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

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.