CN105974917B - A kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method - Google Patents
A kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method Download PDFInfo
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Abstract
The vehicle obstacle-avoidance path planning research method based on novel artificial potential field method that the invention discloses a kind of, comprising steps of utilizing CCD camera, millimetre-wave radar, information needed for onboard sensor acquires vehicle obstacle-avoiding route planning in real time respectively, after information needed for vehicle obstacle-avoidance path planning, establish road boundary repulsion potential field and barrier repulsion potential field model based on Artificial Potential Field Method, equilibrium equation is established in the effect for the power being subject in the Composite Field that road boundary repulsion potential field and barrier repulsion potential field form by main vehicle, solution obtains the main vehicle location point to be passed through during avoidance, to obtain avoidance path, the main vehicle speed during avoidance is controlled to improve safety and comfort simultaneously.Method therefor calculation amount of the present invention is small, is easy to implement real-time control, and the avoidance path cooked up is more safer and more reliable than conventional method.
Description
Technical field
The invention belongs to vehicle driving security fields, more particularly to a kind of vehicle based on novel artificial potential field method
Obstacle-avoiding route planning research method.
Background technique
Road traffic accident is mostly caused by the secondary accident after the collision and collision of vehicle and barrier.According to the Ministry of Public Security
China's statistics of traffic accidents data in 2010 of traffic administration Science Institute publication, analysis is it is found that because of driver's fault (ratio
The number of traffic accidents caused by such as: error in judgement, incorrect decision etc.) accounts for about 90%.If can be helped in emergency traffic
Driver is helped to take corresponding safety measure, then traffic accident probability will substantially reduce, and the part of vehicle is kept away
Barrier path planning is exactly the important means for realizing this target.This method is one safe road of vehicle planning department before collision occurs
Diameter makes the collisionless cut-through object of vehicle, this has a very important significance to road traffic accident is reduced.
Vehicle part path planning is a more complicated process, and driver only relies on feeling and warp when driving
Test the judgement for carrying out avoidance, it is easy to accident occur, especially when running at high speed.Local paths planning is broadly divided into known environment
Information and circumstances not known information two types, since the range that the former is adapted to is limited to very much, so present invention is generally directed to not
Know the vehicle local paths planning under environmental information situation.Vehicle is (millimetre-wave radar, CCD camera, various by mobile unit
Sensor etc.) road information is obtained, it such as has a lot of social connections, the position of number of track-lines, barrier, size etc., and these information are carried out centainly
Analysis processing, then go out the optimal road of a collisionless by starting point to target point according to these information plannings for detecting
Diameter.
102520718 A of Chinese patent CN discloses a kind of robot obstacle-avoiding route planning method based on physical modeling,
This method establishes the dual grid information of robot by setting up the gravitational field grid and range information grid of robot work region
Figure is based on above-mentioned dual grid hum pattern, searches for all feasible paths using oriented traversal and is planned.This method is to be directed to
Obstacle-avoiding route planning is carried out for robot under the conditions of environmental information, and when grid obtains very little, there are computationally intensive etc.
Problem.Chinese patent CN104317291A discloses a kind of robot collision avoidance path planning research side based on Artificial Potential Field Method
Method provides a kind of collision prevention paths planning method of complicated shape mobile robot under circumstances not known.This method is only applicable in
In the occasion of static-obstacle thing, and it cannot overcome the problems, such as the local minimum of traditional artificial potential field method.
Summary of the invention
In view of the deficiencies of the prior art, the present invention provides a kind of, and the vehicle obstacle-avoidance path based on novel artificial potential field method is advised
Research method is drawn, solves the problems, such as the local minimum of computationally intensive, traditional artificial potential field method.
The present invention is to adopt the following technical scheme that, realizes above-mentioned technical purpose.
A kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method, comprising the following steps:
S1. it is acquired needed for vehicle obstacle-avoiding route planning in real time respectively using CCD camera, millimetre-wave radar, mobile unit
Road information, obstacle information, main vehicle information；
S2. after information needed for obtaining vehicle obstacle-avoidance path planning, road is established in the investigative range of millimetre-wave radar and is sat
Mark system, the position of road boundary point, barrier, main vehicle is indicated with vector, according to road information, obstacle information, main vehicle information
Establish road boundary repulsion potential field and barrier repulsion potential field model based on Artificial Potential Field Method；It is specific as follows:
The foundation of S2.1 path coordinate system
On the multiple-lane road that straight or approximate straight, width is B, according to millimetre-wave radar performance, in millimetre-wave radar
Detectable distance L in, road boundary is divided into n equal portions, the distance between each equal portions be L0=L/n；With lane where main vehicle
Center line be x-axis, subpoint of the main vehicle mass center on road surface is that origin establishes path coordinate system, it is assumed that at following each moment
The mass center of automobile is located at road boundary and corresponds on the line of Along ent, then each Along ent on the left and right boundary of road, barrier,
The position of main vehicle can be represented by vectors out；
The foundation of S2.2 road boundary repulsion potential field
By the lane boundary line in front of CCD camera identification and lane boundary line data are extracted, pass through boundary line number
Road information is extracted according to being analyzed and processed, then road boundary repulsion potential field is established with this；
The foundation of S2.3 barrier repulsion potential field
Detect the obstacle information of main front side by millimetre-wave radar, onboard sensor obtains the velocity information of main vehicle,
Barrier repulsion potential field is established with this again；
S3. the power being subject in the Composite Field that road boundary repulsion potential field and barrier repulsion potential field form according to main vehicle
Equilibrium equation is established in effect, and is solved to obtain what main vehicle to be passed through during avoidance to it using mathematical software matlab
Location point, to obtain avoidance path；
S4. the main vehicle speed during avoidance is controlled to improve safety, drops main vehicle by speed in avoidance
As low as a suitable value, and restore normal speed traveling after getting around barrier.
Further, in the S1, road information includes having a lot of social connections and lane quantity；Obstacle information, the number including barrier
Mesh, size, position and speed；Main vehicle information includes the speed of main vehicle, main vehicle at a distance from barrier, main vehicle and road boundary
The angle of distance and main vehicle relative to barrier.
Further, in the establishment process of the S2.3 barrier repulsion potential field, main vehicle is equivalent to a particle, and with one
The safety circle that a diameter is D wraps barrier, meanwhile, in order to enable main vehicle to start avoidance in advance, assign one, barrier
Coverage ρ0, as vehicle barriers to entry object coverage ρ0When, it will be only by the barrier along path coordinate system y directional spreding
The effect of repulsion potential field, meanwhile, for the barrier of main front side movement, if the speed of barrier has on main vehicle speed direction
Velocity component, then main vehicle also suffers from the repulsion effect of barrier velocity potential field.
Further, in the S3, the equilibrium equation of foundation is solved by matlab, actually obtain be main vehicle it is following certain
The ordinate for the point that moment will drive towards to obtain main vehicle in the avoidance process each point to be passed through, then these points is carried out
Curve matching, to obtain the avoidance path that can make the safe cut-through object of main vehicle；Simultaneously as barrier is likely to be
Movement, so Δ t at regular intervals, carries out path planning according to freshly harvested information, to guarantee real-time again.
Further, the S4 is during main vehicle avoidance, after main vehicle barriers to entry object coverage, carries out to main vehicle speed
Control, enables main vehicle speed to reduce with the reduction of main vehicle and obstacle distance, after vehicle cut-through object, main vehicle speed energy
Increase with the increase of main vehicle and obstacle distance, when main vehicle is driven out to the coverage of barrier, main vehicle speed will no longer by
The control of the model.
The utility model has the advantages that being that vehicle automatic obstacle avoiding cooks up a secure path, and is keeping away using improved Artificial Potential Field Method
Main vehicle speed is controlled to improve the safety of avoidance process and comfort during barrier.Barrier for movement and quiet
Barrier only, this method can cook up the collisionless path of safety before collision occurs for vehicle and get around barrier, can pole
Big reduction is because of the traffic accident caused by avoidance fault, and method therefor calculation amount is small, is easy to implement real-time control.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention；
Fig. 2 is road described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention
Road coordinate system diagram；
Fig. 3 is road described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention
Roadside circle repulsion schematic diagram；
Fig. 4 is road described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention
Roadside circle repulsion Distribution of Potential Field figure；
Fig. 5 is speed described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention
Spend direction schematic diagram；
Fig. 6 is master described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention
The suffered resultant force of vehicle is schemed；
Fig. 7 is to keep away described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention
Hinder path profile；
Fig. 8 be described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention not
Introduce speed avoidance path profile；
Fig. 9 is road described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention
Diameter follows figure；
Figure 10 is described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention
Yaw velocity figure；
Figure 11 is described in a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method of the present invention
Side acceleration figure.
