Analyzing shared e-scooter trip frequency on urban road segments in Austin, TX

Abstract

The expansion of e-scooter sharing system presents a mix of advantages and challenges to the urban transportation system. This research delves into the frequency of shared e-scooter trips on urban road segments in Austin, TX, leveraging a Random Forest model to dissect the influence of built environment and demographic variables on e-scooter trip frequencies. The model was then interpreted using Shapley Additive Explanations and Partial Dependence Plots. Results indicated that presence of bike lanes, distance to city center, violent crime, walkability, and land use are the most important variables. Notably, high shared e-scooter trip frequency often coincides with high incidence of violent crimes. The study further explores the non-linear relationships between e-scooter trip frequency and these key variables, revealing threshold effects and significant shifts in usage patterns. These insights offer valuable guidance for cities in the strategic development and regulation of shared e-scooter services.