Understanding electric bike riders' intention to violate traffic rules and accident proneness in China

As electric bicycles (e-bikes) have emerged as an important transportation mode in China in the past decade, e-bike-related accidents have increased drastically. Research suggests that the main cause of most of these accidents is traffic rule violations by e-bike riders and that some e-bike riders have a higher propensity to experience accidents (i.e., higher accident proneness) than otherwise similar individuals. To facilitate the design of safety policies, it is important to understand the factors that influence both e-bike riders' intention to violate traffic rules and accident proneness. For this purpose, an extension of the theory of planned behavior framework (E-TPB) was developed by incorporating seven new latent psychological factors (descriptive norm, moral norm, perceived risk, self-identity, legal norm, conformity tendency, and past behavior) into the original TPB framework (O-TPB). Using self-reported survey data from over 2000 e-bike riders collected in Shanghai, China, structural equation models for the E-TPB and the O-TPB were estimated. The model estimation results show that the E-TPB provides a more intuitive explanation of e-bike riders' intention to violate traffic rules and accident proneness and has superior predictive power compared to the O-TPB. The model estimation results also show that descriptive norm, conformity tendency, and past behavior are important factors that affect both e-bike riders' intention to violate traffic rules and accident proneness. These findings can be used by policymakers to design safety policies such as reward programs for safe riding behavior, e-bike rider education initiatives, and behavior modification interventions to improve road safety.

Automated summary

The study shows that e-bike accidents are mainly caused by riders violating traffic rules, with some riders more prone to accidents. Understanding the factors influencing riders' intention to violate rules and accident proneness is crucial for designing safety policies. The extended Theory of Planned Behavior provides a better explanation and predictive power for these factors, highlighting the importance of descriptive norm, conformity tendency, and past behavior in affecting e-bike riders' behavior.