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Erscheinungsjahr: 
2024
Quellenangabe: 
[Journal:] EURO Journal on Transportation and Logistics (EJTL) [ISSN:] 2192-4384 [Volume:] 13 [Issue:] 1 [Article No.:] 100141 [Year:] 2024 [Pages:] 1-15
Verlag: 
Elsevier, Amsterdam
Zusammenfassung: 
Autonomous trucks are expected to fundamentally transform the freight transportation industry. In particular, Autonomous Transfer Hub Networks (ATHNs), which combine autonomous trucks on middle miles with human-driven trucks on the first and last miles, are seen as the most likely deployment pathway for this technology. This paper presents a framework to optimize ATHN operations and evaluate the benefits of autonomous trucking. By exploiting the problem structure, this paper introduces a flow-based optimization model for this purpose that can be solved by blackbox solvers in a matter of hours. The resulting framework is easy to apply and enables the data-driven analysis of large-scale systems. The power of this approach is demonstrated on a system that spans all of the United States over a four-week horizon. The case study quantifies the potential impact of autonomous trucking and shows that ATHNs can have significant benefits over traditional transportation networks.
Schlagwörter: 
Autonomous Transfer Hub Networks
Autonomous trucking
Load planning
Mixed-integer linear programming
Case study
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