CN103640622B - A kind of automobile steering intelligent control method based on pilot model and control system - Google Patents
A kind of automobile steering intelligent control method based on pilot model and control system Download PDFInfo
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- CN103640622B CN103640622B CN201310565397.4A CN201310565397A CN103640622B CN 103640622 B CN103640622 B CN 103640622B CN 201310565397 A CN201310565397 A CN 201310565397A CN 103640622 B CN103640622 B CN 103640622B
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Abstract
The invention discloses a kind of automobile steering intelligent control method based on pilot model.The position that after first the inventive method takes aim at the period L EssT.LTssT.LTi>T</iGreatT.Gre aT.GT moment in advance according to the prediction of automobile current operating conditions, automobile can arrive, and compare with the target location after the <i>T</iGreatT.Gr eaT.GT moment, obtain both deviations, the ratio of both deviations and <i>T</iGreatT.Gr eaT.GT is the automobile cross velocity of expectation, again the automobile cross velocity of expectation and actual automobile cross velocity are compared, the automobile cross velocity obtaining expecting is poor, then calculate steering wheel angle, and according to the steering wheel angle obtained, vehicle steering is controlled.The invention also discloses a kind of automobile steering intelligent control system based on pilot model, comprise and take aim at module, prediction module, comparison module, computing module and control module in advance.Compared to existing technology, the pilot model that the present invention sets up, its parameter is directly obtained by whole-car parameters, has that parameter is simple, physical meaning advantage clearly, to the control of automobile more accurately and true.
Description
Technical field
The present invention relates to a kind of automobile intelligent control method, particularly relate to a kind of automobile steering intelligent control method based on pilot model and control system, belong to automatic control technology field.
Background technology
Along with the progress of science and technology and the raising of social level, the demand of people to automobile is increasing, and the owning amount of private car rises year by year, has caused traffic safety problem thus and has also become increasingly conspicuous.This situation is particularly evident in China, and China leaps to the whole world first for continuous ten years because of the number of traffic accidents death.Therefore, automotive safety sex chromosome mosaicism becomes most important.
For transport solution safety problem, not only need the formulation paying close attention to various traffic safety code, to the research of intelligent transportation system, intelligent vehicle and other active safety technologies, also need the drive safety being used to improve automobile.And driver modeling is the basis of these researchs, set up one more accurately, more real pilot model not only may be used for intelligent vehicle, also may be used for the detection of vehicle handling stability.
In recent years, domestic and international researchist and scholar have carried out large quantity research to automobile driver model, successively propose several pilot model, the LQR model etc. of the people such as the optimal preview control model of such as MacAdam, the preview follower model of Guo Konghui and Cole.But pilot model comparatively conventional is both at home and abroad, the LQR model of the people such as the preview follower model of China Guo Konghui academician and external Cole.Preview follower model because of the physical meaning of its model parameter clear, be convenient to the mechanism of production understanding driving behavior, application is convenient.But it is when high speed steering, tracking accuracy is not high and occur turning to wave phenomenon, makes its application at high speeds have certain limitation; LQR model adopts optimization method, and theoretical rigorous, tracking accuracy is high.But its physical conception is unintelligible, adopt multipoint preview to cause optimizing calculated amount large, practical application difficulty simultaneously.
Summary of the invention
Technical matters to be solved by this invention is to overcome prior art deficiency, a kind of automobile steering intelligent control method based on pilot model and control system are provided, the parameter of the pilot model adopted directly is obtained by whole-car parameters, have that parameter is simple, physical meaning advantage clearly, to the control of automobile more accurately and true.
