Urban arterial traffic two-direction green wave intelligent coordination control technique and its application
Urban arterial traffic two-direction green wave intelligent coordination control technique and its application
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DOI：
10.1007/s12555-011-0108-4
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发表时间：
2011-02
期刊：
影响因子：
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通讯作者：
Xiangjie Kong;Guojiang Shen;Feng Xia;Chuang Lin
中科院分区：
文献类型：
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作者：
Xiangjie Kong;Guojiang Shen;Feng Xia;Chuang Lin
提出了一种新的双向绿色波智能控制策略来解决城市主干道交通的协调控制问题。整个控制结构包括两层-协调层和控制层。公共周期时间、拆分、入站偏移和出站偏移在协调层中计算。利用模糊神经网络（FNN），根据关键交叉口的交通流饱和度，对公共交通周期进行调整。分流是根据历史和实时交通信息计算的。偏移量由实时平均速度计算。控制层确定相位组成并在每个周期结束时调整分裂。该控制策略的目标是在保证绿色信号时间利用效率较高的情况下，最大限度地提高主干道沿着方向车辆不停车通过本地交叉口的可能性。实际应用结果表明，该方法能有效减少主干道车辆的平均行程时间和平均停靠站数，提高主干道车辆的平均行程速度。
This paper presents a new two-direction green wave intelligent control strategy to solve the coordination control problem of urban arterial traffic. The whole control structure includes two layers — the coordination layer and the control layer. Public cycle time, splits, inbound offset and outbound offset are calculated in the coordination layer. Public cycle time is adjusted by fuzzy neural networks (FNN) according to the traffic flow saturation degree of the key intersection. Splits are calculated based on historical and real-time traffic information. Offsets are calculated by the real-time average speeds. The control layer determines phase composition and adjusts splits at the end of each cycle. The target of this control strategy is to maximize the possibility for vehicles in each direction along the arterial road to pass the local intersection without stop while the utility efficiency of the green signal time is at relatively high level. The actual application results show the proposed method can decrease the average travel time and average number of stops, and increase the average travel speed for vehicles on the arterial road effectively.