Specific embodiment
Below in conjunction with attached drawing and specific embodiment, the present invention is further illustrated, but protection scope of the present invention
It is not limited to this.
As shown in Figure 1, a kind of vehicle obstacle-avoidance path planning research side based on modified Artificial Potential Field Method and speed control
Method flow chart, comprising steps of
S1. respectively using CCD camera, millimetre-wave radar, mobile unit (onboard sensor, global position system GPS)
Road information, obstacle information, main vehicle information needed for acquisition vehicle obstacle-avoiding route planning in real time；CCD camera is mounted on master
On Chinese herbaceous peony windshield, it need to guarantee that camera " can look at " front straight；Millimetre-wave radar is mounted on the longitudinal direction of headstock front, vehicle
On axis, at least it is 35cm at a distance from ground, is up to 65cm；Vehicle speed sensor is mounted in transmission case, and main car is set
There is GPS.
Wherein road information includes having a lot of social connections and lane quantity；Obstacle information, number, size including barrier, position
And speed；Main vehicle information include the speed of main vehicle, main vehicle at a distance from barrier, main vehicle is at a distance from road boundary and main vehicle
Angle relative to barrier.
S2. after information needed for obtaining vehicle obstacle-avoidance path planning, road is established in the investigative range of millimetre-wave radar and is sat
Mark system, the position of road boundary point, barrier, main vehicle is indicated with vector, according to road information, obstacle information, main vehicle information
Establish road boundary repulsion potential field and barrier repulsion potential field model based on Artificial Potential Field Method；It is specific as follows:
The foundation of S2.1 path coordinate system
On the multiple-lane road that straight or approximate straight, width is B, according to millimetre-wave radar performance, in millimetre-wave radar
Detectable distance L in, road boundary is divided into n equal portions, the distance between each equal portions be L0=L/n, as shown in Figure 2；With master
The center line in lane where vehicle is x-axis, and subpoint of the main vehicle mass center on road surface is that origin establishes path coordinate system, it is assumed that not
The mass center for carrying out each moment automobile is located at road boundary and corresponds on the line of Along ent, then each equal part on the left and right boundary of road
Point, barrier, main vehicle position can be represented by vectors out.
The foundation of S2.2 road boundary repulsion potential field
By the lane boundary line in front of CCD camera identification and lane boundary line data are extracted, pass through boundary line number
Road information is extracted according to being analyzed and processed, then road boundary repulsion potential field is established with this；Road boundary repulsion potential field is to place
Repulsion effect is generated in vehicle wherein, as shown in figure 3, limiting the running region of vehicle with this.
According to the experience that Artificial Potential Field Model is used in robot field, the road boundary repulsion gesture being shown below is established
The mathematical model of field:
U in formularoad,L、Uroad,RRespectively road right boundary repulsion potential field, kroadL、kroadRRespectively road is left and right
Cutoff risk repulsion field applies the proportionality constant of repulsion,It is corresponding respectively on the left and right boundary of automobile mass center, road
The coordinate vector of point, WVehicleFor vehicle width.
By mathematical model (1), (2) and Fig. 4 it is found that automobile is smaller at a distance from road boundary, its potential energy value is bigger, vapour
The repulsion that vehicle is subject to is also bigger, and when vehicle goes to zero at a distance from road boundary, road boundary repulsion will tend to be infinitely great,
The running region of vehicle is limited with this, repulsion can be obtained by carrying out gradient algorithm to potential field model.
It, can be along lanes, i.e., when in order to make vehicle in the road without barrier or without taking avoidance measure
Realize lane keep function, we by adjusting potential field proportionality constant kroad,L、kroad,RTo make vehicle in road boundary repulsion
Under the action of potential field, stress balance point is remained among lane, still, it is contemplated that the driving of traffic rules and driver
Habit, we will make main vehicle without that can travel along the center line of right lane in the case where avoidance as far as possible, and the present invention takes master
Vehicle traveling lane is two-way traffic, from potential field mathematical model:
Uroad,L=Uroad,R (3)
When not having barrier, main vehicle is apart from lane right margin distanceMain vehicle is apart from lane
Left margin distance is
I.e.
