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A Predictive Continuum Dynamic User-Optimal Model for the Simultaneous Departure Time and Route Choice Problem in a Polycentric City

机译:多中心城市同时出发时间与路线选择问题的预测连续用户动态优化模型

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This study develops a predictive continuum dynamic user-optimal model for the simultaneous departure time and route choice problem through a variational inequality (VI) approach. A polycentric urban city with multiple central business districts (CBDs) is considered, and travelers are classified into different classes according to their destinations (i.e., CBDs). The road network within the modeling city is assumed to be sufficiently dense and can be viewed as a continuum. A predictive dynamic user-optimal (PDUO) model has been previously used to model traffic flow with a given traffic demand distribution, in which travelers choose the routes that minimize the actual travel cost to the CBD. In this work, we combine the departure time choice with the PDUO model to study the simultaneous departure time and route choice problem. The user-optimal departure time principle is satisfied, which states that for each origin-destination pair, the total costs incurred by travelers departing at any time are equal and minimized. We then present an equivalent VI and solve it using the projection method after discretization based on unstructured meshes. A numerical experiment for an urban city with two CBDs is presented to demonstrate the effectiveness of the numerical algorithm.
机译:这项研究通过变分不等式(VI)方法为同时出发时间和路线选择问题开发了一种预测连续统动态用户最优模型。考虑到一个具有多个中央商务区(CBD)的多中心城市,根据其目的地(即CBD)将旅行者分为不同的类别。假定建模城市内的道路网络足够密集,可以看作是一个连续体。先前已使用预测性动态用户最优(PDUO)模型对具有给定交通需求分布的交通流进行建模,在此模型中,旅行者选择的路线将使前往CBD的实际旅行成本降至最低。在这项工作中,我们将出发时间选择与PDUO模型相结合,以研究同时出发时间和路线选择问题。满足了用户最佳出发时间原则,该原则指出,对于每个起点-目的地对,在任何时间出发的旅行者所招致的总费用是相等的,并且要最小化。然后,我们提出一个等效的VI并在基于非结构化网格的离散化之后使用投影方法对其进行求解。提出了具有两个CBD的城市的数值实验,以证明该数值算法的有效性。

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