An Open-loop Model of Bus Drivers' Lane Change Behavior Based on Naturalistic Driving Data

Abstract

Accurately describing bus driver's behavior is crucial for driving safety intervention strategy. Based on naturalistic data collected from 6 bus drivers, a novel open-loop bus driver model is proposed, which describes bus driver's behavior in starting and ordinary lane change scenarios. 236 lane change segments classified into six groups are extracted, with analysis of variance method being applied to capture maneuver characteristics of bus drivers in typical lane change scenes. 50% cumulative frequency parameter and cluster centers generated by k-means method are used to learn parameters of the proposed model. The results show that the proposed driver model can well simulate behavior of bus drivers under natural starting and ordinary lane change scenes.