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lateral control of autonomous vehicles based on learning driver behavior via cloud model

The Journal of China Universities of Posts and Telecommunications 2017年第2期24卷 10-17页

作者： Gao Hongbo Xie Guotao Liu Hongzhe Zhang Xinyu Li Deyi State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing Key Laboratory of Information Service Engineering Beijing Union University Information Technology Center Tsinghua University The 61th Institute of Electronic System Engineering

In order to achieve the lateral control of the intelligent vehicle, use the bi-cognitive model based on cloud model and cloud reasoning, solve the decision problem of the qualitative and quantitative of the lateral control of the intelligent vehicle. Obtaining a number of experiment data by driving a vehicle, classify the data according to the concept of data and fix the input and output variables of the cloud controller, design the control rules of the cloud controller of intelligent vehicle, and clouded and fix the parameter of cloud controller： expectation, entropy and hyper entropy. In order to verify the effectiveness of the cloud controller, joint simulation platform based on Matlab/Simulink/CarSim is established. Experimental analysis shows that： driver＇s lateral controller based on cloud model is able to achieve tracking of the desired angle, and achieve good control effect, it also verifies that a series of mental activities such as feeling, cognition, calculation, decision and so on are fuzzy and uncertain.

关键词： cloud model driver behavior autonomous vehicles lateral control

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lateral control of Autonomous Vehicles Based on Fuzzy Logic 25th

Lateral Control of Autonomous Vehicles Based on Fuzzy Logic

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第25届中国控制与决策会议

作者： Xinyu Wang Mengyin Fu Yi Yang Hongbin Ma School of Automation Beijing Institution of Technology Key Laboratory of Intelligent control and Decision of Complex Systems Beijing Institution of Technology

ISBN: (纸本)9781467355322

Autonomous vehicles have attracted considerable attention in the research community and industry due to their potential benefits to unmanned driving and assisted driving. This paper addresses the problem of designing lateral control law and the strategy of determining the giving speed for autonomous vehicles. An improved method of calculating lateral offset and angle error based on multiple look-ahead distances is proposed to reduce the impact of noise in reference path data on the lateral control system. Multiple fuzzy inference engines are used to design the steering controller and determine the given driving speed including forward and backward to deal with both simple and complex reference paths. Satisfactory simulation and experimental results have been obtained for different reference paths including a path with U-turn task in which backward driving is needed.

关键词： Autonomous Vehicle lateral control Multiple Look-ahead Distances Given Driving Speed Fuzzy Logic

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lateral control of an Intelligent Vehicle Based on Adaptive Robust Neuron Network

Lateral Control of an Intelligent Vehicle Based on Adaptive ...

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2015中国汽车工程学会年会

作者： Zhang Kun Bai Yong Cheng Bin Brilliance Auto R＆D Center

An adaptive robust neuron network lateral path tracking control strategy is raised in order to solve the non-linear path tracking problem of the intelligent vehicle at high speed on curve ***,a robust term is added to the control law so as to compensate the limit approximation ability of the designed neuron *** stability of this controller is proven by lyapunov *** results indicate that the designed steering control strategy is with low tracking error and high stability.

关键词： intelligent vehicle path tracking lateral control neuron network lyapunov function

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Research on Trajectory Tracking lateral control of Intelligent Vehicle Based on Nested Sliding Mode

Research on Trajectory Tracking Lateral Control of Intellige...

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2019中国汽车工程学会年会

作者： Zhang Bingli Zheng Pingping Zhang Jie Tang Wei Shen Gan School of Automotive and Traffic Engineering Hefei University of Technology

The trajectory tracking lateral controller designed based on the traditional vehicle model make the performance degradation when the vehicle travels on the road with low adhesion coefficient or high ***,a trajectory tracking lateral controller based on nested sliding mode is designed,which a PI control method is adopted for the outer layer to generate a yaw angular velocity reference signal,and the inner layer makes use of the strong robustness of the sliding control ***,this paper carried out the joint simulation with Matlab/Simulink and Carsim,and the real vehicle tests to verify that the proposed trajectory tracking lateral control method can still make the vehicle track the target path stably under the extreme conditions,such as low adhesion coefficient and high vehicle speed.

关键词： trajectory tracking lateral control nested sliding mode real vehicle tests

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Intelligent vehicle lateral controller design based on genetic algorithmand T-S fuzzy-neural network

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Journal of Systems Engineering and Electronics 2005年第2期16卷 382-387页

作者： RuanJiuhong FuMengyin LiYibin SchoolofInformationandScienceTechnology BeijingInstituteofTechnologyBeijing100081P.R.China SchoolofcontrolScienceandEngineering ShandongUniversityJinan250031P.R.China

Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. controller design can be regarded as a process of searching optimal structure from controller structure space and searching optimal parameters from parameter space. Based on this view, an intelligent vehicle lateral motions controller was designed. The controller structure was constructed by T-S fuzzy-neural network (FNN). Its parameters were searched and selected with genetic algorithm (GA). The simulation results indicate that the controller designed has strong robustness, high precision and good ride quality, and it can effectively resolve IV lateral motion non-linearity and time-variant parameters problem.

关键词： intelligent vehicle genetic algorithm fuzzy-neural network lateral control robustness.

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维普期刊数据库

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Steering control strategy guide by two preview vision cues

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Science China(Technological Sciences) 2012年第9期55卷 2662-2670页

作者： SHEN Huan LING Rui MAO JianGuo LI ShunMing College of Energy&Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

Vision cues play an important role in states feedback in motion ***,the existing driver steering models consider little about vision cues utilized by human drivers during their steering *** paper presents a novel steering control strategy based on two preview points(far point and near point).The far point is used to compensate the steering wheel by predicting the upcoming curvature change with respect to the lane,while the near point as vision feedback,which is used to tune the steering wheel by estimating the errors of vehicle states and lane *** obtain much smoother lateral acceleration during steering,a forward internal model is established using a second-order yaw dynamics system that captures the influence of yaw angular acceleration caused by steering wheel *** input parameter of the second-order system is the vision cues of both the near and far points,and the output parameters are the ideal yaw angle and yaw *** calculate suitable the steering wheel angle,an adaptive controller is designed using fuzzy sliding technology,which is used as the input of the vehicle system *** simulation results show that the proposed method performs better than the existing driver steering models in case of imitating human drivers' behavior,and exhibits excellent adaption to the lane curvature change.

关键词： autonomous driving lateral control driver model fuzzy logic cognitive vehicle

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Chained Form and Sliding Mode control of Farm Vehicles in Presence of Sliding

Chained Form and Sliding Mode Control of Farm Vehicles in Pr...

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第二十七届中国控制会议

作者： Fang Hao1,2,Fan Ruixia1,2 1.School of Information Science and Technology,Beijing Institute of Technology,Beijing 100081,P.R.China 2.Key Laboratory of Complex System Intelligent control and Decision(Beijing Institute of Technology) ,Ministry of Education

The problem of lateral control of autonomous farm vehicles in presence of sliding is addressed in this *** a kinematic model is built in which sliding effects are integrated in form of additive disturbances to the ideal kinematic *** make vehicles robust to those sliding effects,a sliding mode controller is designed by transforming the kinematic model into a perturbed chained *** the help of natural algebraic structures of chained systems,the stability of the proposed lateral sliding mode controller is proven which guarantees convergence of lateral deviations and bounded orientation *** and experimental results show that the proposed control law can provide high path-following accuracy even in presence of sliding.

关键词： Chained system theory Sliding mode control lateral control

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