Optimal autonomous truck platooning with detours, nonlinear costs, and a platoon size constraint

Qiaolin Hu, Weihua Gu, Lingxiao Wu, Le Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Autonomous trucks offer a promising avenue for enhancing the efficiency and reducing the environmental impact of road freight transportation. This paper examines a transitional phase towards a fully unmanned truck fleet, focusing on a platooning approach with a lead driver. We develop a novel optimization model for autonomous truck platooning that simultaneously considers platoon formation, scheduling, and routing to minimize costs related to labor and fuel. The model incorporates the possibility of detours, nonlinear fuel savings due to air-drag reduction, and the practical platoon size limit. We present an enhanced column generation method, termed the platoon-generation-and-updating approach, which demonstrates high effectiveness in reducing computational time and complexity. Our numerical analysis, based on the Hong Kong highway network, demonstrates the substantial cost advantages of autonomous truck platooning. It also investigates how platooning efficiency is influenced by various operating factors, including truck fleet size, platoon size restrictions, labor-to-fuel cost ratio, and the strictness of delivery time windows, with practical implications interwoven into the discussion.

Original languageEnglish
Article number103545
JournalTransportation Research Part E: Logistics and Transportation Review
Volume186
DOIs
Publication statusPublished - Jun 2024

Keywords

  • Autonomous trucks
  • Column generation
  • Freight transportation
  • Green logistics
  • Platooning

ASJC Scopus subject areas

  • Business and International Management
  • Civil and Structural Engineering
  • Transportation

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