Qualifying the benefits of ride-sharing on reducing fleet size

Abstract

Reducing the number of operating vehicles in cities has enormous significance on mitigating traffic congestion and environment pollution. Ride-sharing is an efficient way to reduce fleet size in urban areas. In this work, we propose two integer programming models to qualify the benefits of ride-sharing on reducing fleet size. The proposed models are solved by commercial solver Gurobi. Then we conduct a series of instances based on trip records of New York City to test the proposed models. Results indicate that without delaying drop-off times, the fleet size when considering ride-sharing remains almost the same as ride-hailing service for high-density travel demand settings. Whereas the fleet size drops sharply as the demand density decreases. In addition, the number of vehicles required is reduced by nearly 30% regardless of order density under ride-sharing assumptions when a slight delay is allowed.