Investigating Different Types of Red-Light Running Behaviors among Urban e-Bike Rider Mixed Groups

Author:

Zhang Fan12ORCID,Kuai Chenchen1ORCID,Lv Huitao12,Li Wenhao12

Affiliation:

1. School of Transportation, Southeast University, Dongnandaxue Road 2, Nanjing, Jiangsu, China

2. National Demonstration Center for Experimental Road and Traffic Engineering Education (Southeast University), Nanjing 211189, China

Abstract

The red-light running (RLR) behaviors of urban mixed e-bike groups (delivery and ordinary e-bike) have become the main cause of traffic accidents at signalized intersections. The primary purpose of this study is to identify influencing factors of e-bike riders’ RLR behaviors, focusing on the role of delivery e-bike riders in mixed e-bike rider groups. Crossing behaviors of 4,180 e-bike samples (2006 delivery e-bikes and 2174 ordinary e-bikes) at signalized intersections are observed in Xi’an, China. The random parameter multinomial logit model is employed to capture the unobserved heterogeneous effects, and the effects of interaction terms are also considered. The results indicate that delivery e-bike riders are more likely to run red lights than ordinary e-bike riders. E-bike type, riders’ age, waiting position, traffic volume, traffic light type, and time of day are associated with crossing behaviors in urban mixed e-bike groups. In addition, the variable of traffic light status is found to account for unobserved heterogeneity. Findings are indicative to the development of effective implications in improving e-bikes’ traffic safety level at signalized intersections.

Funder

National Key R&D Program of China

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

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