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Issue title: Artificial Intelligence and Advanced Manufacturing (AIAM 2020)
Guest editors: Shengzong Zhou
Article type: Research Article
Authors: Meng, Haoyanga | Dong, Shenga; * | Zhou, Jibiaoa; * | Zhang, Shuichaoa | Li, Zhenjiangb
Affiliations: [a] School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo, Zhejiang Province, China | [b] The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Correspondence: [*] Corresponding author. Sheng Dong and Dr. Jibiao Zhou, School of Civil and Transportation Engineering, Ningbo University of Technology, Fenghua Rd. #201, Jiangbei District, Ningbo, Zhejiang Province, China. E-mail: dongsheng@nbut.edu.cn (S. D), and zhoujb2014@nbut.edu.cn (J.Z).
Abstract: Green flash light (FG) and green countdown (GC) are the two most common signal formats applied in green-red transition that provides drivers additional alert before termination of green phase. Due to their importance and function in stop-pass decision-making process, proper use of them has become a critical issue to greatly improve the safety and efficiency of signalized intersections. Gradually e-bike riders have become more important commuters in China, however, the influence of FG or GC on them is not clear yet and need pay more attention to it. This study chooses two almost identical intersections to obtain highly accurate trajectory data of e-bike riders to study their decision-making behaviors under FG or GC. The e-bike riders’ behavior is classified into four categories and is to identify their stop-pass decision points using the acceleration trend. Two binary-logit models were built to predict the stop–pass decision behaviors for the different e-bike rider groups, explaining that the potential time to the stop-line is the dominant independent factor of the different behaviors of GC and FG. Furthermore empirical analysis of decision points indicated that GC provides the earlier stop-pass decision point and longer decision making duration on the one side while results in more complexity of decision making and greater risk of stop-line crossing than FG on the other side.
Keywords: Driving behavior, flashing green, green countdown, electric bicycle, stop-pass decision
DOI: 10.3233/JIFS-189700
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 3, pp. 4407-4414, 2021
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