Hybrid Simulation to Support Interdependence Modeling of a Multimodal Transportation Network

T. Bipasha, Jose Azucena, Basem A. Alkhaleel, H. Liao, H. Nachtmann
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引用次数: 9

Abstract

The inland waterways in the United States (U.S.) are used to transport approximately 20% of America’s coal, 22% of U.S. petroleum products, and 60% of farm exports making these waterways a significant contributor to the U.S. multimodal transportation system. In this study, data about natural extreme events affecting inland waterways are collected and used to predict possible occurrences of such events in the future using a spatio-temporal statistical model. We also investigate the waterways disruptions effect on interconnected transportation systems using a simulation tool built on a statistical model. The developed methods are centered on inland waterways but can be used broadly for other local, regional and national infrastructures. A case study based on the Mississippi River and the McClellan-Kerr Arkansas River Navigation System (MKARNS) is provided to illustrate the use of the simulation tool in interdependence modeling and decision making for the operation of a multimodal transportation network.
支持多式联运网络相互依赖建模的混合仿真
美国大约20%的煤炭、22%的石油产品和60%的农产品出口都通过内河运输,这使得这些水路成为美国多式联运系统的重要组成部分。在本研究中,收集了影响内河航道的自然极端事件的数据,并使用时空统计模型预测未来可能发生的此类事件。我们还使用基于统计模型的模拟工具研究了水路中断对互联运输系统的影响。开发的方法以内陆水道为中心,但可广泛用于其他地方、区域和国家基础设施。本文以密西西比河和麦克莱伦-克尔阿肯色河导航系统(MKARNS)为例,说明了该仿真工具在多式联运网络运营的相互依赖建模和决策中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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