Cooperative traffic light controlling based on machine learning and a genetic algorithm

Huan Wang, Jiang Liu, Zhenni Pan, Koshimizu Takashi, Shigeru Shimamoto

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

In this paper, a cooperative traffic light controlling algorithm for urban road network aiming at reducing traffic congestion is proposed. Dedicated Short Range Communications (DSRC) is applied to detect the real time traffic flow. Based on the traffic flow at the current traffic light cycle and the historical data, we use machine learning technique to predict the variation of the traffic flow at the next traffic light cycle. With the purpose of reducing the road network's average waiting time and balancing the traffic pressure between different intersections, the traffic light control system adjusts the timing plan cooperatively. The genetic algorithm is used to calculate the optimum traffic light timing plan. In addition, a novel state transition model of the road network for dynamic numerical simulation is utilized to verify the effectiveness of the proposed algorithm. According to a 4-nodes road network simulation result, the vehicles in the traffic flow with congestion problems will have a shorter waiting time while the vehicle in the other traffic flows will have an increased waiting time. More importantly, the average waiting time of the road network declines.

本文言語English
ホスト出版物のタイトル2017 23rd Asia-Pacific Conference on Communications
ホスト出版物のサブタイトルBridging the Metropolitan and the Remote, APCC 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1-6
ページ数6
2018-January
ISBN(電子版)9781740523905
DOI
出版ステータスPublished - 2018 2 27
イベント23rd Asia-Pacific Conference on Communications, APCC 2017 - Perth, Australia
継続期間: 2017 12 112017 12 13

Other

Other23rd Asia-Pacific Conference on Communications, APCC 2017
CountryAustralia
CityPerth
Period17/12/1117/12/13

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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