Modeling real driving behaviors through attractor dynamics for motivation

The main goal of this work is to develop a system capable of imitating the mechanisms by which specific events, taking place in the traffic scenario, trigger driver decisions. Specifically the process that leads to start an overtaking maneuver is addressed. The core of this paper regards the problem of the representation in a compact and meaningful form of the driving environment, the way of interpreting such a representation, that of understanding which events trigger a decision in a driver and the related issue of learning typical driving styles in an artificial behavioral system. The method followed has been primarily inspired by the research on Dynamical Systems for Behavior Generation, whereas the basic criteria for behavior analysis have been derived from measurements on real drivers.