Simulation-based travel time reliable signal control

X Chen, C. Osorio, Bruno F. Santos

Research output: Contribution to journalArticleScientificpeer-review

14 Citations (Scopus)
196 Downloads (Pure)

Abstract

This paper addresses a travel time reliable signal control problem. Travel time distributional estimates are obtained from a stochastic microscopic traffic simulator. The estimates are embedded within a simulation-based optimization algorithm. Analytical approximations of the simulated metrics are combined with the simulated data in order to enhance the computational efficiency of the algorithm. The signal control problems are formulated based on the expectation and the standard deviation of travel time metrics. The proposed approach goes beyond the traditional use of first-order simulated information, it addresses a problem that embeds higher-order distributional information. It is used to solve a large-scale signal control problem. The approach addresses these challenging simulation-based optimization problems in a computationally efficient manner. Its performance is compared to that of a traditional simulation-based optimization approach. The proposed method systematically outperforms the traditional approach. Such an approach can be used to informthe design and operations of transportation systems by, for instance, addressing reliable and/or robust formulations of traditional transportation problems.

Original languageEnglish
Pages (from-to)523-544
Number of pages22
JournalTransportation Science
Volume53
Issue number2
DOIs
Publication statusPublished - 2019

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • simulation-based optimization
  • travel time reliability
  • large-scale signal control
  • metamodel

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