The present invention is concrete by the following technical solutions:
A kind of automobile steering intelligent control method based on pilot model, first the position that after taking aim at the cycle T moment in advance according to the prediction of automobile current operating conditions, automobile can arrive, and compare with the target location after the T moment, obtain both deviations, the ratio of both deviations and T is the automobile cross velocity of expectation, the automobile cross velocity of expectation and actual automobile cross velocity are compared, the automobile cross velocity obtaining expecting is poor again; Then obtain steering wheel angle according to following formula, and according to the steering wheel angle obtained, vehicle steering controlled:
θ(s)=e
vy(s)×G
d(s)
In formula, θ (s) represents steering wheel angle; e
vys () represents that the automobile cross velocity expected is poor; G
ds () is transfer function, obtain according to following formula:
Wherein, m is vehicle complete vehicle quality, and unit is kg; V is the speed of a motor vehicle, and unit is m/s; I
zfor automobile yaw rotation inertia, unit is kgm
2; L be automobile wheel base from, unit is m; l
ffor vehicle complete vehicle barycenter is to the distance of front axle, unit is m; l
rfor vehicle complete vehicle barycenter is to the distance of rear axle, unit is m; c
ffor the equivalent cornering stiffness of vehicle front, unit is N/rad; c
rfor the equivalent cornering stiffness of automobile back wheel, unit is N/rad; T
hfor the arm inertial delay of default chaufeur, unit is s; ω
cthe cutoff frequency of behaviour car closed loop system, unit is rad/s; S is granny rag Laplacian operater.
Based on an automobile steering intelligent control system for pilot model, comprising:
Take aim at module in advance, utilize the road information observed to generate the target location f (t+T) after taking aim at the cycle T moment in advance;
Prediction module, goes out according to the information prediction of automobile current operating conditions the position y (t+T) that automobile can arrive after taking aim at the cycle T moment in advance;
Comparison module, compares the position y (t+T) that target location f (t+T) and automobile can arrive after taking aim at the cycle T moment in advance, output bias e (t+T)=f (t+T)-y (t+T);
Computing module, with described deviation e (t+T) divided by taking aim at cycle T in advance, obtains the automobile cross velocity expected
again with the cross velocity v of the automobile of reality
yt () compares, obtain the automobile cross velocity difference e expected
vy(t)=v
y *(t)-v
y(t);
Control module, poor according to the automobile cross velocity expected, obtain steering wheel angle according to following formula, and according to the steering wheel angle obtained, vehicle steering is controlled:
θ(s)=e
vy(s)×G
d(s)
In formula, θ (s) represents steering wheel angle; e
vys () represents that the automobile cross velocity expected is poor; G
ds () is transfer function, obtain according to following formula:
Wherein, m is vehicle complete vehicle quality, and unit is kg; V is the speed of a motor vehicle, and unit is m/s; I
zfor automobile yaw rotation inertia, unit is kgm
2; L be automobile wheel base from, unit is m; l
ffor vehicle complete vehicle barycenter is to the distance of front axle, unit is m; l
rfor vehicle complete vehicle barycenter is to the distance of rear axle, unit is m; c
ffor the equivalent cornering stiffness of vehicle front, unit is N/rad; c
rfor the equivalent cornering stiffness of automobile back wheel, unit is N/rad; T
hfor the arm inertial delay of default chaufeur, unit is s; ω
cthe cutoff frequency of behaviour car closed loop system, unit is rad/s; S is granny rag Laplacian operater.
The arm inertial delay T of described chaufeur
hspan be preferably 0.1-0.3s.
The cutoff frequency ω of described people's car closed loop system
cspan be preferably 1 ~ 6rad/s.
Compared to existing technology, the present invention has following beneficial effect:
The pilot model that the present invention sets up, its parameter is directly obtained by whole-car parameters, has that parameter is simple, physical meaning advantage clearly, to the control of automobile more accurately and true.
Accompanying drawing explanation
Fig. 1 is the structural principle schematic diagram of pilot model of the present invention;
Fig. 2 is the control principle schematic diagram of automobile steering intelligent control system of the present invention;
Fig. 3 is the simulating, verifying comparison diagram of pilot model of the present invention and preview follower pilot model;
Fig. 4 is the track following error comparison diagram of pilot model of the present invention and preview follower pilot model.
