Empirical Analysis of Underlying Mechanisms and Variability in Car-Following Behavior

Abstract

Car-following models have been used in all microscopic traffic simulation modeling for almost half a century to describe the process of driver behavior in following each other in the traffic stream. In recent years, a detailed understanding of car-following behavior has become more essential for both the design and the assessment of advanced driver assistance systems, such as adaptive cruise control, to help improve appropriate algorithms and develop control strategies. However, previous experimental studies and models of car-following behavior have some important limitations, which make them inconsistent with real driving experience. Hence, this study aims to contribute to the better understanding of driving behavior in following a lead vehicle in car-following situations. Efforts have been made to disclose the problems and the limitations in previous experimental studies and models of car-following behavior; to build a new data collection system, including hardware and software architecture; and to investigate and discover the characteristics of real driving behavior in following a lead vehicle. It is hoped that the findings will provide clues to guide the construction of more realistic car-following models.