Title :
A queueing network approach to the analysis and control of mobility-on-demand systems
Author :
Zhang, Rick ; Pavone, Marco
Author_Institution :
Dept. of Aeronaut. & Astronaut., Stanford Univ., Stanford, CA, USA
Abstract :
This paper presents a queueing network approach to the analysis and control of mobility-on-demand (MoD) systems for urban personal transportation. A MoD system consists of a fleet of vehicles providing one-way car sharing service and a team of drivers to rebalance such vehicles. The drivers then rebalance themselves by driving select customers similar to a taxi service. We model the MoD system as two coupled closed Jackson networks with passenger loss. We show that the system can be approximately balanced by solving two decoupled linear programs and exactly balanced through nonlinear optimization. The rebalancing techniques are applied to a system sizing example using taxi data in three neighborhoods of Manhattan, which suggests that the optimal vehicle-to-driver ratio in a MoD system is between 3 and 5. Lastly, we formulate a real-time closed-loop rebalancing policy for drivers and demonstrate its stability (in terms of customer wait times) for typical system loads.
Keywords :
automobiles; closed loop systems; linear programming; nonlinear programming; queueing theory; Manhattan neighborhoods; MoD systems; customer wait times; decoupled linear programs; drivers rebalance; mobility-on-demand systems; nonlinear optimization; one-way car sharing service; optimal vehicle-to-driver ratio; passenger loss; queueing network approach; real-time closed-loop rebalancing policy; rebalancing techniques; stability; system loads; taxi service; two coupled closed Jackson networks; urban personal transportation; vehicles fleet; Approximation methods; Computational modeling; Measurement; Optimization; Public transportation; Routing; Vehicles;
Conference_Titel :
American Control Conference (ACC), 2015
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4799-8685-9
DOI :
10.1109/ACC.2015.7172070