中国邮电高校学报(英文) ›› 2016, Vol. 23 ›› Issue (4): 37-45.doi: 10.1016/S1005-8885(16)60043-2

• Networks • 上一篇    下一篇

Congestion warning method based on the Internet of vehicles and community discovery of complex networks

赵婷,王斌,高琪   

  1. 北京理工大学
  • 收稿日期:2015-11-18 修回日期:2016-03-25 出版日期:2016-08-30 发布日期:2016-08-30
  • 通讯作者: 高琪 E-mail:gaoqi@bit.edu.cn
  • 基金资助:
    自然科学基金;北京高等学校青年英才计划

Congestion warning method based on the Internet of vehicles and community discovery of complex networks

  • Received:2015-11-18 Revised:2016-03-25 Online:2016-08-30 Published:2016-08-30
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61433003, 61273150), the Beijing Higher Education Young Elite Teacher Project (YETP1192).

摘要: The traffic congestion occurs frequently in urban areas, while most existing solutions only take effects after congesting. In this paper, a congestion warning method is proposed based on the Internet of vehicles (IOV) and community discovery of complex networks. The communities in complex network model of traffic flow reflect the local aggregation of vehicles in the traffic system, and it is used to predict the upcoming congestion. The real-time information of vehicles on the roads is obtained from the IOV, which includes the locations, speeds and orientations of vehicles. Then the vehicles are mapped into nodes of network, the links between nodes are determined by the correlations between vehicles in terms of location and speed. The complex network model of traffic flow is hereby established. The communities in this complex network are discovered by fast Newman (FN) algorithm, and the congestion warnings are generated according to the communities selected by scale and density. This method can detect the tendency of traffic aggregation and provide warnings before congestion occurs. The simulations show that the method proposed in this paper is effective and practicable, and makes it possible to take action before traffic congestion.

关键词: IOV, complex network, community discovery, congestion warning

Abstract: The traffic congestion occurs frequently in urban areas, while most existing solutions only take effects after congesting. In this paper, a congestion warning method is proposed based on the Internet of vehicles (IOV) and community discovery of complex networks. The communities in complex network model of traffic flow reflect the local aggregation of vehicles in the traffic system, and it is used to predict the upcoming congestion. The real-time information of vehicles on the roads is obtained from the IOV, which includes the locations, speeds and orientations of vehicles. Then the vehicles are mapped into nodes of network, the links between nodes are determined by the correlations between vehicles in terms of location and speed. The complex network model of traffic flow is hereby established. The communities in this complex network are discovered by fast Newman (FN) algorithm, and the congestion warnings are generated according to the communities selected by scale and density. This method can detect the tendency of traffic aggregation and provide warnings before congestion occurs. The simulations show that the method proposed in this paper is effective and practicable, and makes it possible to take action before traffic congestion.

Key words: IOV, complex network, community discovery, congestion warning