Path Integral Control for Stochastic Dynamic Traffic Routing Problems

Michael Hibbard, Yasuaki Wasa, Takashi Tanaka

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

2 Citations (Scopus)

Abstract

In order to ensure customer satisfaction, ride-hailing providers typically base their routing strategies around minimizing the total traffic delay faced by their users. However, accurately modeling the provider's routing problem is difficult, as realistic traffic networks are non-linear, stochastic, and time-varying. We approach this problem by modelling the dynamic traffic network using the Lighthill, Whitham, and Richards model and use stochastic path integral control to construct the routing strategy of the ride-hailing provider. Differing from previous results, we allow for multiple input and output locations, as well as varying speed limits and maximum traffic densities. Furthermore, we allow the ride-hailing provider to additionally control its traffic flow at splits in the traffic network, which avoids an exponential blow-up in the state space. A numerical example for a representative traffic network is provided to demonstrate the efficacy of the proposed method.

Original languageEnglish
Title of host publication2020 59th IEEE Conference on Decision and Control, CDC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages261-267
Number of pages7
ISBN (Electronic)9781728174471
DOIs
Publication statusPublished - 2020 Dec 14
Externally publishedYes
Event59th IEEE Conference on Decision and Control, CDC 2020 - Virtual, Jeju Island, Korea, Republic of
Duration: 2020 Dec 142020 Dec 18

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2020-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference59th IEEE Conference on Decision and Control, CDC 2020
Country/TerritoryKorea, Republic of
CityVirtual, Jeju Island
Period20/12/1420/12/18

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

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