Reliable Least-Time Path Estimation and Computation in Stochastic Time-Varying Networks with Spatio-Temporal Dependencies

Monika Filipovska, Hani S. Mahmassani

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

1 Scopus citations

Abstract

This paper studies the problem of estimation and computation of reliable least-time paths in stochastic time-varying (STV) networks with spatio-temporal dependencies. For a given desired confidence level a, the least-time paths from any origin to a given destination node are to be found over a desired planning horizon. In STV networks, least-time path finding approaches aim to incorporate an element of reliability to help travelers better plan their trips to prepare for the risk of arriving later or traveling for longer than desired. A label-correcting algorithm that incorporates time-dependence of the travel time distributions is proposed. The algorithm incorporates a Monte Carlo sampling approach for a path travel time estimation with time-dependence, which can also be used as an approximate solution method with spatial link travel-time correlations. Numerical results on the large-scale Chicago network are provided to test for the performance of the algorithms and the robustness of solutions. The trade-off between accuracy and efficiency of the approximate solution method compared to a Monte Carlo simulation-based approach is discussed and evaluated.

Original languageEnglish (US)
Title of host publication2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728141497
DOIs
StatePublished - Sep 20 2020
Event23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020 - Rhodes, Greece
Duration: Sep 20 2020Sep 23 2020

Publication series

Name2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020

Conference

Conference23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020
Country/TerritoryGreece
CityRhodes
Period9/20/209/23/20

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Information Systems and Management
  • Modeling and Simulation
  • Education

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