2022 Vol.5 Dec.No4

• Title: Congestion control method for urban traffic intersections by integrating Internet of Things and traffic flow data
• Name: WU Jun-jie
• Company: (Quanzhou Institute of Information Engineering,Fujian Quanzhou 362000,China)
• Abstract:

  At present, the congestion control of traffic intersections is mainly through changing the cycle of signal lights in different periods, which can not effectively solve the congestion problem, resulting in long vehicle passage time and affecting the efficiency of road network operation. In order to improve the above defects, the congestion control method of urban traffic intersections combining the Internet of Things and traffic flow data will be studied. After building the Internet of things connecting various sensors at traffic intersections, the Internet of things is used to collect traffic flow data at corresponding intersections. Process traffic flow data, and design the intersection congestion alarm module. The HMM model is used to analyze the change of congestion state at traffic intersections, the adjustment threshold of signal light control is set, and the neural network outputs the congestion control instruction. In the experimental study, the application of the studied method can shorten the vehicle passage time by about 27.3%, and the practical application can solve the problem of massive vehicle congestion at the fastest speed.

  
  

• Keyword: IoT; Traffic flow data; City intersection; Traffic jams; Control method; Hidden Markov model;
• DOI: 10.12250/jpciams2022090520
• Citation form: WU Jun-jie.Congestion control method for urban traffic intersections by integrating Internet of Things and traffic flow data [J]. Computer Informatization and Mechanical System,2022,Vol.5,pp.86-91

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