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.

中文翻译：

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基于电子城市主要街道交通拥堵指数和人工神经网络的交通拥堵分析（案例研究：Hamedan City）

摘要

交通是电子城市面临的主要挑战，要应对这一挑战，需要分析城市道路网络中的交通拥堵情况。本文通过估算车速性能指标来评估路网状况。本研究基于收集的哈密丹交通控制系统的速度性能数据，分析了哈密丹通信路由主网的流量密度。根据该分析，确定了拥堵指数和交通高峰时间。而且，通过神经网络和遗传算法可以预测到车速和交通拥堵之间的关系。在这项研究中，由于车辆的速度，使用Hamedan交通控制中心来识别交通区域。