Development of an Errorable Car-Following Driver Model

†Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, USA An errorable car-following driver model is presented in this paper. An errorable driver model is one that emulates human driver’s functions and can generate both nominal (error-free) as well as devious (with error) behaviors. This model was developed for evaluation and design of active safety systems. The car-following data used for developing and validating the model was obtained from a large-scale naturalistic driving database. The stochastic car-following behavior was first analyzed and modeled as a random process. Three error-inducing behaviors were then introduced. First, human perceptual limitation was studied and implemented. Distraction due to non-driving tasks was then identified based on the statistic analysis of the driving data. Finally, time delay of human drivers was estimated through a recursive least square identification process. By including these three error-inducing behaviors, rear-end collisions with the lead vehicle could occur. The simulated crash rate was found to be similar but somewhat higher than that reported in traffic statistics.