Detailed description of the invention
Below in conjunction with accompanying drawing, technical scheme of the present invention is described in detail:
Automobile steering intelligent control system based on pilot model of the present invention, its core is set up pilot model, by the observation system (image collecting device that such as automobile carries, radar etc.) outside condition of road surface is observed, detected by the oneself state information of internal sensor/observer to automobile of automobile, pilot model calculates outbound course dish corner according to observed road information and the automobile oneself state that detects, and according to steering wheel angle, vehicle steering is controlled, thus realize the intelligent vehicle direction closed loop control of accurately reflection driver behavior.
The pilot model that the present invention sets up as shown in Figure 1, comprising:
Take aim at module in advance, the road information (also directly can input data by outside) observed observation system data such as () image collecting device that such as automobile carries, radars processes (such as adopting the method for fitting of a polynomial) and generates the target location f (t+T) after taking aim at the cycle T moment in advance (or be called take aim at a position in advance), and wherein t represents current time;
Prediction module, goes out according to the information prediction of automobile current operating conditions the position y (t+T) that automobile (i.e. t+T moment) after taking aim at the cycle T moment in advance can arrive;
Comparison module, compares the position y (t+T) that target location f (t+T) and automobile can arrive after taking aim at the cycle T moment in advance, output bias e (t+T)=f (t+T)-y (t+T);
Computing module, first calculates the automobile cross velocity of expectation
again with the cross velocity v of vehicle condition information
yt () compares, ask for the automobile cross velocity difference e of expectation
vy(t)=v
y *(t)-v
y(t);
Control module, poor according to the automobile cross velocity expected, obtain steering wheel angle according to following formula, and according to the steering wheel angle obtained, vehicle steering is controlled:
θ(s)=e
vy(s)×G
d(s)
In formula, θ (s) represents steering wheel angle; e
vys () represents that the automobile cross velocity expected is poor; G
ds () is transfer function, obtain according to following formula:
Wherein, m is vehicle complete vehicle quality, and unit is kg; V is the speed of a motor vehicle, and unit is m/s; I
zfor automobile yaw rotation inertia, unit is kgm
2; L be automobile wheel base from, unit is m; l
ffor vehicle complete vehicle barycenter is to the distance of front axle, unit is m; l
rfor vehicle complete vehicle barycenter is to the distance of rear axle, unit is m; c
ffor the equivalent cornering stiffness of vehicle front, unit is N/rad; c
rfor the equivalent cornering stiffness of automobile back wheel, unit is N/rad; T
hfor the arm inertial delay of default chaufeur, unit is s, and its span is preferably 0.1-0.3s; ω
cthe cutoff frequency of behaviour car closed loop system, unit is rad/s, and its span is preferably 1 ~ 6rad/s; S is granny rag Laplacian operater.
The control principle of automobile steering intelligent control system of the present invention as shown in Figure 2, the status information of internal sensor/observer to automobile of automobile detects and feeds back to pilot model, road information is directly inputted by outside, pilot model calculates steering wheel angle according to road information and vehicle condition information, and according to the steering wheel angle obtained, controlled automobile travel direction is controlled, thus form people-Che-Lu closed loop system, reach the object of following the tracks of path locus, may be used for vehicle handling stability simultaneously and control.
