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Swarm Intelligence Inspired Adaptive Traffic Control for Traffic Networks

  • Daxin Tian
  • Yu Wei
  • Jianshan Zhou
  • Kunxian Zheng
  • Xuting DuanEmail author
  • Yunpeng Wang
  • Wenyang Wang
  • Rong Hui
  • Peng Guo
Conference paper
  • 632 Downloads
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 221)

Abstract

The internet of Vehicles (IoV) technologies have boosted diverse applications related to Intelligent Transportation System (ITS) and Traffic Information Systems (TIS), which have significant potential to advance management of complex and large-scale traffic networks. With the goal of adaptive coordination of a traffic network to achieve high network-wide traffic efficiency, this paper develops a bio-inspired adaptive traffic signal control for real-time traffic flow operations. This adaptive control model is proposed based on swarm intelligence, inspired from particle swarm optimization. It treats each signalized traffic intersection as a particle and the whole traffic network as the particle swarm, then optimizes the global traffic efficiency in a distributed and on-line fashion. Our simulation results show that the proposed algorithm can achieve the performance improvement in terms of the queuing length and traffic flow allocation.

Keywords

Particle swarm optimization Traffic signal control Adaptive control 

Notes

Acknowledgments

This research was supported by the National Key Research and Development Program of China (2017YFB0102500).

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  • Daxin Tian
    • 1
    • 3
    • 4
  • Yu Wei
    • 1
    • 3
    • 4
  • Jianshan Zhou
    • 1
    • 3
    • 4
  • Kunxian Zheng
    • 1
    • 3
    • 4
  • Xuting Duan
    • 1
    • 3
    • 4
    Email author
  • Yunpeng Wang
    • 1
    • 3
    • 4
  • Wenyang Wang
    • 2
  • Rong Hui
    • 2
  • Peng Guo
    • 2
  1. 1.Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijingChina
  2. 2.China Automotive Technology and Research Center, Automotive Engineering Research InstituteTianjinChina
  3. 3.Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and EngineeringBeihang UniversityBeijingChina
  4. 4.Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic TechnologiesNanjingChina

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