A Driver Modeling Methodology Using Hypothetical Reasoning for Multiagent Traffic Simulation

We propose how to acquire driver's individual operation models using the three-dimensional driving simulator in order to implement distinct personalities on each agent. In this paper, operation models are defined as sets of prioritized operation rules, each of which consists of the world as observed by a driver and his/her next operation according to the observation. Each driver might have different set of rules and their priorities. We apply a method to acquire individual operation models using hypothetical reasoning. Because of the method, we are able to obtain operation models which can explain driver's operation during driving simulation. We show some operation models acquired from aged/young human drivers, and then clarify the proposed method can catch each driver's characteristics.