基于人工神经网络的交通信号灯定时优化

Michel B. W. De Oliveira, A. A. Neto
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引用次数: 13

摘要

本文提出了一种基于神经网络的城市交通路口红绿灯控制器,称为EOM-ANN控制器(Environment Observation Method based on Artificial neural networks controller)。EOM是一种非常有趣的确定交通灯定时的数学方法。然而,这种方法对人工神经网络的提出也有一定的启示。为了评估所提出的交通控制系统,在仿真软件SUMO (simulation of Urban Mobility)中建立了一个孤立的交叉口。
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Optimization of traffic lights timing based on Artificial Neural Networks
This paper presents a neural networks based traffic light controller for urban traffic road intersection called EOM-ANN Controller (Environment Observation Method based on Artificial Neural Networks Controller). EOM is a very interesting mathematical method for determining traffic lights timing. However, this method has some implications which artificial neural networks were proposed to improve such problems. To evaluate the proposed traffic control system, an isolated intersection was built in simulation software named SUMO (Simulation of Urban Mobility).
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