Exploiting E-Micro-Mobility for the Sustainable Development of Urban Transport Systems

This thesis aims to investigate the factors influencing the adoption of electric Micro-Mobility in urban contexts. In recent years, this innovative mobility solution, both owned and shared, has undergone a significant increase either as a single mode of transport for short trips and for multimodality for longer distances. Firstly, this work explores the potential demand of this mode of transport and the factors which push to the adoption of e-Micro-Mobility. Then, the thesis focuses on the safety-related issues and the driver’s behaviour that could impact the choice of an electric micro-vehicle. The methodology to infer the potential demand of electric Micro-Mobility is introduced using a parametric approach in first instance. Then, the merge between traditional methods (i.e., surveys) and new sources of data (GPS based Floating Car Data FCD) is explained. While the traditional approach identifies the impact of the several socio-economic characteristics of users and travel patterns (e.g., travel time) on modal choice, the trajectories from FCD allow the simulation of the potential demand. The thesis then focuses on the safety perception of the potential user and the resulting driving behavior of the micro-vehicle. The safety level perceived by users, concerning the infrastructure as well as the vehicle interaction, is one of the main factors influencing modal choice in active mobility. Understanding the driving behavior in different scenarios, including the interaction between micro-vehicles and other transport modes, is approached with the development of microscopic mathematical models able to represent this behavior. Microscopic models take as input trajectories of e-micro-vehicles and, with descriptive analysis, can be the foundations of simulation tools. This research represents an advancement in the systematic analysis and modelling of this new mode of transport. The microscopic approach is developed in its whole complexity, starting from the identification of factors impacting the potential adoption of electric Micro-Mobility, to the simulation of the driving behaviours.