Abstract
This paper presents a personalized driver assisting system that makes use of the driver's behavior model. The Probability-weighted ARX (PrARX) model which is a type of hybrid dynamical system models is introduced as a model of driving behavior. A PrARX model that describes the driver's vehicle-following skill on expressways is identified using a simple gradient descent algorithm from actual driving data collected on a driving simulator. The obtained PrARX model describes the driver's logical decision making as well as continuous maneuver in a uniform manner. Finally, the optimization of the braking assist is formulated as a mixed-integer linear programming (MILP) problem using the identified driver model, and computed online in the model predictive control framework.
