Case Study on the Traffic Collision Patterns of E-Scooter Riders

Abstract

In recent years, nonmotorized transportation and micromobility have become increasingly popular in urban areas, and bike sharing and e-scooter usage are more affordable and accessible than ever before. However, users of these modes face several significant challenges, including risky riding behavior and the danger of being involved in collisions or near collisions with other motorists. Because of a lack of relevant data sets, it is difficult to comprehend the underlying causes of e-scooter collisions. This study collected narrative descriptions of 24 e-scooter collisions that occurred in Texas in 2021. The perceptual cycle model (PCM) was applied to these narrative crash reports to analyze the causation patterns of the crash occurrences. The PCM mechanism was applied independently to fatal and injury collisions, and the results were then compared with Haddon’s matrix to develop policy recommendations. The novel approach proposed in this study can be widely utilized by road safety professionals to understand the causal relationships behind other key road safety issues.