To obtain following relationship:
The foundation of S2.3 barrier repulsion potential field
Detect the obstacle information of main front side by millimetre-wave radar, onboard sensor obtains the velocity information of main vehicle,
Barrier repulsion potential field is established with this again.
Barrier repulsion potential field generates repulsion effect to the vehicle in traveling, makes vehicle far from barrier.Automobile is travelling
In the process, the road traffic condition in front may all change at any time, may not have barrier, may occur obstacle suddenly
Object, barrier may be static, it is also possible to movement；Therefore, trailer-mounted radar must constantly detect front with certain frequency
Road conditions, number, size, position and speed including barrier.The factor for influencing barrier repulsion size mainly has:
Position and speed of the barrier relative to this vehicle, the size (pressing standard vehicle) of barrier.
During path planning, main vehicle is equivalent to a particle, this is not inconsistent with actual conditions, thus with a diameter
Barrier is wrapped for the safety circle of D, this size justified safely must all take into account the size of main vehicle and barrier, be
The tentative diameter D of this present invention is twice of vehicle width.Meanwhile in order to which main vehicle can start avoidance in advance, we assign barrier one
A coverage ρ0, ρ0Value is the brake safe distance of vehicle, as vehicle barriers to entry object coverage ρ0When, it will be hindered
Hinder the effect of object repulsion potential field, and the repulsion potential field is only distributed in the y-direction.Meanwhile for the barrier of main front side movement, rule
Determining barrier directional velocity is β, and the direction of main vehicle speed is θ, as shown in figure 5, then main vehicle speed direction and barrier speed side
Angle α=θ-β between；IfI.e. the speed of barrier has one-component v on main vehicle speed0Cos α, then
Main vehicle also suffers from the repulsion effect of barrier velocity potential field；IfI.e. the speed of barrier is in main vehicle speed direction
Upper no velocity component, then main vehicle is not by the effect of speed repulsion potential field.Avoidance process only considers the barrier of main front side, therefore
α∈(0,π)。
Situation one, whenWhen, the repulsion potential field of barrier are as follows:
Situation two, whenWhen, the repulsion potential field of barrier are as follows:
Situation three, whenWhen, at this point, main vehicle is by the effect of barrier repulsion potential field, i.e.,
Ureq=0 (8)
In conclusion barrier repulsion potential field is
K in formulaobFor the proportionality coefficient of barrier repulsion potential field,For the coordinate vector of automobile mass center corresponding points, WVehicleFor vehicle
Width,For the position vector of barrier, D is safe diameter of a circle, ρ0For the coverage of barrier, v is the current fortune of main vehicle
Dynamic speed, v0For the current kinetic speed of dynamic barrier, θ is the current kinetic direction of moving body；φ is dynamic barrier
Current kinetic direction.
From the potential energy value distribution map of mathematical model (9) and Fig. 4 it is found that main vehicle is after the coverage of barriers to entry object,
As main vehicle and obstacle distance reduce, the repulsion that main vehicle is subject to increases, when main vehicle level off at a distance from barrier zero when, barrier
Hinder the repulsion of object by region infinity, is bumped against with this to make main vehicle refuse barrier.Meanwhile for the barrier of movement, obstacle
Component of the speed of object on this vehicle speed direction is bigger, and the repulsion that this vehicle is subject to is also bigger.
S3. the power being subject in the Composite Field that road boundary repulsion potential field and barrier repulsion potential field form according to main vehicle
Equilibrium equation is established in effect, and is solved to obtain the main vehicle location point to be passed through during avoidance to it using matlab,
To obtain avoidance path；
In the Composite Field that road boundary repulsion potential field and barrier repulsion potential field form, work of the main vehicle by compound field force
With, and it is finally reached equilibrium state, as shown in Figure 6, it may be assumed that
It is solved by mathematical software matlab, as it is assumed that main vehicle all corresponds to for the abscissa of the following any time
The a certain Along ent in roadside circle, i.e., (x known to the abscissa of main vehiclei=(i-1) L0), equilibrium equation is solved, is actually obtained
It is the ordinate for the point that will be driven towards at certain following moment of main vehicle, to obtain main vehicle in the avoidance process each point to be passed through, so
As soon as afterwards being connected these points with smooth curve, the avoidance road that can make the safe cut-through object of main vehicle is obtained
Diameter.Simultaneously as barrier is likely to be movement, so Δ t at regular intervals, carries out again according to freshly harvested information
Path planning, to guarantee real-time.
