CN109001976A - A kind of two-way collaboration of automatic Pilot vehicle can open up crosswise joint method - Google Patents
A kind of two-way collaboration of automatic Pilot vehicle can open up crosswise joint method Download PDFInfo
- Publication number
- CN109001976A CN109001976A CN201810927572.2A CN201810927572A CN109001976A CN 109001976 A CN109001976 A CN 109001976A CN 201810927572 A CN201810927572 A CN 201810927572A CN 109001976 A CN109001976 A CN 109001976A
- Authority
- CN
- China
- Prior art keywords
- open
- follows
- deviation
- vehicle
- circle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
- Steering Control In Accordance With Driving Conditions (AREA)
Abstract
The two-way collaboration that the present invention discloses a kind of automatic Pilot vehicle can open up crosswise joint method, comprising the following steps: suggest two degrees of freedom kinetic model, establish track following and take aim at error model, feature extraction and domain circle in advance and divide, calculate two-way correlation function and control system exports.The present invention chooses lateral position deviation and course deviation as extension controller characteristic quantity respectively, and establish two Region place values, the division of domain circle is carried out to Region place value, Classical field, extension range and three, non-domain region are divided into two Region place values respectively, then two correlation function values are calculated by vehicle-roadnet real-time characteristic amount, each real-time characteristic quantity of state is categorized into each region based on correlation function value, output two-way front wheel angle output valve is calculated separately based on this, realizes that two-way extension controller coordinates output finally by weight coefficient is coordinated.
Description
Technical field
The invention belongs to automatic driving control technologies, and in particular to a kind of two-way collaboration of automatic Pilot vehicle can open up cross
To control method.
Background technique
For the requirement for meeting safe and efficient intelligent traffic development, autonomous driving vehicle is as its important carrier and mainly
Research object, especially electronic autonomous driving vehicle are asked for improving environmental pollution, raising energy utilization rate, improving traffic congestion
Topic has great role.Therefore, under different kinds of roads operating condition, vehicle lateral control precision and safety become certainly automatic driving vehicle
It is dynamic to drive a part important in vehicle control.
Automatic driving vehicle be based on common vehicle platform, framework computer, visual sensor, automatically control executing agency with
And signal communication equipment, realization independently perceive, make decisions on one's own and independently execute operational motion and guarantee safety traffic function.It is common from
The dynamic vehicle that drives is mostly front-wheel drive, guarantees the safety of vehicle lateral control precision and vehicle driving by adjusting front wheel angle
Stability.
From many automatic driving vehicle athletic competitions it is not difficult to find out that, at present automatic driving vehicle difficult point the most main it
First is that the safety and reliability under the high dynamics such as high speed bend operating condition.Statistics indicate that when car speed is more than 50km/h, tracking
When path curvatures radius is greater than 75m, maximum transversal position deviation is difficult to ensure less than 0.1m, is driven automatically under some bad working environments
Sailing vehicle will appear unstable or out-of-control phenomenon.
There are mainly two types of crosswise joints: in advance take aim at formula frame of reference and it is non-it is pre- take aim at formula frame of reference, take aim at formula frame of reference master in advance
Will using the road curvature of vehicle front position as input, according between vehicle and expected path lateral deviation or course deviation
To control target, by the design of various feedbacks to the feedback control system of Vehicle dynamic parameters robust, such as it is based on
The frame of reference of the visual sensors such as radar or camera.Non- pre- formula frame of reference of taking aim at is led to according to the expected path near vehicle
The physical quantity that vehicle kinematics model calculates description vehicle movement is crossed, such as yaw rate, then design of feedback controls
System is tracked.
There is presently no the prior arts to be given to vehicle-roadnet real-time state monitoring, and based on real-time status characteristic
Out controller export, cause deep camber and when variable curvature under tracing control precision it is not high, it is difficult to meet automatic driving vehicle height
Dynamic real-time demand for control.
Summary of the invention
Goal of the invention: it is an object of the invention to solve the deficiencies in the prior art, a kind of automatic Pilot vehicle is provided
Two-way collaboration can open up crosswise joint method.
Technical solution: a kind of two-way collaboration of automatic Pilot vehicle of the invention can open up crosswise joint method, including following step
It is rapid:
(1) suggest two degrees of freedom kinetic model；
(2) suggest that track following takes aim at error model in advance；
(3) feature extraction and domain circle divide；
(4) two-way correlation function is calculated；
(5) control system exports.
