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Real-time information feedback based on a sharp decay weighted function

机译:基于急剧衰​​减的加权函数的实时信息反馈

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Information feedback strategy, serving as the critical part of intelligent traffic systems, has been treated with growing emphasis. In recent years, a variety of feedback strategies have been proposed. Despite the fact that these strategies have been proved to enhance the traffic efficiency, we find that the road capacity has not been saturated and there is still plenty of room for improvement. Based on the analytic approximations, we found the reason why corresponding angle feedback strategy is superior to weighted congestion coefficient feedback strategy. Given that the sharp decay of the weighted coefficient is the key point, we proposed an efficient feedback strategy called the exponential function feedback strategy (EFFS). We applied it to both the symmetrical two-route model with two exits and that with a single exit. The simulation results indicate that, compared with other strategies, EFFS has decided numerical advantages in average flow, a physical quantity used for depicting the road capacity. Even more importantly, EFFS stands out for its convenient application as well as its fitness for modeling the rugged roads.
机译:信息反馈策略作为智能交通系统的关键部分,已经越来越受到重视。近年来,已经提出了各种反馈策略。尽管事实证明这些策略可以提高交通效率,但我们发现道路通行能力尚未达到饱和,仍有很大的改进空间。基于解析近似,我们找到了相应的角度反馈策略优于加权拥塞系数反馈策略的原因。鉴于加权系数的急剧衰减是关键点,我们提出了一种有效的反馈策略,称为指数函数反馈策略(EFFS)。我们将其应用于具有两个出口和具有单个出口的对称两路径模型。仿真结果表明,与其他策略相比,EFFS决定了平均流量(用于描述道路通行能力的物理量)的数值优势。更为重要的是,EFFS以其便捷的应用以及对崎road不平的道路进行建模的适用性而脱颖而出。

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