Main program is as follows:
By the operation of matlab, the coordinate in available avoidance path shares 120 groups of data according to the value of l, by
In the limitation of length, 20 groups are only listed here, as shown in table 1:
20 groups of coordinates of 1 avoidance process of table
It can be seen that improved method from 1 data of table and Fig. 7 and cook up the path come main vehicle and barrier during avoidance
The distance of object is hindered to be greater than the distance at least 20cm before improving, this can effectively improve safety when avoidance, avoid and obstacle
There is a phenomenon where " brushing past " for object.As can be seen from Figure 8, for the barrier of movement, what the method before improvement was cooked up
Path and barrier have overlapping, this illustrates that main vehicle can be bumped against by this route with barrier, and improved method can be very
The good barrier for evading movement.
S4. the main vehicle speed during avoidance is controlled to improve safety, drops main vehicle by speed in avoidance
As low as a suitable value, and restore normal speed traveling after getting around barrier.
Vehicle guarantees safety during avoidance, it is necessary to maintain a certain distance with barrier, and turn in avoidance
When, if still travelling (usual > 40km/h) with speed before, safety and the riding comfort of avoidance can be seriously affected,
When especially running at high speed, this paper presents the control methods to avoidance process car speed thus, make vehicle will in avoidance
Speed is reduced to a suitable value, and restores normal speed traveling after getting around barrier.The Controlling model of speed are as follows:
D in formulacoRepresent main vehicle between barrier at a distance from, d0For reserved safe distance, vcIt is the speed before main vehicle avoidance
Degree, amaxFor maximum deceleration, λ is amplification coefficient, takes λ=0.6~0.7, ρ0Represent the influence distance of barrier, tdFor vehicle from
Start the time that braking stops to it.
From speed control model as can be seen that main vehicle in barriers to entry object coverage after, speed can with obstacle
The reduction of object distance and reduce, when vehicle cut-through object, speed increases with the increase of vehicle and obstacle distance, works as master
When vehicle is driven out to the coverage of barrier, speed will be no longer by the control from model.
The calculated avoidance path matlab is imported in vehicle dynamics simulation software carsim, it is available such as Fig. 9
With simulation curve shown in Fig. 10；Wherein Fig. 9 is that path follows curve, and zone circle curve is the true of main vehicle in simulation software in figure
Driving path, zone circle curve is not destination path, to solve obtained path；It can be seen from the figure that two curves are kissed substantially
It closes, illustrates in carsim simulation software, main vehicle is along the avoidance route being calculated, while this alternatively bright emulation
The various dynamic informations of main vehicle of process are consistent with the status information of main vehicle avoidance process in reality.Each model ginseng in simulation process
Number is shown in Table 2.
2 simulation parameters of table
| Variable | Numerical value | Unit |
| KL | 900 | -- |
| KR | 100 | -- |
| Koj | 1500 | -- |
| λ | 2.5 | -- |
| l0 | 1.25 | m |
| ρ0 | 10 | m |
| L | 180 | m |
| B | 7 | m |
| D | 4 | m |
Figure 10 and Figure 11 is the yaw velocity and side acceleration figure during main vehicle avoidance.As can be seen that two figures
Variation tendency is roughly the same, this illustrates that the yaw velocity of main vehicle and side acceleration become with the variation of main vehicle avoidance process
Change, only in the avoidance incipient stage, the pace of change of side acceleration is greater than yaw velocity.
The variation tendency of two figures reflects the entire avoidance process of main vehicle, and when beginning, main vehicle accelerates in the extremely short time
To preset vehicle speed, all there is biggish value in yaw velocity and side acceleration, as speed is increased to preset value, yaw angle
Speed and side acceleration only change to a very small extent, and until the 6th second or so, main vehicle started to delay close to front obstacle
Slow-speed is at 8.4 seconds or so, main vehicle yaw velocity and side acceleration all reached maximum value, illustrated that main vehicle arrived barrier
Hinder the positive side of object, i.e., will cut-through object, later, the value of yaw velocity and side acceleration becomes smaller, main vehicle gradually around
It crosses barrier and returns to former lane.
