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As a significant active safety technology towards fully autonomous driving, driver-automation co-piloting provides a new thinking for enhancing vehicle active safety and relieving driver's workload. However, the preview pattern divergence between driver and steering assistance system (SAS) may give rise to serious steering conflicts, which reduces driver's faith in SAS, cause him/her to turn off it, and even result in fatal traffic accidents. Focusing on mimicking the driver's steering behaviour, this paper proposes a human-like steering assistance scheme by adaptively varying the preview time and assistance gain of the SAS controller. Driver's preview behaviour of the road curvature is numerically identified using simulator tests along a multi-curves road, based on which a nominal preview-scheduled driver model is established. Based on the nominal driver model, a co-piloting system featuring human-like preview behaviour and a time-varying assistance penalty is proposed to formulate the steering torque-overlay dynamics of both agents in path-tracking. Next, a linear parameter varying (LPV)/H∞ controller satisfying pole placement is integrated to ensure the robustness and stability within the entire parameter space. This enables the steering assistance scheme to have a scheduled preview pattern like a human driver. Results of driving simulator experiment indicate that the proposed steering assistance scheme is able to mitigate driver-SAS conflicts and improve driver's path-tracking performance. [ABSTRACT FROM AUTHOR]

This paper is concerned with developing a new method for measuring a driver’s steering efficiency during a steering manoeuvre, for investigating the driver’s steering performance and for evaluating the steering comfort. Electromyography was successfully used to measure the driver’s muscle activity and to reveal the function of the driver’s key muscles in the steering manoeuvre. A measurement of the driver’s steering efficiency during a dynamic steering manoeuvre with two hands is presented on the basis of a regression analysis of the electromyography and steering-force data. The proposed measurement procedure consists of two parts. First, a multiple-regression analysis of the steering-force and electromyography data is conducted, and the steering forces in the steering wheel plane are predicted using the electromyography data of the key muscles producing the steering torque. Second, by predicting the steering force, the force capacity of the driver in the steering manoeuvre is estimated, and then the steering efficiency of the driver is measured. The steering efficiency of the driver, which characterizes the inefficiency, is thought to be a significant movement control strategy employed by driver, and its application in investigating the driver’s steering strategy is the subject of further study. [ABSTRACT FROM PUBLISHER]