E-scooter Crash Data Analysis towards E-scooter Automatic Emergency Braking System Design and Validation for Automated Vehicles*

Electric scooters (e-scooters) have become increasingly popular for intermodal transportation across major US cities, raising safety concerns for both motorists and non-motorists. To develop E-scooter AEB (Autonomous Emergency Braking) systems for intelligent vehicles, it is important to understand the association between e-scooter crash characteristics including facility type, crash severity, and motorist/non-motorist maneuvers. This paper investigates e-scooter crashes to map variable associations. The findings reveal that less severe crashes may be highly underreported. The most critical facilities for e-scooter safety are intersection crosswalks and travel lanes, with the former resulting in more severe injuries. Observing crash trajectories, right-turn crashes are found to be most common at intersections, while only a few intersection crashes result from left-turning vehicles. The findings highlight the need for dedicated safety design and policies for e-scooters, especially for vehicles at intersection crosswalks. Since data on e-scooter crashes is limited, future studies should focus on gathering larger samples from a wider geographic area to investigate and quantify predictor-crash relationships and develop diagnostic and predictive models using statistics and data-driven approaches.