Complex Lane Change Behavior in the Foresighted Driver Model

This paper presents a general model for lane-change decision and dynamic lane change behavior based on the Foresighted Driver Model. Differently to previous models, it does not rely on indirect features like gap lengths, TTC or decelerations, but it models the lane change process by explicitly calculating the involved risks and benefits of the different trajectory alternatives. The lane change decision occurs by searching a tradeoff between the anticipated risks and the utility of the maneuver for the driver. In such a way, the model generalizes to a large variability of lane-change situations with varying number of involved traffic participants, since their states are incorporated into the risk estimation. We show that with our model, regular lane change processes can be reliably captured. We also show, how in complex constellations, the model reacts in plausible ways which are not covered by previous models. This is the case e.g. when an emergency lane-change is forced by a fast rear-end approach, or when a lane change occurs in anticipation to an expected merge-in at an entrance.