Title

A hazard-based duration model for analyzing crossing behavior of cyclists and electric bike riders at signalized intersections

Authors

Authors

X. B. Yang; M. Huan; M. Abdel-Aty; Y. C. Peng;Z. Y. Gao

Comments

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Abbreviated Journal Title

Accid. Anal. Prev.

Keywords

Cyclist; Electric bike; Red-light running; Waiting time; Hazard-based; duration model; Intersection; LIGHT RUNNING BEHAVIOR; PEDESTRIAN CROSSINGS; INCIDENT DURATION; SAFETY; CHINA; RISK; INJURY; Ergonomics; Public, Environmental & Occupational Health; Social; Sciences, Interdisciplinary; Transportation

Abstract

This paper presents a hazard-based duration approach to investigate riders' waiting times, violation hazards, associated risk factors, and their differences between cyclists and electric bike riders at signalized intersections. A total of 2322 two-wheeled riders approaching the intersections during red light periods were observed in Beijing, China. The data were classified into censored and uncensored data to distinguish between safe crossing and red-light running behavior. The results indicated that the red-light crossing behavior of most riders was dependent on waiting time. They were inclined to terminate waiting behavior and run against the traffic light with the increase of waiting duration. Over half of the observed riders cannot endure 49s or longer. 25% of the riders can endure 97 s or longer. Rider type, gender, waiting position, conformity tendency and crossing traffic volume were identified to have significant effects on riders' waiting times and violation hazards. Electric bike riders were found to be more sensitive to the external risk factors such as other riders' crossing behavior and crossing traffic volume than cyclists. Moreover, unobserved heterogeneity was examined in the proposed models. The finding of this paper can explain when and why cyclists and electric bike riders run against the red light at intersections. The results of this paper are useful for traffic design and management agencies to implement strategies to enhance the safety of riders. (c) 2014 Elsevier Ltd. All rights reserved.

Journal Title

Accident Analysis and Prevention

Volume

74

Publication Date

1-1-2015

Document Type

Article

Language

English

First Page

33

Last Page

41

WOS Identifier

WOS:000347581800005

ISSN

0001-4575

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