Further, two degrees of freedom kinetic model in the step (1) are as follows:
Vehicle two degrees of freedom kinetic model math equation can indicate are as follows:
Wherein, whole vehicle quality is M, and vehicle is I around the rotary inertia of mass center (CG) z-axisz, wheel base is from mass center
Distance respectively lfAnd lr, vxAnd vyRespectively for vehicle along the longitudinal velocity and side velocity of x-axis and y-axis, β and r are respectively mass center
Side drift angle and yaw velocity, Fyfl、Fyfr、FyrlAnd FyrrThe lateral force that respectively four wheels are subject to；
Fyf、FyfThe respectively resulting side force that is subject to of front axle and rear axle tire, is expressed as Fyf=Fyfl+Fyfr、Fyr=Fyrl+
Fyrr, front wheel angle δfAdjust vehicle heading, δfFor the input parameter of vehicle two-freedom model, it is assumed herein that longitudinal direction of car
Speed vxSide drift angle for constant, left and right wheels is identical, IzFor around the rotary inertia of mass center；
Front and back side force of tire Fyf、FyrWith front and back wheel slip angle of tire αf、αrRelationship are as follows:
Fyf(t)=cfαf(t) Fyr(t)=crαr(t) (2)
Wherein, cf、crFor front and back tire cornering stiffness, in tire working when linear zone, value is definite value；
Front and back slip angle of tire αf、αrIt indicates are as follows:
Formula (2) and (3) are substituted into formula (1), equation is obtained:
Wherein,
Write as state space equation form:
Quantity of state x=[β, r]T, and
Further, track following takes aim at error model in advance in the step (2) are as follows:
In formula, evFor the lateral distance for arriving reference locus at taking aim in advance, lateral position deviation is as taken aim in advance；L is vehicle matter
Heart CG is to the distance taken aim in advance a little；Course angle at being taken aim in advance for reference locus,For vehicle course angle, definition
For course deviation；；For the curvature of reference locus, R is road curve radius.
Further, the detailed process that Characteristic Extraction and domain circle divide in the step (3) are as follows:
(3.1) lateral position Dian Chu deviation e is taken aim in extension controller selection in advancevAnd course deviationAs characteristic quantity, and lead to
Cross the deviation and deviation differential building Region place value of the twoWith
(3.2) by lateral position deviation Region place valueWith course deviation Region place valueIt is divided into
Three regions: Classical field, extension range and non-domain；Setting vehicle-roadnet be in controllable state, state and uncontrollable is adjusted
State processed；Then two-way Region place value domain circle is defined are as follows:
Lateral position deviation Classical field circle are as follows:
Lateral position deviation extension range circle are as follows:
Course deviation Classical field circle are as follows:
Course deviation extension range circle are as follows:
Further, the step (4) according to taking aim at a lateral position deviation extendible set chalaza in advance under real-time statusWith course deviation extendible set chalazaWith optimum point S0(0,0) open up away from | SeS0|、And
Classical field circle and extension range circle can be opened up away from the two correlation function is calculated, as
Wherein, the lateral position Dian Chu deviation is taken aim in advanceWith optimum point S0(0,0) weighting can open up away from are as follows:
Course deviationWith optimum point S0(0,0) weighting can open up away from for
Lateral position deviation Classical field circle can open up away from for
Lateral position deviation extension range circle can open up away from for
Course deviation Classical field circle can open up away from for
Course deviation extension range circle can open up away from for
Further, in the step (5) control system output method are as follows:
(5.1) according to two-way correlation function to system character evWithCarry out pattern-recognition；
(5.2) it based on the pattern-recognition to real-time characteristic amount, is rotated before using corresponding controller under corresponding mode
Angle output valve；
(5.3) it is based on characteristic quantity evAnd characteristic quantityIt is coordinated phase by weight by the front wheel angle output valve determined
Add mode obtains the front wheel angle input δ of vehicle dynamic modelf。
Further, mode identification procedure in the step (5.1) are as follows:
IF Ke(Se)≥0,THENMeasure models Me1；
IF -1≤Ke(Se)<0,THENMeasure models Me2；
ELSE measure models Me3.
