Investigating the Impact of Ride Sharing on the Performance of One-way Car-sharing Systems

Car-sharing is emerging as an effective and flexible alternative to car ownership in many large cities in the world. However, car-sharing is still dominated by single-occupancy vehicles, and its convenience may attract still more passengers from public transport, thus aggravating congestion and pollution. Ride sharing can mitigate this problem by pooling together passengers doing similar trips, thus decreasing the number of cars on the road. In this work we propose a strategy for offering ride-sharing in one-way car-sharing systems. To this end, we design a graph-based approach to model the trip-matching problem in a car-sharing system using passenger pooling. Then, we formulate both online and offline trip-matching algorithms, and we investigate their impact on the performance of the system using a large data set from the city of New York. We consider both the point of view of the operator and the users, in terms of net revenues and utility, respectively. We show that with the right fare structure a ride-sharing option can lead to a solution that increases both net revenues for the operator and the utility of passengers, while decreasing vehicles-km travelled.