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原文传递 Data Envelopment Analysis for the Selection of Highway-Rail Grade Separation Projects

题名：	Data Envelopment Analysis for the Selection of Highway-Rail Grade Separation Projects
正文语种：	eng
作者：	Xue 'Helen' Yang;Joshua Qiang Li;Chaohui Wang;Kelvin Wang;Jared Schwennesen
作者单位：	School of Civil and Environmental Engineering Oklahoma State Univ. Stillwater OK 74078;School of Civil and Environmental Engineering Oklahoma State Univ. Stillwater OK 74078;School of Highway Engineering Chang'an Univ. Xi'an 710064 China;School of Civil and Environmental Engineering Oklahoma State Univ. Stillwater OK 74078;Multimodal Division Oklahoma Department of Transportation Oklahoma OK 73105
关键词：	Highway-rail grade crossings (HRGCs); Grade separation; Data envelopment analysis (DEA); Enhanced DEA (E-DEA)
摘要：	With the ambitious goal of zero deaths but growing traffic and congestion at highway-rail grade crossings (HRGCs), grade separation of these conflicting points has become an increasing strategy that improves railway safety but also increases network capacity and enhances livability attributes. Meanwhile, the engineering costs of grade separation are expensive and can vary considerably, which results in difficulties in the rational selection of such projects. This paper implemented the data envelopment analysis (DEA) for the benchmarking of high-risk HRGCs for grade separation considerations in Oklahoma. The top 1% of HRGCs were identified based on the New Hampshire Hazard Index (NHI) rankings and used as the decision-making units (DMUs) for DEA. The outputs of the DEA process included safety benefits, travel time savings, vehicle operating cost savings, and environmental benefits, and the input was the estimated cost of a grade separation project. The DEA efficiency scores of the DMUs were calculated, and nine HRGCs were identified on the frontiers with efficiency scores of 1.0. To further discriminate the DEA-efficient HRGCs, the enhanced DEA (E-DEA), which combines self-evaluation and cross-evaluation methods, was performed and the most efficient crossing was decreased to four with the E-DEA scores of 1.0. This study established a hierarchical framework combining the NHI, DEA, and E-DEA approaches, available data sets, and decision-making tools for the selection of the most efficient investment alternatives for highway-rail grade separation.
出版年：	2023
期刊名称：	Journal of Transportation Engineering
卷：	149
期：	6
页码：	04023040.1-04023040.11