And
Measure models
Measure models
ELSE measure models
Further, characteristic quantity e in the step (5.2)vController front wheel angle output valve under corresponding modes are as follows:
When measure models are Me1When, vehicle-roadnet is in stable state, at this time controller front wheel angle output valve
Are as follows: δe=-kCMe1ev (19)
Wherein, kCMe1For measure models Me1Based on characteristic quantity evState feedback factor, for example, by using pole-assignment
Selection state feedback factor；According to vehicle dynamic model front wheel angle δfAnd a lateral position deviation e is taken aim in advancevTransmission function is led to
Crossing in MATLAB orders [K, r]=rlocfind (num, den) to obtain state feedback factor, and ties according to response on this basis
Fruit is to small parameter perturbations.
When measure models are Me2When, vehicle-roadnet is in slight instability status, belongs in adjustable extent, passes through increasing
Add controller to add output item, vehicle-roadnet readjusted into stable state, controller front wheel angle output valve are as follows:
δe=-kCMe1ev+kCMe2Ke(Se)[-sgn(ev)] (20)
kCMe2For measure models Me2Additional output item control coefrficient down, the coefficient are based on measure models Me1Lower control amount is appropriate
Manual adjustment guarantees that additional output item enables to vehicle-roadnet to return to stable state herein.
Wherein,
kCMe2Ke(Se)[-sgn(ev)] it is that controller adds output item, this combines correlation function value Ke(Se), it is associated with letter
Number, can intuitively embody vehicle-roadnet stable distance region adjusting difficulty, therefore, by the variation of correlation function value,
Change the value that controller adds output item in real time according to control difficulty.
When measure models are Me3When, vehicle-road model can not adjust stable state in time, be since deviation is larger
Guarantee vehicle safety, at this time controller front wheel angle output valve are as follows:
δe=0 (22)
Measure models Me3It should be avoided as far as possible in control process.
In conclusion for characteristic quantity evController front wheel angle output valve are as follows:
Solve characteristic quantityController front wheel angle output valve are as follows:
Further, features described above amount e is based in the step (5.3)vAnd characteristic quantityThe front wheel angle determined is defeated
It is worth out, it is coordinated into phase add mode by weight and obtains the front wheel angle input δ of vehicle dynamic modelf。
Wherein, keThe amount of being characterized evController front wheel angle output valve cooperation index,The amount of being characterizedController front-wheel
Corner output valve cooperation index.
The utility model has the advantages that the present invention is reached using a kind of method for being expanded controller output result in real time based on change of error
Error is guaranteed into the effect in lower range, it therefore, can be by extension control approach application to automatic driving vehicle crosswise joint system
System guarantees high tracking accuracy during vehicle movement.Automatic driving vehicle crosswise joint target guarantees lateral position deviation and boat
Small as far as possible to deviation, in order to realize control target, creative design two-way extension control system, chooses horizontal respectively herein
To position deviation and course deviation as extension controller characteristic quantity, and two Region place values are established, domain is carried out to Region place value
Boundary divides, and entire Region place value is divided into Classical field, extension range and three, non-domain region.It is real-time by vehicle-roadnet
Characteristic quantity calculates correlation function value, each real-time characteristic quantity of state is categorized into each region based on correlation function value, base
Output two-way front wheel angle output valve is calculated separately in this, realizes that two-way extension controller is coordinated finally by weight coefficient is coordinated
Output.
Detailed description of the invention
Fig. 1 is flow chart of the invention；
Fig. 2 is two degrees of freedom vehicle dynamic model of the invention；
Fig. 3 is that track following of the invention takes aim at error model in advance；
Fig. 4 is two-way Region place value zoning plan of the invention；
Fig. 5 is two-way correlation function computing module schematic diagram of the invention；
Fig. 6 is correlation function and domain circle relational graph of the invention；
Fig. 7 is feasibility simulating, verifying figure in embodiment；
Fig. 8 is double lane change operating condition track following result figures of embodiment；
Wherein, Fig. 8 (a) is whole track following schematic diagram；Fig. 8 (b) is the partial schematic diagram of the box in Fig. 8 (a).
Specific embodiment
Technical solution of the present invention is described in detail below, but protection scope of the present invention is not limited to the implementation
Example.
