An optimal velocity robust car-following model with consideration of control uncertainty

The real world is an uncertain environment in which vehicles' actions can be stochastic and, as a result, drivers become uncertain of the exact outcome of their decisions. A correct and accurate modelling of the driving task while taking uncertainty into consideration is crucial to reproduce a reliable and realistic driving behaviour. Hence, the simulation of such behaviour will be useful for understanding the dynamics of the urban traffic and, most importantly, for the development of new intelligent transportation systems. In this paper, we propose an optimal velocity robust car-following model (OV-RCFM) to describe and simulate the longitudinal control task with consideration of control uncertainty. The main aim of this model is to produce a reliable and collision-free velocity control under different configurations of an uncertain simulation environment.