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A stochastic process traffic assignment model considering stochastic traffic demand

机译:考虑随机流量需求的随机过程流量分配模型

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摘要

In real traffic network, both link capacity and traffic demand are subject to stochastic fluctuations. These random fluctuations are major sources of travel time uncertainty. All existing stochastic process traffic assignment model models considering the uncertainty of travel time are presented with fixed traffic demand. In this study, a stochastic process traffic assignment model is presented to consider stochastic traffic demand. The traffic demand is assumed to be comprised of two groups of travelers: commuters with fixed traffic demand and irregular travelers with discrete random demand. With mild conditions, it is proved that our stochastic process traffic assignment model is ergodic and has a unique stable distribution. An algorithm is given to describe the stochastic process model. By conducting numerical test, we analyze the effect of commuters' memory length, irregular travelers' demand and commuters' perception error on the stable distribution of our model.
机译:在实际的交通网络中,链路容量和流量需求都会受到随机波动的影响。这些随机波动是旅行时间不确定性的主要来源。考虑到旅行时间的不确定性,所有现有的随机过程交通分配模型模型都以固定的交通需求给出。在这项研究中,提出了一种随机过程交通分配模型来考虑随机交通需求。假定交通需求由两组旅客组成:交通需求固定的通勤者和离散随机需求的不规则旅客。在温和的条件下,证明了我们的随机过程业务分配模型是遍历遍历的,并且具有独特的稳定分布。给出了描述随机过程模型的算法。通过数值测试,我们分析了通勤者的记忆长度,不规则的旅行者需求和通勤者的感知误差对模型稳定分布的影响。

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