Analysis of Crossing Behavior and Violations of Electric Bikers at Signalized Intersections
Joint Authors
Tang, Tianpei
Ma, Jie
Zhou, Xizhao
Wang, Hua
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-20
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
This paper focuses on investigating electric bikers’ (e-bikers) crossing behavior and violations based on survey data of 3,126 e-bikers collected at signalized intersections in Nantong, China.
We first explore e-bikers’ characteristics of late crossing, incomplete crossing, and violating crossing behaviors by frequency analysis and duration distribution, and examine a few influential factors for e-bikers’ red-light running (RLR) behavior, including site type, crossing length and traffic signal countdown timers (TSCTs).
E-bikers’ RLR behavior is further divided into three categories, namely GR near-violations, RR violations, and RG violations.
Second, we use a binary logistic regression model to identify the relationship between e-bikers’ RLR behavior and potential influential factors, including demographic attributes, movement information, and infrastructure conditions.
We not only make regression analysis for respective violation type, but also carry out an integrated regression of a census of all three types of violations.
Some insightful findings are revealed: (i) the green signal time and site type are the most significant factors to GR near-violations, but with little impact on the other two violation types; (ii) the waiting time, waiting position, passing cars and crossing length exert considerable impact on RR violations; (iii) for RG violations, TSCTs, leading violators and gender are the most significant factors; (iv) it is also unveiled that site type, green signal time and TSCTs have negligible impact on the whole violations regardless of the violation types.
Thus, it is more meaningful to investigate the impacts of these variables on e-bikers’ RLR behavior according to different violation types; otherwise, the potential relationship between some crucial factors and e-bikers’ RLR behavior might be ignored.
These findings would help to improve intersection crossing safety for traffic management.
American Psychological Association (APA)
Tang, Tianpei& Wang, Hua& Ma, Jie& Zhou, Xizhao. 2020. Analysis of Crossing Behavior and Violations of Electric Bikers at Signalized Intersections. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1175544
Modern Language Association (MLA)
Tang, Tianpei…[et al.]. Analysis of Crossing Behavior and Violations of Electric Bikers at Signalized Intersections. Journal of Advanced Transportation No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1175544
American Medical Association (AMA)
Tang, Tianpei& Wang, Hua& Ma, Jie& Zhou, Xizhao. Analysis of Crossing Behavior and Violations of Electric Bikers at Signalized Intersections. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1175544
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175544