Identifying E-Scooter Hazard Hotspots

Abstract

This paper develops an approach to investigate locations with potentially dangerous interactions within the system of active mobility in the city of Berlin. The approach consists of explorative expert interviews, an online poll, and quantitative analyses. For the latter we combine three datasets. First, we research hotspots of accidents using official data. Second, we use data based on acceleration sensors from cyclists’ smartphones to find locations of sudden movements. Third, we use trip data from the operators of e-scooter sharing systems. The information gathered are used in a conclusive expert workshop to identify hazard hotspots. Results show that many of the conflicts with pedestrians are caused by parked e-scooters. Second, e-scooter trips are concentrated in the inner city and along specific routes. In moving traffic, hotspots can be identified at crossings and in areas between junctions using various data sources.