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Intelligent traffic light control based on clustering using Vehicular Ad-hoc Networks

机译:基于车载自组织网络聚类的智能交通灯控制

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As urbanization grows and the cost of vehicle production decreases, urban traffic has become a major problem of modern life. Developing intelligent vehicles alongside standardizing inter-vehicle communications promises that this technology will be a part of future life. In this research, we propose a method in which clustering is used to gather vehicles' movements information in a vehicle ad-hoc network. This method is based on extending green wave using road-side units as a fixed agent and on board units (OBU) in vehicles as a mobile agent. This information is then transmitted to traffic lights for decision making. This algorithm evaluated using Monte Carlo simulation. The simulation results show this method has a positive effect on reducing the average waiting time and overall stop of the vehicles behind the traffic lights.
机译:随着城市化的发展和汽车生产成本的降低,城市交通已成为现代生活的主要问题。与标准化的车辆间通信一起开发智能车辆有望使这项技术成为未来生活的一部分。在这项研究中,我们提出了一种方法,其中使用聚类在车辆自组织网络中收集车辆的运动信息。该方法基于使用路边单元作为固定代理人和车辆中的车载单元(OBU)作为移动代理人来扩展绿波的方法。然后,此信息将传输到交通信号灯以进行决策。该算法使用蒙特卡洛模拟进行评估。仿真结果表明,该方法对减少交通信号灯后面车辆的平均等待时间和总体停车有积极的作用。

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