As shown in Figure 1, a kind of two-way collaboration of automatic Pilot vehicle of the invention can open up crosswise joint method, including following step
It is rapid:
(1) suggest two degrees of freedom kinetic model；As shown in Figure 1,
Vehicle two degrees of freedom kinetic model math equation indicates are as follows:
Wherein, whole vehicle quality is M, and vehicle is I around the rotary inertia of mass center (CG) z-axisz, wheel base is from mass center
Distance respectively lfAnd lr, vxAnd vyRespectively for vehicle along the longitudinal velocity and side velocity of x-axis and y-axis, β and r are respectively mass center
Side drift angle and yaw velocity, Fyfl、Fyfr、FyrlAnd FyrrThe lateral force that respectively four wheels are subject to；
Fyf、FyrThe respectively resulting side force that is subject to of front axle and rear axle tire, is expressed as Fyf=Fyfl+Fyfr、Fyr=Fyrl+
Fyrr, front wheel angle δfAdjust vehicle heading, δfFor the input parameter of vehicle two-freedom model, it is assumed herein that longitudinal direction of car
Speed vxSide drift angle for constant, left and right wheels is identical, IzFor around the rotary inertia of mass center；
Front and back side force of tire Fyf、FyrWith front and back wheel slip angle of tire αf、αrRelationship are as follows:
Fyf(t)=cfαf(t) Fyr(t)=crαr(t) (2)
Wherein, cf、crFor front and back tire cornering stiffness, in tire working when linear zone, value is definite value；
Front and back slip angle of tire αf、αrIt indicates are as follows:
Formula (5) and (6) are substituted into formula (4), equation is obtained:
Wherein,
Write as state space equation form:
Quantity of state x=[β, r]T, and
(2) suggest that track following takes aim at error model in advance；
The model as shown in Figure 3 are as follows:
In formula, evFor the lateral distance for arriving reference locus at taking aim in advance, lateral position deviation is as taken aim in advance；L is vehicle matter
Heart CG is to the distance taken aim in advance a little；Course angle at being taken aim in advance for reference locus,For vehicle course angle, definitionFor
Course deviation；ρ is the curvature of reference locus, is the inverse of road curve radius；
(3) feature extraction and domain circle divide:
(3.1) lateral position Dian Chu deviation e is taken aim in extension controller selection in advancevAnd course deviationAs characteristic quantity, and lead to
Cross the deviation and the building of deviation differential of the twoWith
(3.2) as shown in figure 4, by lateral position deviation Region place valueWith course deviation Region place valueIt is divided into three regions: Classical field, extension range and non-domain；Setting vehicle-roadnet be in controllable state, can
Adjustment state and uncontrollable state；Then it is as follows to define two-way Region place value domain circle:
Lateral position deviation Classical field circle are as follows:
Lateral position deviation extension range circle are as follows:
Course deviation Classical field circle are as follows:
Course deviation extension range circle are as follows:
(4) two-way correlation function is calculated:
As shown in figure 5, according to a lateral position deviation extendible set chalaza is taken aim under real-time status in advanceIt is inclined with course
Poor extendible set chalazaWith optimum point S0(0,0) open up away from | SeS0|、And Classical field circle and extension range
Boundary can be opened up away from the two correlation function is calculated, as
Wherein, the lateral position Dian Chu deviation is taken aim in advanceWith optimum point S0(0,0) weighting can open up away from are as follows:
Course deviationWith optimum point S0(0,0) weighting can open up away from for
Lateral position deviation Classical field circle can open up away from for
Lateral position deviation extension range circle can open up away from for
Course deviation Classical field circle can open up away from for
Course deviation extension range circle can open up away from for
(5) control system exports:
(5.1) as shown in fig. 6, according to two-way correlation function to system character evWithCarry out pattern-recognition；
(5.2) it based on the pattern-recognition to real-time characteristic amount, is rotated before using corresponding controller under corresponding mode
Angle output valve；
(5.3) it is based on characteristic quantity evAnd characteristic quantityIt is coordinated phase by weight by the front wheel angle output valve determined
Add mode obtains the front wheel angle input δ of vehicle dynamic modelf。
Wherein, mode identification procedure in step (5.1) are as follows:
IF Ke(Se)≥0,THENMeasure models Me1；
IF -1≤Ke(Se)<0,THENMeasure models Me2；
ELSE measure models Me3.
