关于异质交通流路径边际成本在一般网络中的研究
On Path-based Marginal Cost of Heterogeneous Traffic Flow for General Networks
AI总结：
本文提出了一种评估异质交通条件下路径边际成本的方法，通过分解和建模车辆类间关系，提高了动态交通分配的效率和准确性。
摘要：
路径边际成本（PMC）是解决基于路径的系统最优动态交通分配（SO-DTA）、动态OD需求估计（DODE）和网络韧性分析中的关键组成部分。然而，在异质交通条件下准确评估PMC存在重大挑战。以往研究往往专注于单一车辆类别的同质交通流，未能很好地处理异质交通流的相互作用效应及由此产生的计算问题。本研究提出了一种新颖但简单的近似评估PMC在复杂异质交通条件下的方法。该方法将PMC分解为类内和类间项，并利用从异质链接动态中导出的转换因子，明确建模车辆类之间的复杂关系。此外，该方法考虑了混合交通流接近系统最优条件时出现的非可导问题。所提出的方法在具有合成需求的小型走廊网络和具有校准需求的大规模网络上进行了测试。结果表明，本方法在解决双类SO-DTA问题中表现出优越的性能，产生较低的总旅行成本，并在系统最优状态下捕捉到多类流量的竞争。
英文摘要：
Path marginal cost (PMC) is a crucial component in solving path-based system-optimal dynamic traffic assignment (SO-DTA), dynamic origin-destination demand estimation (DODE), and network resilience analysis. However, accurately evaluating PMC in heterogeneous traffic conditions poses significant challenges. Previous studies often focus on homogeneous traffic flow of single vehicle class and do not well address the interactive effect of heterogeneous traffic flows and the resultant computational issues. This study proposes a novel but simple method for approximately evaluating PMC in complex heterogeneous traffic condition. The method decomposes PMC into intra-class and inter-class terms and uses conversion factor derived from heterogeneous link dynamics to explicitly model the intricate relationships between vehicle classes. Additionally, the method considers the non-differentiable issue that arises when mixed traffic flow approaches system optimum conditions. The proposed method is tested on a small corridor network with synthetic demand and a large-scale network with calibrated demand from real-world data. Results demonstrated that our method exhibits superior performance in solving bi-class SO-DTA problems, yielding lower total travel cost and capturing the multi-class flow competition at the system optimum state.
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