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A Stochastic Approach To Traffic Congestion Costs

机译:交通拥堵成本的随机方法

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摘要

The real world is a complex dynamic and stochastic environment.This is especially true for the traffic moving daily on our roads.As such,accurate modeling that correctly considers the real-world dynamics and the inherent stochasticity is very important,especially if government will base its road tax decisions on the outcomes of these models.The contemporary traffic prices,if any,however,do not reflect the external congestion costs.In order to induce road users to make the correct decision,marginal external costs should be internalized.To assess these costs,the public sector managers need accurate operational models.We show in this article that using a better representation and characterization of the road traffic,via stochastic queueing models,leads to a more adequate reflection of the congestion costs involved.Using extensive numerical experiments,we show the superiority of the stochastic traffic flow models.
机译:现实世界是一个复杂的动态和随机环境。这对于每天在道路上行驶的交通尤为如此。因此,正确考虑现实世界动态和固有随机性的准确建模非常重要,尤其是在政府是否要建立基础的情况下。它的道路税决定取决于这些模型的结果。但是,现代交通价格(如果有的话)不能反映外部拥堵成本。为了诱使道路使用者做出正确的决定,应将边际外部成本内部化。这些费用,公共部门经理需要准确的运营模型。我们在本文中表明,通过随机排队模型使用更好的道路交通表示和特征,可以更充分地反映所涉及的拥堵成本。使用大量的数值实验,我们展示了随机交通流模型的优越性。

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