Impact of Driver Behavior and Vehicle Type on Safety of Vehicle Platoon Under Lane Change Situation. Issue 5 (May 2023)

• Record Type: Journal Article
• Authors: Shin, Yong Woo; Kim, Dong-Kyu; Kim, Eui-Jin
• Is Part Of: Transportation research record. Volume 2677:Issue 5(2023)
• Page Start: 40
• Page End: 50
• Publication Date: 2023-05
• Subjects: safety -- general -- hazard analysis -- modeling and forecasting; Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/03611981221127274
• Languages: English
• ISSNs: 0361-1981

Abstract

Lane changes are critical contributors to road traffic safety on highways. Among the safety indexes aimed at evaluating the risk associated with lane changes, the lane-change risk index (LCRI) is used to determine the collision probability of a platoon of vehicles during lane-change maneuvers. This study estimated the impact of driver behavior and vehicle type on the LCRI using individual vehicle trajectory data from the Next Generation Simulation (NGSIM) program. We define the subject vehicle (i.e., a vehicle changing lane) and its surrounding vehicles (i.e., front, rear, lead, and lag vehicles) as a platoon. Each vehicle type (i.e., truck, bus, car, and motorcycle) and driver behavior (i.e., aggressive, ordinary, and timid) were categorized for regression analysis. Driver behavior was classified through time–space deviations between each vehicle's trajectories and expected trajectories using Newell's car-following model. In addition, to take into account the heterogeneity among the lanes, this study used a linear mixed model, which reflected fixed and random effects. Two unique findings were that (i) we were able to quantify and analyze the complex interaction between vehicle type and driver behavior within the platoon during lane changes, and (ii) using the random parameter model, the influence of vehicle type and driver behavior in the platoon was heterogeneous, depending on the lane. The findings of this study are expected to provide detailed lane-change strategies for autonomous vehicles as well as to evaluate the causative factors of lane-change risk.