# Fleet management for autonomous vehicles: Online PDP under special constraints

## TL;DR

This paper presents a dynamic fleet management system for autonomous vehicles that switches between tram and elevator modes to efficiently meet transportation demands, using online algorithms evaluated through competitive analysis.

## Contribution

It introduces a novel online fleet management framework for autonomous vehicles with mode switching, including algorithms and performance evaluation.

## Key findings

- Algorithms achieve competitive performance in mode switching
- Framework effectively manages demand variations
- Practical evaluation shows promising results

## Abstract

The VIPAFLEET project consists in developing models and algorithms for man- aging a fleet of Individual Public Autonomous Vehicles (VIPA). Hereby, we consider a fleet of cars distributed at specified stations in an industrial area to supply internal transportation, where the cars can be used in different modes of circulation (tram mode, elevator mode, taxi mode). One goal is to develop and implement suitable algorithms for each mode in order to satisfy all the requests under an economic point of view by minimizing the total tour length. The innovative idea and challenge of the project is to develop and install a dynamic fleet management system that allows the operator to switch between the different modes within the different periods of the day according to the dynamic transportation demands of the users. We model the underlying online transportation system and propose a correspond- ing fleet management framework, to handle modes, demands and commands. We consider two modes of circulation, tram and elevator mode, propose for each mode appropriate on- line algorithms and evaluate their performance, both in terms of competitive analysis and practical behavior.