In Figure 10 and Figure 11, dotted line is the main vehicle yaw velocity obtained after avoidance process controls speed and side
To acceleration diagram, solid line is the main vehicle yaw velocity and side acceleration figure not controlled speed.Main vehicle is not
When in the coverage of barriers to entry object, two curves coincide substantially in figure, in the coverage of barriers to entry object after, can be with
, it is evident that the value of yaw velocity and side acceleration is not both less than to speed after avoidance process controls speed
The value controlled, and the value of side acceleration is less than 0.4g, this explanation controls speed in avoidance process can be effective
Improve comfort.
The foregoing is only a preferred embodiment of the present invention, is not intended to limit the scope of the present invention, should
Understand, the present invention is not limited to implementation as described herein, the purpose of these implementations description is to help this field
In technical staff practice the present invention.Any those of skill in the art are easy to do not departing from spirit and scope of the invention
In the case of be further improved and perfect, therefore the present invention is only by the content of the claims in the present invention and the limit of range
System, intention, which covers, all to be included the alternative in the spirit and scope of the invention being defined by the appended claims and waits
Same scheme.
Claims (5)
1. a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method, which is characterized in that including following step
It is rapid:
S1. road needed for acquiring vehicle obstacle-avoiding route planning in real time respectively using CCD camera, millimetre-wave radar, mobile unit
Road information, obstacle information, main vehicle information；
S2. after information needed for obtaining vehicle obstacle-avoidance path planning, path coordinate system is established in the investigative range of millimetre-wave radar,
Base is established according to road information, obstacle information, main vehicle information in the position that road boundary point, barrier, main vehicle are indicated with vector
In the road boundary repulsion potential field and barrier repulsion potential field model of Artificial Potential Field Method；It is specific as follows:
The foundation of S2.1 path coordinate system
Straight or approximate straight, width be B multiple-lane road on, according to millimetre-wave radar performance, in millimetre-wave radar can
In detection range L, road boundary is divided into n equal portions, the distance between each equal portions is L0=L/n；In the lane of main vehicle place
Heart line is x-axis, and subpoint of the main vehicle mass center on road surface is that origin establishes path coordinate system, it is assumed that in following each moment automobile
Mass center be located at road boundary and correspond on the line of Along ent, then each Along ent, barrier, main vehicle on the left and right boundary of road
Position can be represented by vectors out；
The foundation of S2.2 road boundary repulsion potential field
By CCD camera identification front lane boundary line and extract lane boundary line data, by boundary line data into
Row analysis processing extracts road information, then establishes road boundary repulsion potential field with this；
The foundation of S2.3 barrier repulsion potential field
Detect the obstacle information of main front side by millimetre-wave radar, onboard sensor obtains the velocity information of main vehicle, then with
This establishes barrier repulsion potential field；
S3. the effect for the power being subject in the Composite Field that road boundary repulsion potential field and barrier repulsion potential field form according to main vehicle
Equilibrium equation is established, and it is solved using mathematical software matlab to obtain the position to be passed through during avoidance of main vehicle
Point, to obtain avoidance path；
S4. the main vehicle speed during avoidance is controlled to improve safety, is reduced to main vehicle by speed in avoidance
One suitable value, and restore normal speed traveling after getting around barrier.
2. a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method according to claim 1,
It is characterized in that, in the S1, road information includes having a lot of social connections and lane quantity；Obstacle information include the number of barrier, size,
Position and speed；Main vehicle information include the speed of main vehicle, main vehicle at a distance from barrier, main vehicle at a distance from road boundary and
Angle of the main vehicle relative to barrier.
3. a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method according to claim 1,
It is characterized in that, in the establishment process of the S2.3 barrier repulsion potential field, main vehicle is equivalent to a particle, and with a diameter
Barrier is wrapped for the safety circle of D, meanwhile, in order to enable main vehicle to start avoidance in advance, assign one influence model of barrier
Enclose ρ0, as vehicle barriers to entry object coverage ρ0When, it will be only by the barrier repulsion gesture along path coordinate system y directional spreding
The effect of field, meanwhile, for the barrier of main front side movement, if the speed of barrier has speed point on main vehicle speed direction
Amount, then main vehicle also suffers from the repulsion effect of barrier velocity potential field.