And
Measure models
Measure models
ELSE measure models
Characteristic quantity e in above-mentioned steps (5.2)vController front wheel angle output valve under corresponding modes are as follows:
When measure models are Me1When, vehicle-roadnet is in stable state, at this time controller front wheel angle output valve
Are as follows: δe=-kCMe1ev (19)
Wherein, kCMe1For measure models Me1Based on characteristic quantity evState feedback factor, for example, by using pole-assignment
Selection state feedback factor；According to vehicle dynamic model front wheel angle δfAnd a lateral position deviation e is taken aim in advancevTransmission function is led to
Crossing in MATLAB orders [K, r]=rlocfind (num, den) to obtain state feedback factor, and ties according to response on this basis
Fruit is to small parameter perturbations.
When measure models are Me2When, vehicle-roadnet is in slight instability status, belongs in adjustable extent, passes through increasing
Add controller to add output item, vehicle-roadnet readjusted into stable state, controller front wheel angle output valve are as follows:
δe=-kCMe1ev+kCMe2Ke(Se)[-sgn(ev)] (20)
kCMe2For measure models Me2Additional output item control coefrficient down, the coefficient are based on measure models Me1Lower control amount is appropriate
Manual adjustment guarantees that additional output item enables to vehicle-roadnet to return to stable state herein.
Wherein,
kCMe2Ke(Se)[-sgn(ev)] it is that controller adds output item, this combines correlation function value Ke(Se), it is associated with letter
Number, can intuitively embody vehicle-roadnet stable distance region adjusting difficulty, therefore, by the variation of correlation function value,
Change the value that controller adds output item in real time according to control difficulty.
When measure models are Me3When, vehicle-road model can not adjust stable state in time, be since deviation is larger
Guarantee vehicle safety, at this time controller front wheel angle output valve are as follows:
δe=0 (22)
Measure models Me3It should be avoided as far as possible in control process.
In conclusion for characteristic quantity evController front wheel angle output valve are as follows:
Solve characteristic quantityController front wheel angle output valve are as follows:
Features described above amount e is based in the step (5.3)vAnd characteristic quantityThe front wheel angle output valve determined, by it
Coordinate phase add mode by weight and obtains the front wheel angle input δ of vehicle dynamic modelf。
Wherein, keThe amount of being characterized evController front wheel angle output valve cooperation index,The amount of being characterizedController front-wheel
Corner output valve cooperation index.
Embodiment:
This implementation is based on MATLAB (Simulink)-Carsim platform, builds feasibility Simulation Model, the present embodiment
Two-way collaboration can open up crosswise joint method feasibility simulating, verifying frame as shown in fig. 7, and verifying this hair by two kinds of operating conditions
The two-way collaboration of bright proposition can open up the validity and stability of crosswise joint system, use operating condition for double lane change paths, vehicle
Speed selects 100km/h, 110km/h and 120km/h.Each parameter value adjusting is as follows in control method:
Preview distance L=15m in track following error model；Road-adhesion coefficient μ=1.0；Vehicular longitudinal velocity vxFor
Constant；Two-way extension controller front wheel angle output coordinating coefficient ke=0.471, becauseSo
For characteristic setIts Classical field circle RecWith extension range circle ReeRespectively
For characteristic setIts Classical field circleWith extension range circleRespectively
According to zero-pole assignment method, measure models M in double collaboration extension control systems is determinede1WithUnder, state is anti-
Feedforward coefficient kCMe1=50.12,Measure models Me2WithUnder, add output item control coefrficient kCMe2=
0.01,
As shown in figure 8, response results find that double collaborations of the invention can open up under high-speed working condition according to double secondary lane change operating conditions
Crosswise joint system variable curvature road tracking accuracy with higher in high speed, control method good reliability.
Claims (9)
1. a kind of two-way collaboration of automatic Pilot vehicle can open up crosswise joint method, it is characterised in that: the following steps are included:
(1) two degrees of freedom kinetic model is established；
(2) it establishes track following and takes aim at error model in advance；
(3) feature extraction and domain circle divide；
(4) two-way correlation function is calculated；
(5) control system exports.
