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Reliability-based Marginal Cost Pricing with Stochastic Demand

机译:具有随机需求的基于可靠性的边际成本定价

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The paper explores the marginal cost pricing (MCP) issues in a traffic network with stochastic demand. It has been known that the naive method by simply replacing the link flow and link travel time in the original MCP with their expected values is not workable. While on the other hand, when network uncertainty is accounted for, not only the mean travel time but also the variance of travel time, i.e. the reliability, are cared by travelers. In this study, the value of reliability is incorporated in both the travelers' route choice criteria and the objective of system optimum. Then, a reliabilitybased MCP, which drives a user equilibrium flow distribution under stochastic network toward system optimum, is presented. A numerical example is examined in different levels of uncertainty and with different values of reliability. It exhibits that the higher the uncertainty and the value of reliability, the worse the naive method.
机译:本文探讨了具有随机需求的交通网络中的边际成本定价(MCP)问题。众所周知,仅用原始MCP替换其预期值的链接流量和链接行进时间的幼稚方法是行不通的。另一方面,当考虑到网络不确定性时,旅行者不仅要注意平均旅行时间,而且还要旅行时间的方差,即可靠性。在这项研究中,可靠性的价值既包含在旅行者的路线选择标准中,又包含在系统优化的目标中。然后,提出了一种基于可靠性的MCP,该MCP驱动随机网络下的用户平衡流向系统最优方向分配。在不同级别的不确定性和不同可靠性值下检查了一个数值示例。结果表明,不确定性和可靠性值越高,天真的方法越差。

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