A stochastic model predictive control approach for modelling human driver steering control Online publication date: Mon, 04-Apr-2016
by Ting Qu; Hong Chen; Yan Ji; Hongyan Guo; Yueting Xu
International Journal of Vehicle Design (IJVD), Vol. 70, No. 3, 2016
Abstract: The simulation-based design and development of various vehicle active safety systems necessitate an enhanced understanding of the driver-vehicle-road system, and particular attention is paid to the improved modelling of the driver driving control characteristics. In this paper, a novel driver steering control model based on stochastic model predictive control (SMPC) is proposed to effectively incorporate the random variation characteristics of road friction. A multi-point driver preview approach is employed to represent the driver's perception of the desired path. An internal vehicle dynamic model with parameter uncertainty in the friction coefficient is formulated to represent the knowledge and adaptation of the driver to the variations in road conditions. A transport delay is applied to reflect the driver's physiological constraints. The SMPC method is then used to minimise a weighted cost function. Simulation and experimental validations are presented to demonstrate the effectiveness and practicability of the proposed modelling framework.
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