## Abstract

We consider a closed queueing network model of ridesharing systems such as Didi Chuxing, Lyft, and Uber. We focus on empty-car routing, a mechanism by which we control car flow in the network to optimize system-wide utility functions, e.g. the availability of empty cars when a passenger arrives. We establish both process-level and steady-state convergence of the queueing network to a fluid limit in a large market regime where demand for rides and supply of cars tend to infinity, and use this limit to study a fluid-based optimization problem. We prove that the optimal network utility obtained from the fluid-based optimization is an upper bound on the utility in the finite car system for any routing policy, both static and dynamic, under which the closed queueing network has a stationary distribution. This upper bound is achieved asymptotically under the fluid-based optimal routing policy. Simulation results with real-word data released by Didi Chuxing demonstrate that the utility under the fluid-based optimal routing policy converges to the upper bound with a rate of 1 √N, where N is the number of cars in the network.

Original language | English (US) |
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Pages (from-to) | 11-12 |

Number of pages | 2 |

Journal | Performance Evaluation Review |

Volume | 45 |

Issue number | 1 |

DOIs | |

State | Published - Jun 5 2017 |

Externally published | Yes |

## Keywords

- BCMP network
- car routing
- closed queueing network
- fluid limit
- ridesharing

## ASJC Scopus subject areas

- Software
- Hardware and Architecture
- Computer Networks and Communications