Surrogate-assisted high-dimensional optimization on microscopic traffic simulators

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

1 Citation (Scopus)

Abstract

Microscopic traffic simulation is able to capture many details of a traffic system, which makes it inherently interesting for simulation-based optimization. However, the considerable computational effort required for a single simulation run limits the use of standard heuristic optimization techniques and encourages the use of surrogate models to facilitate the search for an optimal solution. In this work, a grey-box surrogate model for microscopic traffic simulations is presented which allows the optimization of high-dimensional traffic optimization problems without relying on geographic or simulation-specific knowledge.

Original languageEnglish
Title of host publication30th European Modeling and Simulation Symposium, EMSS 2018
EditorsYuri Merkuryev, Miquel Angel Piera, Francesco Longo, Agostino G. Bruzzone, Michael Affenzeller, Emilio Jimenez
PublisherDIME UNIVERSITY OF GENOA
Pages46-53
Number of pages8
ISBN (Electronic)9788885741065
ISBN (Print)978-88-85741-03-4
Publication statusPublished - 2018
Event30th European Modeling and Simulation Symposium, EMSS 2018 - Budapest, Hungary
Duration: 17 Sep 201819 Sep 2018

Publication series

Name30th European Modeling and Simulation Symposium, EMSS 2018

Conference

Conference30th European Modeling and Simulation Symposium, EMSS 2018
CountryHungary
CityBudapest
Period17.09.201819.09.2018

Keywords

  • Evolutionary algorithms
  • Noisy optimization
  • Surrogate assisted optimization
  • Traffic simulation

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