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Fleet Management for Autonomous Vehicles Using Multicommodity Coupled Flows in Time-Expanded Networks

Authors Sahar Bsaybes, Alain Quilliot, Annegret K. Wagler

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Author Details

Sahar Bsaybes
  • Université Grenoble Alpes , Institute of Engineering (Grenoble INP), G-SCOP F-38000 Grenoble, France
Alain Quilliot
  • Université Clermont Auvergne , Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), BP 10125, 63173 Aubière Cedex, France
Annegret K. Wagler
  • Université Clermont Auvergne , Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS), BP 10125, 63173 Aubière Cedex, France

Funding

This work was founded by the French National Research Agency, the European Commission (Feder funds) and the Région Auvergne in the Framework of the LabEx IMobS3.

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Sahar Bsaybes, Alain Quilliot, and Annegret K. Wagler. Fleet Management for Autonomous Vehicles Using Multicommodity Coupled Flows in Time-Expanded Networks. In 17th International Symposium on Experimental Algorithms (SEA 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 103, pp. 25:1-25:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.SEA.2018.25

Abstract

VIPAFLEET is a framework to develop models and algorithms for managing a fleet of Individual Public Autonomous Vehicles (VIPA). We consider a homogeneous fleet of such vehicles distributed at specified stations in a closed site to supply internal transportation, where the vehicles can be used in different modes of circulation (tram mode, elevator mode, taxi mode). We treat in this paper a variant of the Online Pickup-and-Delivery Problem related to the taxi mode by means of multicommodity coupled flows in a time-expanded network and propose a corresponding integer linear programming formulation. This enables us to compute optimal offline solutions. However, to apply the well-known meta-strategy Replan to the online situation by solving a sequence of offline subproblems, the computation times turned out to be too long, so that we devise a heuristic approach h-Replan based on the flow formulation. Finally, we evaluate the performance of h-Replan in comparison with the optimal offline solution, both in terms of competitive analysis and computational experiments, showing that h-Replan computes reasonable solutions, so that it suits for the online situation.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Discrete mathematics
Keywords
  • fleet management
  • offline and online pickup and delivery problem
  • multicommodity flows

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