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Multi-Agent Collaborative Control Method of Ramps Based on Fuzzy Neural Network

机译:基于模糊神经网络的坡道多代理协作控制方法

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In order to improve the growing serious traffic congestion on the junction of freeway and expressway (junction of road network in short), starting from the on-ramp metering, considering the main line and its on-ramp control requirements, the multi-agent collaborative was introduced. And the relativity of different segments of junction of road network was analyzed. Meanwhile, the correlation of different segments was calculated. With the consistency of control objectives for urbanized segments of expressway, a relative density model of multi-agent consistency was proposed. Then, on basis of multi-agent and fuzzy control theory, a multi-agent ramp cooperative control model based on fuzzy neural network was presented. Urbanized segments of Beijing-Tianjin-Tanggu Expressway were selected to validate the model. The results show that the model was effective. The method can stabilize the density of the urbanized expressway, and relief traffic congestion in the area.
机译:为了改善高速公路和高速公路交界处的越来越严重的交通拥堵(简称道路网络的交界处),从斜坡计量开始,考虑到主线及其在斜坡控制要求,多代理协作介绍了。分析了道路网络交界区不同段的相对性。同时,计算了不同段的相关性。随着高速公路城市化段的控制目标的一致性,提出了多种子体一致性的相对密度模型。然后,在多助剂和模糊控制理论的基础上,提出了一种基于模糊神经网络的多代理斜坡协作控制模型。选择了北京 - 天津塘沽高速公路的城市化段以验证该模型。结果表明该模型是有效的。该方法可以稳定城市化高速公路的密度,以及该地区的浮雕交通拥堵。

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