2. the two-way collaboration of automatic Pilot vehicle according to claim 1 can open up crosswise joint method, it is characterised in that: described
Two degrees of freedom kinetic model in step (1) are as follows:
Vehicle two degrees of freedom kinetic model math equation indicates are as follows:
Wherein, whole vehicle quality is M, and vehicle is I around the rotary inertia of mass center (CG) z-axisz, wheel base is with a distance from mass center
Respectively lfAnd lr, vxAnd vyRespectively for vehicle along the longitudinal velocity and side velocity of x-axis and y-axis, β and r are respectively mass center lateral deviation
Angle and yaw velocity, Fyfl、Fyfr、FyrlAnd FyrrThe lateral force that respectively four wheels are subject to；
Fyf、FyrThe respectively resulting side force that is subject to of front axle and rear axle tire, is expressed as Fyf=Fyfl+Fyfr、Fyr=Fyrl+Fyrr, preceding
Take turns corner δfAdjust vehicle heading, δfFor the input parameter of vehicle two-freedom model；
Front and back side force of tire Fyf、FyrWith front and back wheel slip angle of tire αf、αrRelationship are as follows:
Fyf(t)=cfαf(t)Fyr(t)=crαr(t) (2)
Wherein, cf、crFor front and back tire cornering stiffness, in tire working when linear zone, value is definite value；
Front and back slip angle of tire αf、αrIt indicates are as follows:
Formula (2) and (3) are substituted into formula (1), equation is obtained:
Wherein,
Write as state space equation form:
Quantity of state x=[β, r]T, and
3. the two-way collaboration of automatic Pilot vehicle according to claim 1 can open up crosswise joint method, it is characterised in that: described
Track following takes aim at error model in advance in step (2) are as follows:
In formula, evFor the lateral distance for arriving reference locus at taking aim in advance, lateral position deviation is as taken aim in advance；L is that vehicle centroid CG is arrived
Distance a little is taken aim in advance；Course angle at being taken aim in advance for reference locus,For vehicle course angle, definitionIt is inclined for course
Difference；For the curvature of reference locus, R is road curve radius.
4. the two-way collaboration of automatic Pilot vehicle according to claim 1 can open up crosswise joint method, it is characterised in that: described
The detailed process that Characteristic Extraction and domain circle divide in step (3) are as follows:
(3.1) lateral position Dian Chu deviation e is taken aim in extension controller selection in advancevAnd course deviationBoth as characteristic quantity, and pass through
Deviation and deviation differential construct Region place valueWith
(3.2) by lateral position deviation Region place valueWith course deviation Region place valueIt is divided into three areas
Domain: Classical field, extension range and non-domain；Setting vehicle-roadnet is in controllable state, adjustable state and uncontrollable shape
State；Then two-way Region place value domain circle is defined are as follows:
Lateral position deviation Classical field circle are as follows:
Lateral position deviation extension range circle are as follows:
Course deviation Classical field circle are as follows:
Course deviation extension range circle are as follows:
5. the two-way collaboration of the automatic Pilot vehicle according to claim can open up crosswise joint method, it is characterised in that: described
Step (4) according to taking aim at a lateral position deviation extendible set chalaza in advance under real-time statusWith course deviation extendible set chalazaWith optimum point S0(0,0) open up away from | SeS0|、And Classical field circle and extension range circle can be opened up away from calculating
The two correlation function, as
Wherein, the lateral position Dian Chu deviation and deviation differential are taken aim in advanceWith optimum point S0(0,0) weighting can open up away from are as follows:
Course deviationWith optimum point S0(0,0) weighting can open up away from for
Lateral position deviation Classical field circle can open up away from for
Lateral position deviation extension range circle can open up away from for
Course deviation Classical field circle can open up away from for
Course deviation extension range circle can open up away from for
6. the two-way collaboration of automatic Pilot vehicle according to claim 1 can open up crosswise joint method, it is characterised in that: described
The output method of control system in step (5) are as follows:
(5.1) according to two-way correlation function to system character evWithCarry out pattern-recognition；
(5.2) defeated using corresponding controller front wheel angle under corresponding mode based on the pattern-recognition to real-time characteristic amount
It is worth out；
(5.3) it is based on characteristic quantity evAnd characteristic quantityIt is coordinated phase add mode by weight by the front wheel angle output valve determined
Obtain the front wheel angle input δ of vehicle dynamic modelf。
7. the two-way collaboration of automatic Pilot vehicle according to claim 6 can open up crosswise joint method, it is characterised in that: described
Mode identification procedure in step (5.1) are as follows:
IF Ke(Se)≥0,THENThen measure models Me1；
IF -1≤Ke(Se)<0,THENThen measure models Me2；
ELSE measure models Me3.
