This paper proposes to empirically investigate the members’ behaviors over time in a free-floating carsharing system. With a continuously evolving service in terms of service area and fleet size, member usage intensity and activity space are explored with passive data streams. Members are labeled according to their usage intensity for various periods of analysis. Results show an increase in higher usage intensity classes and a change in demographic composition of new members adopting the service over time: new members are younger and a parity between both genders is reached. Activity space investigation shows that members perform a fair share of their trips to return home and that ultra-frequency members seem to perform a substantial number of symmetric trips, meaning they are more inclined to use free-floating cars for commute-like trips. Interaction with the metro network is also investigated, with a proportion of members using free-floating carsharing to access stations. When looking at the activity space formed by members’ trip ends, users seem to constantly discover new portions of the service area. Multiple clusters of activity locations are determined for each member, with a recurrence level showing a fair amount of variability among members.
Using 5 parallel passive data streams to report on a wide range of mobility options