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A Relaxation Approach for Estimating Origin-Destination Trip Tables

机译:一种估计起点到终点行程表的松弛方法

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The problem of estimating origin-destination travel demands from partial observations of traffic conditions has often been formulated as a network design problem (NDP) with a bi-level structure. The upper level problem in such a formulation minimizes a distance metric between measured and estimated traffic conditions, and the lower level enforces user-equilibrium traffic conditions in the network. Since bi-level problems are usually challenging to solve numerically, especially for large-scale networks, we proposed, in an earlier effort (Nie et al., Transp Res, 39B:497-518, 2005), a decoupling scheme that transforms the O-D estimation problem into a single-level optimization problem. In this paper, a novel formulation is proposed to relax the user equilibrium conditions while taking users' route choice behavior into account. This relaxation approach allows the development of efficient solution procedures that can handle large-scale problems, and makes the integration of other inputs, such as path travel times and historical O-Ds rather straightforward. An algorithm based on column generation is devised to solve the relaxed formulation and its convergence is proved. Using a benchmark example, we compare the estimation results obtained from bi-level, decoupled and relaxed formulations, and conduct various sensitivity analysis. A large example is also provided to illustrate the efficiency of the relaxation method.
机译:通过对交通状况的部分观察来估计起点-目的地旅行需求的问题通常被表述为具有双层结构的网络设计问题(NDP)。在这种表述中,上层问题最小化了所测得的流量状况和估计的流量状况之间的距离度量,而下层问题则在网络中强制了用户均衡流量状况。由于双层问题通常难以用数值方法解决,尤其是对于大型网络,因此,我们在较早的工作中提出了一种解耦方案,该方案可以解决问题(Nie等人,Transp Res,39B:497-518,2005)。 OD估计问题转化为单级优化问题。在本文中,提出了一种新颖的公式来放松用户平衡条件,同时考虑到用户的路线选择行为。这种放松方法允许开发可解决大规模问题的有效解决方案程序,并使其他输入(例如路径旅行时间和历史O-D)的集成变得非常简单。设计了一种基于列生成的算法来求解松弛公式,并证明了算法的收敛性。使用一个基准示例,我们比较了从双层,解耦和松弛公式中获得的估计结果,并进行了各种敏感性分析。还提供了一个大示例来说明松弛方法的效率。

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