And
IFTHENThen measure models
THENThen measure models
ELSE measure models
8. the two-way collaboration of automatic Pilot vehicle according to claim 6 can open up crosswise joint method, it is characterised in that: described
Characteristic quantity e in step (5.2)vController front wheel angle output valve are as follows:
Characteristic quantityController front wheel angle output valve are as follows:
Wherein, kCMe1For measure models Me1Based on characteristic quantity evState feedback factor；kCMe2For measure models Me2Lower additional output
Item control coefrficient,KCMe2Ke(Se)[-sgn(ev)] it is that controller adds output item.
9. the two-way collaboration of automatic Pilot vehicle according to claim 6 can open up crosswise joint method, it is characterised in that: described
Characteristic quantity e is based in step (5.3)vAnd characteristic quantityIt is coordinated to be added by the front wheel angle output valve determined by weight
Mode obtains the front wheel angle input δ of vehicle dynamic modelf；
Wherein, keThe amount of being characterized evController front wheel angle output valve cooperation index,The amount of being characterizedController front wheel angle is defeated
It is worth cooperation index out.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810927572.2A CN109001976B (en) | 2018-08-15 | 2018-08-15 | Double-path cooperative extension transverse control method for automatic driving vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810927572.2A CN109001976B (en) | 2018-08-15 | 2018-08-15 | Double-path cooperative extension transverse control method for automatic driving vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109001976A true CN109001976A (en) | 2018-12-14 |
| CN109001976B CN109001976B (en) | 2021-04-02 |
Family
ID=64592923
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810927572.2A Active CN109001976B (en) | 2018-08-15 | 2018-08-15 | Double-path cooperative extension transverse control method for automatic driving vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109001976B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111674386A (en) * | 2020-05-15 | 2020-09-18 | 武汉科技大学 | Vehicle coordination control method and device based on AFS and DYC and storage medium |
| CN112835292A (en) * | 2020-12-31 | 2021-05-25 | 天津大学 | Transverse control method of automatic driving electric vehicle on rugged road |
| CN113848953A (en) * | 2021-10-25 | 2021-12-28 | 济南大学 | Unmanned path tracking control method for large hydraulic plant protection machine |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080112179A1 (en) * | 2006-11-13 | 2008-05-15 | Koito Manufacturing Co., Ltd. | Lighting device for vehicle |
| US20140336789A1 (en) * | 2013-05-13 | 2014-11-13 | Massachusetts Institute Of Technology | Controlling dynamical systems with bounded probability of failure |
| CN106915271A (en) * | 2017-03-08 | 2017-07-04 | 江苏大学 | A kind of intelligent electric bus and its wireless charging platform |
| CN107200020A (en) * | 2017-05-11 | 2017-09-26 | 江苏大学 | It is a kind of based on mix theory pilotless automobile self-steering control system and method |
| CN107264534A (en) * | 2017-05-23 | 2017-10-20 | 北京理工大学 | Intelligent driving control system and method, vehicle based on driver experience's model |
| CN108216231A (en) * | 2018-01-12 | 2018-06-29 | 合肥工业大学 | One kind can open up united deviation auxiliary control method based on steering and braking |
-
2018
- 2018-08-15 CN CN201810927572.2A patent/CN109001976B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080112179A1 (en) * | 2006-11-13 | 2008-05-15 | Koito Manufacturing Co., Ltd. | Lighting device for vehicle |
| US20140336789A1 (en) * | 2013-05-13 | 2014-11-13 | Massachusetts Institute Of Technology | Controlling dynamical systems with bounded probability of failure |
| CN106915271A (en) * | 2017-03-08 | 2017-07-04 | 江苏大学 | A kind of intelligent electric bus and its wireless charging platform |
| CN107200020A (en) * | 2017-05-11 | 2017-09-26 | 江苏大学 | It is a kind of based on mix theory pilotless automobile self-steering control system and method |
| CN107264534A (en) * | 2017-05-23 | 2017-10-20 | 北京理工大学 | Intelligent driving control system and method, vehicle based on driver experience's model |
| CN108216231A (en) * | 2018-01-12 | 2018-06-29 | 合肥工业大学 | One kind can open up united deviation auxiliary control method based on steering and braking |
