Department of Computer, Control and Management Engineering

Rapid growing in urbanization and miles driven in the city will triple urban mobility by 2050. This explosion in demand requires switching to Mobility-as-a-Service models, such as Car-sharing. A critical issue for Car-sharing one-way free floating services is the imbalance problem that requires to solve the conflict between the positioning of vehicles “at the right place and time” and the freedom for customers to return vehicles where and when they want. To better understand the imbalance problem, we use a grid partition of the served city into zones with different demand potentials. We gather real data of vehicle positions of three Car-sharing services for approximately three months in the city of Rome (Italy). In particular, our study is focused on analysing user behaviour by using the number of stops in selected city zones (stop frequency) and the duration of any stop (stop duration). Performing the spatial analysis with a thermographic map of frequency and duration of the stops of the three main Car-sharing services together allows us to show the existence of city zones with crucial different demand potentials. In such a way, given a specific time slot of the day, we can rank and sort distinct city zones from high to low demand potential areas. Finally, we show that such analysis enable to define a flexible and dynamic pricing model, where any trip fare is determined taking into account both the difference of demand potentials between origin and destination zones, and the opportunity costs of user vs operator relocation.