；
By above-mentioned 4 coordinate P0(0,0)、P1(a1, 0), P2(a2, a3)、P3(a4, d) and it substitutes into above-mentioned trajectory parameters equation, it obtains
This vehicle overtake other vehicles track longitudinal direction and lateral expression formula:
It constructs cost function and solves time tmWith length travel a4:
In formula: axFor the longitudinal acceleration of this vehicle of any moment.
The cost function of trajectory planning of overtaking other vehicles should meet the constraint of anti-sideslip, lateral position constraint, the constraint of parallel transcending time and multiply
Objective comfort constraint, specific as follows:
(1) anti-sideslip constraint:
In formula: vmax(k) maximum speed for allowing to travel for this vehicle, k are the curvature of vehicle driving trace, and μ is the friction of this wheel tire
Coefficient, L be this axle away from；
(2) lateral position constrains:
In formula: y (t) is this vehicle lateral displacement, and d is lane width, and α is this vehicle yaw angle, LeFor this vehicle commander degree；
(3) parallel transcending time constraint:
In formula: LeFor this vehicle commander degree, LfFor front truck length；
(4) passenger comfort constrains:
In formula: axFor this vehicle longitudinal acceleration, axmaxFor maximum longitudinal acceleration；ayFor this vehicle transverse acceleration, aymaxFor maximum
Transverse acceleration；jxFor this vehicle longitudinal acceleration change rate, jxmaxFor maximum longitudinal acceleration change rate；jyLaterally add for this vehicle
Percentage speed variation, jymaxFor maximum lateral acceleration change rate；
Using differential evolution algorithm to time tmWith length travel a4It is solved respectively, by variation, intersection, selection, thus really
Determine unknown parameter tm、a4Value, obtain optimal expectation and overtake other vehicles track.
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