Non-Patent Citations (3)
| Title |
|---|
| 汪洪波: "基于功能分配的汽车底盘集成系统协调控制与稳定性分析", 《中国博士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 袁朝春 等: "Design and Analysis of an Autobraking System Controller for Autonomous Vehicles Under the Influence of Perturbation", 《IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY》 * |
| 陈无畏 等: "基于可拓决策和人工势场法的车道偏离辅助系统研究", 《机械工程学报》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111674386A (en) * | 2020-05-15 | 2020-09-18 | 武汉科技大学 | Vehicle coordination control method and device based on AFS and DYC and storage medium |
| CN112835292A (en) * | 2020-12-31 | 2021-05-25 | 天津大学 | Transverse control method of automatic driving electric vehicle on rugged road |
| CN112835292B (en) * | 2020-12-31 | 2024-03-08 | 天津大学 | Transverse control method of automatic driving electric vehicle on rugged road |
| CN113848953A (en) * | 2021-10-25 | 2021-12-28 | 济南大学 | Unmanned path tracking control method for large hydraulic plant protection machine |
| CN113848953B (en) * | 2021-10-25 | 2023-12-08 | 济南大学 | Unmanned path tracking control method for large-scale hydraulic plant protection machine |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109001976B (en) | 2021-04-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110187639B (en) | Trajectory planning control method based on parameter decision framework | |
| CN108454623B (en) | A kind of unmanned electric vehicle Trajectory Tracking Control method of four motorized wheels | |
| CN109606368B (en) | Intelligent automobile extension vehicle speed self-adaptive change trajectory tracking control method | |
| CN106218638B (en) | Intelligent network-connected automobile cooperative lane change control method | |
| CN109131325B (en) | Lane keeping control method for three-dimensional extension preview switching of intelligent driving automobile | |
| CN110827535B (en) | Nonlinear vehicle queue cooperative self-adaptive anti-interference longitudinal control method | |
| CN110001637A (en) | A kind of pilotless automobile path following control device and control method based on multiple spot tracking | |
| CN109606363B (en) | Multi-state feedback intelligent automobile extension lane keeping control method | |
| CN113276848B (en) | Intelligent driving lane changing and obstacle avoiding track planning and tracking control method and system | |
| CN107856737B (en) | A kind of man-machine coordination rotating direction control method based on degree of danger variable weight | |
| CN106671982A (en) | Multi-intelligent agent based unmanned electric car automatic overtaking system and method | |
| CN109001976A (en) | A kind of two-way collaboration of automatic Pilot vehicle can open up crosswise joint method | |
| CN109144076A (en) | A kind of more vehicle transverse and longitudinals coupling cooperative control system and control method | |
| CN107015477A (en) | Vehicle route tracking H ∞ control methods based on feedback of status | |
| CN108791491A (en) | Vehicle lateral tracking control method based on self-evaluation learning | |
| CN108646763A (en) | A kind of autonomous driving trace tracking and controlling method | |
| CN103760908B (en) | A kind of rover Closed loop track control method | |
| CN108569336A (en) | Vehicle kinematics model rotating direction control method is based under Dynamic Constraints | |
| CN108227491A (en) | A kind of intelligent vehicle Trajectory Tracking Control method based on sliding formwork neural network | |
| CN109664884A (en) | A kind of adaptive lane of opening up under variable speed keeps prosecutor method | |
| CN112068445B (en) | Integrated control method and system for path planning and path tracking of automatic driving vehicle | |
| CN104881030A (en) | Unmanned vehicle-side longitudinal coupling tracking control method based on rapid terminal sliding mode principle | |
| CN108944943A (en) | A kind of bend following-speed model based on risk shifting balance theory | |
| CN207328574U (en) | A kind of intelligent automobile Trajectory Tracking Control System based on active safety | |
| CN108919837A (en) | A kind of dynamic (dynamical) automatic driving vehicle Second Order Sliding Mode Control method of view-based access control model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |