Human-like cybernetic driver model for lane keeping
Résumé
This paper describes a newly developed driver model which focuses on the control of steering (lane keeping) by the human driver. Obstacle avoidance and lane change are not being addressed. Our goal is to obtain a model which is i) consistent with what is known about sensorimotor and cognitive control in humans, ii) accurate (predictive) enough to support the development of efficient steering assistance system and iii) simple to be used in the context of real-time control embedded systems. Driving simulator experiments with human drivers have been carried out to validate the proposed model and to identify its parameters. The results highlight the relations between the model parameters and some characteristics of the human driver. Moreover, the model is valid over a large speed range.