Understanding Electric Bike Accidents Through Safe System Approach in Guangzhou, China: A Mixed-Methods Study

Abstract

Electric bike (e-bike) accidents have emerged as a significant road safety concern in recent years. Employing a mixed-methods approach, this study seeks to elucidate the mechanisms underlying e-bike accidents and to develop an e-bike safe system aimed at enhancing e-bike safety and accident prevention. Quantitative analysis was employed to identify key components and their relationships through an event-based examination of a structured accident dataset using a Bayesian network. Complementing this, qualitative methods—including observations and interviews—were conducted to gain deeper insights into how riders interact with other components within the system. This study was carried out in Guangzhou, a metropolitan city with an increasing use of e-bikes and e-bike-related accidents. The key findings of this study are as follows: 1. The safe system of e-bike safety comprises critical components, including infrastructure (roads and facilities), e-bikes, riding behavior, individual riders, and other road users. 2. E-bike accidents predominantly result from dysfunctions of the safe system. The alteration of one component influences other components, which may, in turn, provide feedback to the original component. 3. While riders’ mistakes play a role, the interactions between riders and other components also contribute to the accidents. 4. At the individual rider level, barriers to safe riding include a lack of safety knowledge, low penalties for violations, and high opportunity costs associated with safe riding behaviors. Deficiencies in infrastructure, regulations, and law enforcement contribute to violations and risky riding practices. This study contributes to the current body of accident studies by developing an e-bike safe system.

Keywords

• e-bike accidents
• safe system approach
• riding behavior
• mixed-methods
• Bayesian network