A Multifaceted Characterization of Free-Floating CarSharing Service usage

After having witnessed the diffusion of car sharing systems during the lastdecade, the research community has posed a number of relevant questions abouttheir current utilization trends in different contexts, their growth perspectives,and the gradual shift towards more sustainable and efficient technologies. Sincea large and heterogeneous amount of car sharing usage data is now available,researchers have started to address the aforesaid issues through data-driven ap-proaches.In this paper, we provide a extensive usage characterization of the FreeFloating Car Sharing (FFCS) services provided in 23 cities in Europe and NorthAmerica over a 14-month period. We describe FFCS services in terms of fleetsize, operative area, and characteristics of car bookings and rentals. We iden-tify also temporal patterns that are peculiar to specific cities and countries aswell as spatial recurrences describing urban zones with high attractiveness orwith high rental generation rate. Finally, we compare the systems relying oninternal combustion cars with those based on electric vehicles in terms of vari-ous indicators, including the effects on booking cancellations and on charge/fillevents.The results show significantly variable patterns across different cities andcountries. The insights provided by empirical evidences allow system managersto assess profitability and sustainability of the services under multiple aspects.

Dataset Samples

Anonymized datasaset of 2 months of trips of car sharing users in the city of Turin.

Anonymized datasaset of 2 months of trips of car sharing users in the city of Vancouver.

Interactive Graphs

We provide below interactive graphs for the extraction of further details related to different FFCS analysis.

Rental Characterization

Rental Duration
Rental Distance

Daily Characterization

Daily Rental Distribution
Daily Rental Duration
Daily Rental Distance

Monthly Trends

Deviation of Average Number of Rentals per day in each Month w.r.t. Average Number of Rentals per day
Deviation of Average Rental Duration per Month w.r.t. Average Duration
Deviation of Average Rental Distance per Month w.r.t. Average Distance

Daily Trends

Deviation of Average Number of Rentals per day w.r.t. Average Number of Rentals per day
Deviation of Average Duration per day w.r.t. Average Duration
Deviation of Average Distance per day w.r.t. Average Distance
Distribution of cancellations per average day

Hour Characterization

Rentals Distribution
Columbus % of Rentals Per Hour w.r.t. day
Average Rentals Duration
Columbus Average Duration
Average Rentals Distance
Columbus Average Distance

Spatial Analysis

Rental Departure Location
Columbus Average Rental Departure (% w.r.t. max max value)
Generative vs Attractive
Columbus Generative vs Attractive