Optimal policy for scheduling automated guided vehicles in large-scale intelligent transportation systems

Huiwen Wang, Wen Yi, Lu Zhen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Automated electric mobility technologies have been increasingly applied to large-scale intelligent transportation systems (ITSs) to enhance productivity and efficiency. Advanced technologies have reshaped the traditional transportation systems and posed numerous challenges to the deployment and management of new ITSs. A major challenge in the real-life implementation of ITSs is how to manage a large number of automated objects in a cooperative manner. In this paper, we investigate the scheduling and routing problem of automated guided vehicles (AGVs) in a complicated ITS. Cost and efficiency are identified as the two crucial performance indicators of such a novel ITS. An easy-to-implement practical decision policy and a tailored particle swarm based solution method are designed for problem solving. In addition to the theoretical contributions, this paper also conducts a case study to validate the effectiveness and applicability of the proposed methodology, thus contributing to the planning and management of large-scale transportation systems by modeling, optimizing, and validating a new ITS deployed with AGVs.

Original languageEnglish
Article number103910
JournalTransportation Research Part A: Policy and Practice
Volume179
DOIs
Publication statusPublished - Jan 2024

Keywords

  • Electric mobility
  • Large-scale intelligent transportation system
  • Transport policy
  • Travel behavior modeling

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Business, Management and Accounting (miscellaneous)
  • Transportation
  • Aerospace Engineering
  • Management Science and Operations Research

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