Traffic signal control based on a predicted traffic jam distribution

Cheng You Cui, Ji Sun Shin, Fumihiro Shoji, Hee Hyol Lee

研究成果: Article査読

1 被引用数 (Scopus)

抄録

In this article, we propose a new method of traffic signal control based on the predicted distribution of traffic jams. First, we built a forecasting model to predict the probability distribution of vehicles being in a traffic jam during each period of the traffic signals. A dynamic Bayesian network was used as the forecasting model, and this predicted the probability distribution of the number of standing vehicles in a traffic jam. According to calculations by the dynamic Bayesian network, a prediction of the probability distribution of the number of standing vehicles at each time will be obtained, and a control rule to adjust the split and cycle of the signals to maintain the probability of a lower limit and a ceiling of standing vehicles is deduced. Through a simulation using the actual traffic data of a city, the effectiveness of our method is shown.

本文言語English
ページ(範囲)134-137
ページ数4
ジャーナルArtificial Life and Robotics
14
2
DOI
出版ステータスPublished - 2009 11 1

ASJC Scopus subject areas

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

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