Using Asymmetric Theory to Identify Heterogeneous Drivers’ Behavior Characteristics Through Traffic Oscillation

Autor: Qian Wan, Guoqing Peng, Zhibin Li, Felipe Inomata, Yu Zheng, Qianqian Liu
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: IEEE Access, Vol 7, Pp 106284-106294 (2019)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2019.2930762
Popis: This paper applies the asymmetric driving theory to capture driving characteristics of car-following behavior throughout traffic oscillation. Unmanned aerial vehicle (UAV) was employed to record videos near a bottleneck on an expressway in Nanjing, China, from which authors used advanced image processing technology to track and extract the high-fidelity vehicles trajectory data for a microscopic analysis in this study. First, with analyzing the individual vehicle trajectory throughout oscillation, authors find that the driving characteristics of drivers are heterogeneous but show several consistent features: before and after experiencing oscillation, relatively more drivers tend to maintain aggressive driving, i.e., 49.7% are originally aggressive (OA) and 37.2% are later aggressive (LA). Second, the statistical analysis indicates some representative characteristics of Chinese drivers: the polarization (aggressive or timid) is more significant before oscillation (OA 49.7%, originally Newell ON 18.9% and originally timid OT 31.4%) but changing to relative equilibrium after oscillation (LA 37.2%, later Newell LN 33.8% and later timid LT 29%). Finally, the authors also find that the type and intensity of each driver's reaction in oscillation are related to the characteristics he or she have before encountering oscillation. These findings of asymmetric driving behavior evolution in this paper may help to explain the causes of hysteresis and unstable traffic flow phenomena.
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