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 co...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.展开更多
Vision cues play an important role in states feedback in motion control.However,the existing driver steering models consider little about vision cues utilized by human drivers during their steering procedure.This pape...Vision cues play an important role in states feedback in motion control.However,the existing driver steering models consider little about vision cues utilized by human drivers during their steering procedure.This 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 center.To 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 angle.The 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 rate.To 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 dynamics.Numerical 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.展开更多
基金supported by the National Natural Science Foundation of China (61035004,61273213,61300006,61305055,90920305,61203366,91420202,61571045,61372148)the National Hi-Tech Research and Development Program of China (2015AA015401)+2 种基金the National Basic Research Program of China (2016YFB0100906,2016YFB100903)the Junior Fellowships for Advanced Innovation Think-Tank Program of China Association for Science and Technology (DXB-ZKQN-2017-035)the Beijing Municipal Science and Technology Commission Special Major (D171100005017002)
文摘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.
基金supported by the China Postdoctoral Science Foundation(Grant No. 2011M500917)the Jiangsu Planned Projects for Postdoctoral Research Funds (Grant No. 1101153C)
文摘Vision cues play an important role in states feedback in motion control.However,the existing driver steering models consider little about vision cues utilized by human drivers during their steering procedure.This 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 center.To 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 angle.The 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 rate.To 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 dynamics.Numerical 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.