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

Civil Engineering

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