The benefit of complete trip information in free-floating carsharing systems

Abstract

Free-floating and instant-access carsharing systems are two features of the most flexible carsharing systems. In the former, users are allowed to freely park the car in any legal parking spot within the boundaries defined by the service operator. In the latter, users are not requested to make any reservation in advance before picking up the car. This paper aims at evaluating the importance of complete trip information in free-floating instant-access carsharing systems. To this aim, we consider a system, referred to as the look-ahead system, where users can reserve a car in advance and are also allowed to directly pick up a car without any reservation. In both cases, the user is requested to specify complete trip details, including the estimated usage duration and the location where the car will be returned. Taking advantage of a complete knowledge of the trip details, the service operator can assign a reservation request to a car that is in use at the time of reservation, provided it will become available at the time and location the user will need it. In its nature, the operational setting we consider is dynamic, as trip information is revealed to the service operator at the time the user requests a car. We also investigate the possibility of suggesting to the user that makes a reservation a pickup location different from the desired one, provided it is not too distant from the latter. We compare the performance of the look-ahead system with the case no information is anticipated, which resembles the service provided by the main carsharing operators currently active in Milan (Italy). Additionally, we use, as a benchmark, the static case where all the information about the users requests (pickup and return locations, as well as delivery time) is known before the start of the planning horizon. We consider a system with no car relocations performed by ad-hoc operators. This enables us to measure the pure benefit of anticipated information, i.e., the benefit coming only from knowing in advance where and when the vehicles will be returned, purged from potential vehicles availability related to relocation operations. The matching between user requests and cars is obtained, for the look-ahead system, iteratively at fixed time intervals through the solution of a Binary Linear Program (BLP) and, for the benchmark case, through the solution of a single BLP. No optimization model is needed for the case where no information is anticipated. A simulation study, based on real-world data from the city of Milan, shows that the look-ahead system can satisfy a number of requests much greater than the case without anticipated information and close to the benchmark case. Moreover, we perform a sensitivity analysis on different parameters, including the maximum distance a user is available to walk and the minimum amount of anticipation requested to users for booking requests, showing their impact on the performance of the systems.