4. a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method according to claim 1,
It is characterized in that, in the S3, is solved by equilibrium equation of the matlab to foundation, what is actually obtained is that certain following moment of main vehicle will
These to obtain main vehicle in the avoidance process each point to be passed through, then are put progress curve and intended by the ordinate for the point to be driven towards
It closes, to obtain the avoidance path that can make the safe cut-through object of main vehicle；Simultaneously as barrier is likely to be movement
, so Δ t at regular intervals, carries out path planning according to freshly harvested information, to guarantee real-time again.
5. a kind of vehicle obstacle-avoidance path planning research method based on novel artificial potential field method according to claim 1,
It being characterized in that, the S4 after main vehicle barriers to entry object coverage, controls main vehicle speed during main vehicle avoidance,
Main vehicle speed is set to reduce with the reduction of main vehicle and obstacle distance, after vehicle cut-through object, main vehicle speed can be with master
The increase of vehicle and obstacle distance and increase, when main vehicle is driven out to the coverage of barrier, main vehicle speed will be no longer by the mould
The control of type.
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Families Citing this family (41)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN115092183B (en) * | 2022-07-15 | 2024-04-09 | 东风柳州汽车有限公司 | Active obstacle avoidance control method and system for vehicle based on potential field force |
| CN115489548A (en) * | 2022-09-20 | 2022-12-20 | 重庆大学 | Intelligent automobile park road path planning method |
| CN117270575B (en) * | 2023-11-22 | 2024-01-30 | 中节能（新泰）太阳能科技有限公司 | Unmanned aerial vehicle inspection obstacle avoidance method for high-voltage line overhead area based on coordinate transformation |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102591332A (en) * | 2011-01-13 | 2012-07-18 | 同济大学 | Device and method for local path planning of pilotless automobile |
| CN103092204A (en) * | 2013-01-18 | 2013-05-08 | 浙江大学 | Mixed robot dynamic path planning method |
| CN103576686A (en) * | 2013-11-21 | 2014-02-12 | 中国科学技术大学 | Automatic guide and obstacle avoidance method for robot |
| WO2014075598A1 (en) * | 2012-11-13 | 2014-05-22 | Zhu Shaoming | Mobile robot separating visual positioning and navigation method and positioning and navigation system thereof |
| CN104317291A (en) * | 2014-09-16 | 2015-01-28 | 哈尔滨恒誉名翔科技有限公司 | Artificial-potential-field-based robot collision preventation path planning method |
| CN104317292A (en) * | 2014-09-16 | 2015-01-28 | 哈尔滨恒誉名翔科技有限公司 | Method for planning collision avoidance path of robot with complicated shape |
| CN104977933A (en) * | 2015-07-01 | 2015-10-14 | 吉林大学 | Regional path tracking control method for autonomous land vehicle |
-
2016
- 2016-05-11 CN CN201610309717.3A patent/CN105974917B/en not_active Expired - Fee Related
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102591332A (en) * | 2011-01-13 | 2012-07-18 | 同济大学 | Device and method for local path planning of pilotless automobile |
| WO2014075598A1 (en) * | 2012-11-13 | 2014-05-22 | Zhu Shaoming | Mobile robot separating visual positioning and navigation method and positioning and navigation system thereof |
| CN103092204A (en) * | 2013-01-18 | 2013-05-08 | 浙江大学 | Mixed robot dynamic path planning method |
| CN103576686A (en) * | 2013-11-21 | 2014-02-12 | 中国科学技术大学 | Automatic guide and obstacle avoidance method for robot |
| CN104317291A (en) * | 2014-09-16 | 2015-01-28 | 哈尔滨恒誉名翔科技有限公司 | Artificial-potential-field-based robot collision preventation path planning method |
| CN104317292A (en) * | 2014-09-16 | 2015-01-28 | 哈尔滨恒誉名翔科技有限公司 | Method for planning collision avoidance path of robot with complicated shape |
| CN104977933A (en) * | 2015-07-01 | 2015-10-14 | 吉林大学 | Regional path tracking control method for autonomous land vehicle |
Non-Patent Citations (2)
| Title |
|---|
| 基于改进人工势场法的智能无人车路径规划仿真研究;刘洲洲;《计算技术与自动化》;20130630;第32卷(第2期);第133-136页 * |
| 智能车辆车道保持系统中避障路径规划;汪明磊;《合肥工业大学学报》;20140228;第37卷(第2期);第129-133页 * |
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