In order to verify effect of the present invention, pilot model of the present invention and existing preview follower pilot model is adopted to carry out the l-G simulation test of two-track thread test respectively.Two-track thread test is the closed test of synthesis measuring chaufeur-vehicle handling stability, can more fully study and evaluate the road-holding property of automobile.The reference road adopted in test is input as ISO-3888-1:1999 governing criterion two-track lineman condition; In order to embody validity of the present invention, now adopting identical whole-car parameters and samely taking aim at the time in advance, to pilot model of the present invention with take aim in advance and follow the tracks of pilot model and carry out simulation comparison analysis.The verification msg that emulation adopts has: m=1715Kg, v=30m/s, I
z=2697Kgm
2, L=2.54m, l
f=1.07m, l
r=1.47m, c
f=2*89733N/rad, c
r=2*114100N/rad, T
h=0.15s, ω
c=2.5rad/s, T=0.8s.As shown in Figure 3, Figure 4, wherein Fig. 4 is the track following error comparison diagram of pilot model of the present invention and preview follower pilot model to proving and comparisom result.Track following error simulation result as shown in Figure 4 can be found out, tracking accuracy of the present invention is higher, and maximum tracking error is reduced to 0.7m compared with the 1.2m of preview follower model, and maximum tracking error reduces 42%.In addition, the tracking error of the inventive method does not have larger fluctuating as seen from Figure 4, shows that ride comfort of the present invention is better.Automobile, after lane change, finally reaches stable distance and is reduced to 220m by original 250m, show that stabilization time of the present invention is less, stability and responsibility better.
Claims (6)
1. the automobile steering intelligent control method based on pilot model, it is characterized in that, first the position that after taking aim at the cycle T moment in advance according to the prediction of automobile current operating conditions, automobile can arrive, and compare with the target location after the T moment, obtain both deviations, the ratio of both deviations and T is the automobile cross velocity of expectation, then the automobile cross velocity of expectation and actual automobile cross velocity is compared, and the automobile cross velocity obtaining expecting is poor; Then obtain steering wheel angle according to following formula, and according to the steering wheel angle obtained, vehicle steering controlled:
θ(s)＝e
vy(s)×G
d(s)
In formula, θ (s) represents steering wheel angle; e
vy(s) for the automobile cross velocity of the expectation represented with complex frequency domain poor; G
ds () is transfer function, obtain according to following formula:
Wherein, m is vehicle complete vehicle quality, and unit is kg; V is the speed of a motor vehicle, and unit is m/s; I
zfor automobile yaw rotation inertia, unit is kgm
2; L be automobile wheel base from, unit is m; l
ffor vehicle complete vehicle barycenter is to the distance of front axle, unit is m; l
rfor vehicle complete vehicle barycenter is to the distance of rear axle, unit is m; c
ffor the equivalent cornering stiffness of vehicle front, unit is N/rad; c
rfor the equivalent cornering stiffness of automobile back wheel, unit is N/rad; T
hfor the arm inertial delay of default chaufeur, unit is s; ω
cthe cutoff frequency of behaviour car closed loop system, unit is rad/s; S is granny rag Laplacian operater.
2. as claimed in claim 1 based on the automobile steering intelligent control method of pilot model, it is characterized in that, the arm inertial delay T of described chaufeur
hspan be 0.1-0.3s.
3. as claimed in claim 1 based on the automobile steering intelligent control method of pilot model, it is characterized in that, the cutoff frequency ω of described people's car closed loop system
cspan be 1 ~ 6rad/s.
