DocumentCode :
105262
Title :
Switching-Based Stochastic Model Predictive Control Approach for Modeling Driver Steering Skill
Author :
Ting Qu ; Hong Chen ; Dongpu Cao ; Hongyan Guo ; Bingzhao Gao
Author_Institution :
Dept. State Key Lab. of Automotive Simulation & Control, Jilin Univ., Changchun, China
Volume :
16
Issue :
1
fYear :
2015
fDate :
Feb. 2015
Firstpage :
365
Lastpage :
375
Abstract :
Great advances in simulation-based vehicle system design and development of various driver assistance systems have enhanced the research on improved modeling of driver steering skills. However, little effort has been made on developing driver steering skill models while capturing the uncertainties or statistical properties of the vehicle-road system. In this paper, a stochastic model predictive control (SMPC) approach is proposed to model the driver steering skill, which effectively incorporates the random variations in the road friction and roughness, a multipoint preview approach, and a piecewise affine (PWA) model structure that are developed to mimic the driver´s perception of the desired path and the nonlinear internal vehicle dynamics. The SMPC method is then used to generate a steering command by minimization of a cost function, including the lateral path error and ease of driver control. In the analyses, first, the experimental data of Hongqi HQ430 are used to validate the driver steering skill controller. Then, the parametric studies of control performance during a nonlinear steering maneuver are provided. Finally, further discussions about the driver´s adaption and the indication on vehicle dynamics tuning are given. The proposed switching-based SMPC driver steering control framework offers a new approach for driver behavior modeling.
Keywords :
nonlinear control systems; predictive control; road traffic; road vehicles; statistical analysis; PWA model structure; SMPC approach; driver assistance systems; driver steering skill; nonlinear internal vehicle dynamics; nonlinear steering maneuver; road friction; simulation based vehicle system design; statistical properties; switching based stochastic model predictive control approach; vehicle road system; Force; Mathematical model; Predictive models; Roads; Tires; Vehicle dynamics; Vehicles; Driver modeling; driver steering skill; piecewise affine (PWA) internal vehicle dynamics; road roughness and friction variations; stochastic model predictive control (SMPC);
fLanguage :
English
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1524-9050
Type :
jour
DOI :
10.1109/TITS.2014.2334623
Filename :
6862053
Link To Document :
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