TY - GEN

T1 - Fluid-model-based car routing for modern ridesharing systems

AU - Braverman, Anton

AU - Dai, J. G.

AU - Liu, Xin

AU - Ying, Lei

N1 - Publisher Copyright:
© 2017 ACM.

PY - 2017/6/5

Y1 - 2017/6/5

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85021795559&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85021795559&partnerID=8YFLogxK

U2 - 10.1145/3078505.3078595

DO - 10.1145/3078505.3078595

M3 - Conference contribution

AN - SCOPUS:85021795559

T3 - SIGMETRICS 2017 Abstracts - Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems

SP - 11

EP - 12

BT - SIGMETRICS 2017 Abstracts - Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems

PB - Association for Computing Machinery, Inc

T2 - 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2017

Y2 - 5 June 2017 through 9 June 2017

ER -