4., based on an automobile steering intelligent control system for pilot model, it is characterized in that, comprising:
Take aim at module in advance, utilize the road information observed to generate the target location f (t+T) after taking aim at the cycle T moment in advance;
Prediction module, goes out according to the information prediction of automobile current operating conditions the position y (t+T) that automobile can arrive after taking aim at the cycle T moment in advance;
Comparison module, compares the position y (t+T) that target location f (t+T) and automobile can arrive after taking aim at the cycle T moment in advance, output bias e (t+T)=f (t+T)-y (t+T);
Computing module, with described deviation e (t+T) divided by taking aim at cycle T in advance, obtains the automobile cross velocity expected
Again with the cross velocity v of the automobile of reality
yt () compares, the automobile cross velocity difference e of the expectation of acquisition time-domain representation
vy(t)=v
y *(t)-v
y(t);
Control module, poor according to the automobile cross velocity expected, obtain steering wheel angle according to following formula, and according to the steering wheel angle obtained, vehicle steering is controlled:
θ(s)＝e
vy(s)×G
d(s)
In formula, θ (s) represents steering wheel angle; e
vy(s) for the automobile cross velocity of the expectation represented with complex frequency domain poor; G
ds () is transfer function, obtain according to following formula:
Wherein, m is vehicle complete vehicle quality, and unit is kg; V is the speed of a motor vehicle, and unit is m/s; I
zfor automobile yaw rotation inertia, unit is kgm
2; L be automobile wheel base from, unit is m; l
ffor vehicle complete vehicle barycenter is to the distance of front axle, unit is m; l
rfor vehicle complete vehicle barycenter is to the distance of rear axle, unit is m; c
ffor the equivalent cornering stiffness of vehicle front, unit is N/rad; c
rfor the equivalent cornering stiffness of automobile back wheel, unit is N/rad; T
hfor the arm inertial delay of default chaufeur, unit is s; ω
cthe cutoff frequency of behaviour car closed loop system, unit is rad/s; S is granny rag Laplacian operater.
5. as claimed in claim 4 based on the automobile steering intelligent control system of pilot model, it is characterized in that, the arm inertial delay T of described chaufeur
hspan be 0.1-0.3s.
6. as claimed in claim 4 based on the automobile steering intelligent control system of pilot model, it is characterized in that, the cutoff frequency ω of described people's car closed loop system
cspan be 1 ~ 6rad/s.
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| CN104181923A (en) * | 2014-08-29 | 2014-12-03 | 武汉大学 | Intelligent automobile curve tracking method based on linear controller |
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| JP6356585B2 (en) * | 2014-11-28 | 2018-07-11 | 株式会社デンソー | Vehicle travel control device |
| CN105785964B (en) * | 2014-12-25 | 2018-06-29 | 上海机动车检测认证技术研究中心有限公司 | A kind of vehicle closed test method |
| CN104843057B (en) * | 2015-05-26 | 2017-03-29 | 吉林大学 | A kind of rotating direction control method of four-wheel independent steering automobile |
| CN107933686B (en) * | 2016-10-19 | 2019-11-29 | 中车株洲电力机车研究所有限公司 | A kind of multi-shaft steering vehicle tracking center lane line rotating direction control method and system |
| CN106681327B (en) * | 2017-01-11 | 2019-05-24 | 中南大学 | A kind of the intelligent driving transverse and longitudinal decoupling control method and system of big inertial electrodynamic car |
| CN110006419B (en) * | 2018-01-04 | 2021-11-19 | 郑州宇通客车股份有限公司 | Vehicle track tracking point determination method based on preview |
| CN108791301B (en) * | 2018-05-31 | 2020-03-24 | 重庆大学 | Intelligent automobile driving process transverse dynamic control method based on driver characteristics |
| CN110979305B (en) * | 2019-03-18 | 2021-06-22 | 毫末智行科技有限公司 | Vehicle abnormal lane change control method, device and system |
| CN110329347B (en) * | 2019-07-03 | 2021-05-11 | 南京航空航天大学 | Steering control system based on driver characteristics and control method thereof |
| JP6663072B1 (en) * | 2019-12-06 | 2020-03-11 | 株式会社ショーワ | Steering determination device, steering control device, and steering device |
| JP6679801B1 (en) * | 2019-12-06 | 2020-04-15 | 株式会社ショーワ | Steering device, steering control device, and steering device |
| CN111391916B (en) * | 2020-03-27 | 2021-05-28 | 南京航空航天大学 | Steer-by-wire system assist control strategy taking into account driver steering characteristics |
| CN111703417B (en) * | 2020-06-24 | 2023-09-05 | 湖北汽车工业学院 | High-low speed unified pre-aiming sliding film driving control method and control system |
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