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Q Value-Based Dynamic Programming with Boltzmann Distribution in Large Scale Road Network

机译:大规模路网中基于Q值的Boltzmann分布动态规划

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摘要

In this paper, a global optimal traffic assignment strategy, i.e., Q value-based Dynamic Programming with Boltzmann Distribution is applied to the Kitakyushu City traffic system. The main idea of the proposed traffic assignment strategy is to calculate the expected traveling time for each origin-destination pair and the probability of selecting the next section, then to generate a considerable number of route candidates for the drivers based on the calculated probability. In the simulation, how to select the temperature parameter and the number of the route candidates is discussed in detail. The comparison between the proposed method and the shortest path algorithms indicates that the proposed method could reduce the risk of the traffic congestion occurrence and save the traveling cost effectively. In addition, the computation time is given to reveal the feasibility of the proposed method in large scale networks.
机译:本文将一种全球最优交通分配策略,即基于Q值的Boltzmann分布动态规划应用于北九州市交通系统。拟议的交通分配策略的主要思想是计算每个起点-终点对的预期行驶时间和选择下一个路段的概率,然后根据计算出的概率为驾驶员生成大量的候选路线。在仿真中,详细讨论了如何选择温度参数和候选路线的数量。所提方法与最短路径算法的比较表明,所提方法可以降低交通拥堵发生的风险,并有效节省出行成本。另外,给出了计算时间以揭示该方法在大规模网络中的可行性。

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