Transportation Labor Cost Reduction via Vehicle Platooning: Alternative Models and Solution Methods

卡车 灵活性(工程) 启发式 付款 降低成本 计算机科学 补偿(心理学) 运筹学 一套 数学模型 运输工程 数学优化 工程类 经济 汽车工程 控制(管理) 数学 心理学 统计 管理 考古 人工智能 万维网 精神分析 历史 操作系统
作者
William N. Caballero,Florian Jaehn,Brian J. Lunday
出处
期刊:Transportation Science [Institute for Operations Research and the Management Sciences]
卷期号:56 (6): 1549-1572 被引量:7
标识
DOI:10.1287/trsc.2022.1151
摘要

The advent of automated and semiautomated driving technologies is prompting a reevaluation of the benefits of truck platooning. Whereas the effect of truck platooning on fuel costs is relatively well studied, automated driving enables further cost reductions in the form of labor savings that has, heretofore, been sparingly investigated. The degree to which such savings can be realized depends upon myriad factors. Foremost among them are driver payment policies and platoon formation procedures. Automated driving technology reduces the demands on a platoon’s follower vehicles, which, in turn, justifies modified driver compensation structures. However, reductions in labor expenditures are often limited by load characteristics that inhibit platoon formation. Therefore, this research sets forth a suite of related truck platooning problems that correspond to alternative assumptions about unloaded-truck compensation and shipment temporal flexibility. The computational complexities of these problem variants are examined, [Formula: see text]-hardness is proved for the suite, and other useful mathematical properties are derived. Extensive empirical testing using the U.S. highway system explores the effect of network topology, commerce flow, and platooning labor savings on each problem’s optimal solution, tractability, and other related metrics. Multiple heuristics are also designed and tested for larger-scale instances. In so doing, this research not only explores the effects of varied factors on platooning labor costs but it also provides practical means to identify high-quality, labor-cost-reducing routes.
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