E-scooter safety under scrutiny: Examining crash patterns and injuries in the UK

Abstract

Introduction: Electric-powered scooters (E-scooters), as an emerging sustainable micromobility mode, are increasingly popular. However, safety concerns regarding the use of e-scooters are also rising. For example, in 2022, 1,492 casualties resulting from e-scooter-involved crashes were observed in 24 trial areas across the UK. To enhance the understanding of e-scooter riding risks, this study conducted a nationwide crash analysis using a UK dataset. It explores the spatial and environmental contexts of e-scooter crashes and the factors influencing crash severity. Method: A comprehensive approach, including exploratory data analysis, latent class analysis (LCA), chi-square test, and logistic regression model, were employed. Results: Findings revealed distinctive spatiotemporal patterns in e-scooter crashes compared to overall crashes, with a higher incidence in deprived communities. Three crash typologies were identified using LCA: night-time, morning, and information-deficient. Multiple demographical and environmental factors were found to influence crash severity. Conclusions: Compared to overall crash trends, e-scooter crashes are more prevalent in urban areas with high population density and exhibit distinct peak patterns in the afternoon. Night-time crashes in low-light conditions and morning crashes with ample daylight are two significant crash clusters. Factors such as the involvement of riders aged 45 to 65 (Odd Ratio [OR] = 1.76) or > 65 (OR = 3.61), crashes occurring at late night/early morning (OR = 2.29), and rural locations (OR = 1.72) increased e-scooter crash severity compared to their respective reference groups. Moreover, highly deprived communities not only experience a higher number of e-scooter crashes but also contribute to crash severity. Practical Applications: This study underscores the necessity for targeted interventions, such as providing safety campaigns and training programs for older individuals and e-scooter users residing in dense urban areas. It also highlights the need for policies that address inequities, particularly through improved infrastructure and enforcement in lower-income urban areas with more e-scooter crashes.