A one-boundary drift-diffusion model for time to collision estimation in a simple driving task

ABSTRACT

Driving is a complex everyday task. Every year a huge number of driving accidents around the world causes serious physical and mental injuries and deaths. The correct estimation of the remaining time to reach the other vehicles on the road, known as time to collision (TTC), is an important factor to avoid accidents. In this study, we aimed to use a drift-diffusion model (DDM) to better understand the participants’ estimation of TTC in two driving experiments. Both experiments were the same, except that in one of them participants were asked to finish the experiment as fast as they could, while in the other experiment there was no time constraint. DDM fitted the data from all participants well in both experiments according to the chi-square goodness of fit criterion. Also, results showed that time pressure increases subjects’ estimated TTC, the rate of accumulation of sensory information and the response threshold.