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The Traffic Congestion Analysis Using Traffic Congestion Index and Artificial Neural Network in Main Streets of Electronic City (Case Study: Hamedan City)

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Abstract

Traffic is a major challenge for electronic cities and coping with it requires analyzing traffic congestion in the city road network. In this paper, the performance index of vehicle speed was estimated to evaluate the conditions of road networks. This study analyzes the traffic density for the main network of Hamedan communication routes based on the collected data of Speed performance of Hamedan traffic control system. According to this analysis, the congestion index and traffic peak hours were determined. Also the relationship between vehicle speed and traffic congestion was predictably predictable by neural network and the genetic algorithm. In this study areas of traffic were identified using Hamedan traffic control center due to the speed of vehicles.

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Authors and Affiliations

  1. Computer Engineering Department, Arak Branch, Islamic Azad University, Arak Imam Khomeini Arak, Markazi Province, Iran

    Mohammad Mehdi ShirMohammadi

  2. Computer Engineering Department, Hamedan Branch, Islamic Azad Universit Hamadan Province, Hamedan, Hamedan, Iran

    Mansour Esmaeilpour

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  1. Mohammad Mehdi ShirMohammadi
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  2. Mansour Esmaeilpour
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Correspondence to Mohammad Mehdi ShirMohammadi or Mansour Esmaeilpour.

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ShirMohammadi, M.M., Esmaeilpour, M. The Traffic Congestion Analysis Using Traffic Congestion Index and Artificial Neural Network in Main Streets of Electronic City (Case Study: Hamedan City). Program Comput Soft 46, 433–442 (2020). https://doi.org/10.1134/S0361768820060079

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