A New Model of Human Steering Using Far-Point Error Perception and Multiplicative Control

In this paper, a new steering control model is introduced, motivated by several characteristics of human driving. The model uses as input an optical variable portraying visual information directly accessible to the driver: the splay error, representing the lane positioning aspect of driving. The splay error is regulated through a multiplicative control model; this approach displays similar statistical properties to those found in human compensatory control. Further, multiplicative control exhibits steering pulse behavior related to human steering. A second input variable in the model, the critical normalized yaw rate, reflects the information from the far region of the road. The parameters of the model are optimized for low and high vehicle speeds through a genetic algorithm. With the fitted parameters, the response of the model is compared to driver behavior by means of steering workload measurement, and validated with naturalistic driving data.