This paper presents a queueing network approach to the analysis and controlof mobility-on-demand (MoD) systems for urban personal transportation. A MoDsystem consists of a fleet of vehicles providing one-way car sharing serviceand a team of drivers to rebalance such vehicles. The drivers then rebalancethemselves by driving select customers similar to a taxi service. We model theMoD system as two coupled closed Jackson networks with passenger loss. We showthat the system can be approximately balanced by solving two decoupled linearprograms and exactly balanced through nonlinear optimization. The rebalancingtechniques are applied to a system sizing example using taxi data in threeneighborhoods of Manhattan, which suggests that the optimal vehicle-to-driverratio in a MoD system is between 3 and 5. Lastly, we formulate a real-timeclosed-loop rebalancing policy for drivers and demonstrate its stability (interms of customer wait times) for typical system loads.
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