Speed Behaviour of E-scooter Riders in Non-motorized Shared Spaces: Insights from Naturalistic Riding Data

Abstract

E-scooter use has grown sharply in recent years, with riders frequently engaging in risky and illegal behaviours. Previous naturalistic studies with e-scooters have primarily focused on safety-critical events. However, few studies have analyzed the movement of e-scooter riders in natural riding conditions. This study analyses the speed behaviour of 16 e-scooter riders in non-motorised shared spaces. The data were collected in a naturalistic riding experiment in France using e-scooters instrumented with smartphones. Vulnerable road users were automatically detected from video data, and their characteristics were manually annotated. A linear mixed-effects regression model that accounts for unobserved heterogeneity among riders and among trips was estimated. The results show that e-scooter riders tend to ride significantly faster in the morning, when they are male, when they are not at intersections and when there are fewer cyclists in their field of view. These findings offer concrete inputs for stakeholders aiming to improve mobility management and safety in shared spaces.