Multiobjective traffic signal timing optimization using non-dominated sorting genetic algorithm

Dazhi Sun, Rahim F. Benekohal, S. Travis Waller

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

Abstract

The purpose of this paper is to investigate the application of non-dominated sorting genetic algorithm in solving the multiobjective signal timing optimization problem (MOSTOP). Three n-objective signal timing optimization problems with m-constraint, which cover both deterministic and stochastic traffic patterns, are defined and solved in this study. Mathematical approximations of the resulting Pareto Frontiers are presented to evaluate the trade-off among various objectives and thus provide the most appropriate alternatives for all potential situations of the intersection traffic signal design.

Original languageEnglish (US)
Title of host publicationIEEE Intelligent Vehicles Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages198-203
Number of pages6
ISBN (Electronic)0780378482
DOIs
StatePublished - 2003
Event2003 IEEE Intelligent Vehicles Symposium, IV 2003 - Columbus, United States
Duration: Jun 9 2003Jun 11 2003

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings

Other

Other2003 IEEE Intelligent Vehicles Symposium, IV 2003
Country/TerritoryUnited States
CityColumbus
Period6/9/036/11/03

ASJC Scopus subject areas

  • Modeling and Simulation
  • Automotive Engineering
  • Computer Science Applications

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