Fluid-model-based car routing for modern ridesharing systems

Anton Braverman, J. G. Dai, Xin Liu, Lei Ying

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper considers 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.

Original languageEnglish (US)
Title of host publicationSIGMETRICS 2017 Abstracts - Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems
PublisherAssociation for Computing Machinery, Inc
Pages11-12
Number of pages2
ISBN (Electronic)9781450350327
DOIs
StatePublished - Jun 5 2017
Event2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2017 - Urbana-Champaign, United States
Duration: Jun 5 2017Jun 9 2017

Other

Other2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2017
CountryUnited States
CityUrbana-Champaign
Period6/5/176/9/17

Fingerprint

Railroad cars
Queueing networks
Fluids
Availability

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computational Theory and Mathematics

Cite this

Braverman, A., Dai, J. G., Liu, X., & Ying, L. (2017). Fluid-model-based car routing for modern ridesharing systems. In SIGMETRICS 2017 Abstracts - Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems (pp. 11-12). Association for Computing Machinery, Inc. https://doi.org/10.1145/3078505.3078595

Fluid-model-based car routing for modern ridesharing systems. / Braverman, Anton; Dai, J. G.; Liu, Xin; Ying, Lei.

SIGMETRICS 2017 Abstracts - Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. Association for Computing Machinery, Inc, 2017. p. 11-12.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Braverman, A, Dai, JG, Liu, X & Ying, L 2017, Fluid-model-based car routing for modern ridesharing systems. in SIGMETRICS 2017 Abstracts - Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. Association for Computing Machinery, Inc, pp. 11-12, 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2017, Urbana-Champaign, United States, 6/5/17. https://doi.org/10.1145/3078505.3078595
Braverman A, Dai JG, Liu X, Ying L. Fluid-model-based car routing for modern ridesharing systems. In SIGMETRICS 2017 Abstracts - Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. Association for Computing Machinery, Inc. 2017. p. 11-12 https://doi.org/10.1145/3078505.3078595
Braverman, Anton ; Dai, J. G. ; Liu, Xin ; Ying, Lei. / Fluid-model-based car routing for modern ridesharing systems. SIGMETRICS 2017 Abstracts - Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. Association for Computing Machinery, Inc, 2017. pp. 11-12
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