Analysis of traffic crashes involving electric personal mobility vehicles

Abstract

The future requires environmentally friendly and efficient vehicles for transportation. The vehicles should be safe and easy to use. Electric Personal Mobility Vehicles (e-PMVs) have become popular in cities. Reported crashes for e-PMVs are limited and information about the number of crashes and the injury level is important to get more information in order to prevent future crashes. The crashes were analysed and evaluated by extracting reported information from databases. The databases used were STRADA and IGLAD. To extract data from the databases a query was written and the main part of the query consisted of a text search algorithm that used a wildcard search to extract relevant cases. A literature review was done in order to understand, evaluate and develop the best extraction method and the most relevant variables regarding the crashes for e-PMVs. E-scooters, Segways and hoverboards are the largest categories by number of crashes reported. The results indicate that the majority of accidents involved e-scooters, with mild to medium-level injuries. Most of the crashes were in urban areas with a driver aged between 20 and 30 years old.