Stochastic optimal control for traffic signals of asymmetrical intersection

Chengyou Cui, HeeHyol Lee, Chengzhe Xu

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper, a real time stochastic optimal control method for traffic signals of asymmetrical intersection is proposed. A modified cellular automaton (CA) traffic model and Bayesian network (BN) model are used to predict the traffic jams. Here, the calculation for priori probabilistic of outflows at different traffic signals is modified based on the actual situation. In addition, PSO algorithm is used to search optimal traffic signals based on the stochastic model. Finally, the effectiveness of the proposed method is shown through simulations at an asymmetrical intersection using a micro-traffic simulator.

Original languageEnglish
Pages (from-to)190-195
Number of pages6
JournalArtificial Life and Robotics
Volume20
Issue number2
DOIs
Publication statusPublished - 2015 Jun 17

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Traffic signals
Cellular automata
Bayesian networks
Stochastic models
Particle swarm optimization (PSO)
Simulators

Keywords

  • Asymmetrical intersection
  • Stochastic optimal control
  • Traffic signal

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Stochastic optimal control for traffic signals of asymmetrical intersection. / Cui, Chengyou; Lee, HeeHyol; Xu, Chengzhe.

In: Artificial Life and Robotics, Vol. 20, No. 2, 17.06.2015, p. 190-195.

Research output: Contribution to journalArticle

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