Siting charging stations and identifying safe and convenient routes for environmentally sustainable e-scooter systems

Abstract

E-scooters are considered a new type of micromobility that promotes sustainable transportation modes by shifting the private car mode to a Mobility as a Service. Irregular parking and high life cycle global warming impacts of e-scooters due to dockless operating system cause a tendency from dockless systems to charging stations. This article presents one of the first comprehensive spatial analysis studies aiming to develop a novel GIS-based multi-criteria decision support model for: (1) siting optimum e-scooter charging station locations that will integrate e-scooter system with the existing public transportation systems and point of interests, and (2) finding the most secure and convenient road network to connect the charging stations. Identifying the optimum road network for connecting the charging stations and developing a raster based spatial method for this purpose distinguish this study from the previous studies. The developed model was implemented by performing a case study in Karsiyaka, Izmir, Turkey. 35 suitable locations were determined for siting e-scooter charging stations and the optimal connectivity network connecting each station with its neighboring stations were identified. The model can be reproduced for other locations and used to develop innovative policies and plans for environmentally more sustainable and operationally effective shared e-scooter systems.