Distributed traffic signal control using PSO based on probability model for traffic jam

Cheng You Cui*, Hee Hyol Lee

*Corresponding author for this work

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

5 Citations (Scopus)

Abstract

In this article, a new traffic signal control method is proposed. The Bayesian Network (BN) model and the Cellular Automaton (CA) model are used to build up a probability model for traffic jam. And then using the Particle Swarm Optimization (PSO) based on the probability model, the optimal traffic signal can be obtained. Finally, the effectiveness of the proposed method is shown with a micro-traffic simulator.

Original languageEnglish
Title of host publicationIntelligent Autonomous Systems 12 - Proceedings of the 12th International Conference, IAS 2012
PublisherSpringer Verlag
Pages629-639
Number of pages11
EditionVOL. 1
ISBN (Print)9783642339257
DOIs
Publication statusPublished - 2013
Event12th International Conference on Intelligent Autonomous Systems, IAS 2012 - Jeju Island, Korea, Republic of
Duration: 2012 Jun 262012 Jun 29

Publication series

NameAdvances in Intelligent Systems and Computing
NumberVOL. 1
Volume193 AISC
ISSN (Print)2194-5357

Conference

Conference12th International Conference on Intelligent Autonomous Systems, IAS 2012
Country/TerritoryKorea, Republic of
CityJeju Island
Period12/6/2612/6/29

Keywords

  • bayesian network
  • cellular automaton
  • particle swarm optimization
  • probabilistic distribution
  • traffic jam

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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