Modeling of Human Driving Behavior Based on Expression as Hybrid Dynamical System

摘要

This paper develops a new framework to understand the human driving behavior based on the expression as a Hybrid Dynamical System(HDS) focusing on the driver's stopping maneuver. The driving data are collected by using the three-dimensional driving simulator based on CAVE, which provides three three-dimensional visual information. In our modeling, the relationship between the measured information such as distance to the stop line, its first and second derivatives and the braking amount are expressed by the Piece-Wise, Polynomial System (PWPS) model, which is a class of HDS. The key idea to solve the identification problem is to formulate the problem as the Mixed Integer Linear Programming (MILP) with replacing the switching conditions by binary variables. From the obtained results, it is found that the driver appropriately switches the 'control law' according to the distance to the stop line. Our proposed approach enables us to capture not only the physical meaning of the driving skill, but also the decision-making aspect (switching conditions) in the driving behavior.