首页> 外文会议>ICCEE 2010;International conference on computer and electrical engineering >Control of Traffic Light in Isolated Intersections Using Fuzzy Neural Network and Genetic Algorithm
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Control of Traffic Light in Isolated Intersections Using Fuzzy Neural Network and Genetic Algorithm

机译:基于模糊神经网络和遗传算法的孤立路口交通信号灯控制

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In this paper a fuzzy neural network is applied for real time traffic signal control at an isolated intersection. The FNN has advantages of both fuzzy expert system (fuzzy reasoning) and artificial neural network (self-study).A traffic light controller based on fuzzy neural network can be used for optimum control of fluctuating traffic volumes such as oversaturated or unusual load condition. The objective is to improve the vehicular throughput and minimize delays. The rules of fuzzy logic controller are formulated by following the same protocols that a human operator would use to control the time intervals of the traffic light. For adjusting the parameters of FNN, genetic algorithm was used. Compared with traditional control methods for traffic signal, the proposed FNN algorithm shows better performances and adaptability.
机译:本文将模糊神经网络应用于孤立路口的实时交通信号控制。 FNN既具有模糊专家系统(模糊推理)又具有人工神经网络(自学)的优势,基于模糊神经网络的交通信号灯控制器可用于最优控制交通流量的波动,例如过饱和或异常负载情况。目的是提高车辆通行量并最大程度地减少延误。模糊逻辑控制器的规则是通过遵循与操作员用来控制交通灯的时间间隔的相同协议来制定的。为了调整FNN的参数,使用了遗传算法。与传统的交通信号控制方法相比,本文提出的FNN算法具有更好的性能和适应性。

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