Developing a multi-method approach to identifying e-scooter hazard hotspots

Abstract

In recent years, e-scooters have been introduced in many European cities. In several places we have witnessed a rapid uptake of this new mode of transport mainly as a result of public sharing schemes. A number of incidents, injuries and even fatalities have given rise to questions regarding the safety of these vehicles. These questions are being researched mainly using official crash data and data specifying injuries and hospital treatment. Until now, the research has focused on investigating typical injury patterns and estimating risk levels. Very little is known about exactly where conflicts and crashes occur. Knowledge of hazard hotspots is crucial when investigating risk levels and improving safety for all road users.

Hence, this paper develops an approach to investigating locations with potentially dangerous interactions within the active mobility system 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 crash hotspots 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 is 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, various data sources are used to identify hotspots at intersections and in areas between intersections.

The present research lays the foundation for important further studies to investigate interactions at hotspots in detail by determining nine specific locations in the city of Berlin.