Citation

Zhang F, Ji Y, Lv H, Ma X. Accid. Anal. Prev. 2021; 152: e105977.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.aap.2021.105977

PMID

unavailable

Abstract

The red-light running (RLR) behavior of delivery e-bike (DEB) riders in cities has become the primary cause of traffic accidents associated with this group at signalized intersections. This study aimed to explore the influencing factors of red light running behavior and identify the differences between the DEB riders and the ordinary e-bike (OEB) riders to aid the development of countermeasures. In this study, the mixed (random parameter) binary logistic model was employed to capture the effects of unobserved heterogeneity. With this approach, factors including individual characteristics, behavioral variables, characteristics of signalized intersections, and the traffic environment were examined. Additionally, to account for the combined influence on the RLR occurrence, mixed logit framework was developed to reveal the correlations among the random parameters. The data of e-bike riders' crossing behaviors at four signalized intersections in Xi'an, China were collected, and 3335 samples were recorded. The results indicated showed that DEB riders are more likely to run red lights than OEB riders. Factors that affect RLR behaviors of the two groups are different. Factors associated with the unobserved heterogeneity include red-light stage, observation time, age and waiting position of the rider. The joint influence among random parameters further illustrates the complexity of the contributing factors of riders' crossing behavior.

RESULTS from the models provide insights into the development of intervention systems to improve the traffic safety of e-bike riders at intersections.

Language: en

Keywords

Red light running; Correlated mixed logit; Delivery e-bike; Influencing factor; Random parameter