• Individual Mobility Networks
• Electrical vehicles

Electric mobility appears to be one of the future ways to make cities more sustainable and improve the quality of live in urban environments. However,when it comes to private vehicles, users need to evaluate how their mobility lifestyle is going to change when their fuel-based vehicle is replaced by and electric one (EV).
The objective of this work is to propose a process that, through a mix of mobility data analytics, ad hoc trip planning and simulation, is able to analyze the current fuel-based mobility of a user and quantitatively describe the impact of switching to EVs on her mobility life style.
Exploiting a network-based representation of human mobility (Individual Mobility Networks), four simulation scenarios are considered, distinguished by the battery recharge options that the user might have in real life: recharging only at public stations, charging also at home or also at work or both. For each scenario we calculate how much battery the user has to charge in each charging option and how much time he has to wait for charging, as well as how much her original mobility (performed with a combustion engine) is affected by the limits of EVs, evaluating the expected increment in travel times and distances.
This work is part of the activities of the H2020 European Project Track & Know (https://trackandknowproject.eu/).