FEAT: Fleet management for Efficient and sustAinable electric micromobility sysTems

The FEAT project aims to develop efficient and sustainable fleet management strategies for shared electric micromobility systems (EmmS).

The goal is to jointly optimize the energy consumption and the level of service of EmmS fleets, by taking into account dynamic energy grid loads, stochastic travel demands, battery energy waste in idle status, and coordination with other transportation modes.

The approach is to use advanced machine learning models and state-of-the-art routing algorithms to empower the decision-making of where, when, and how to charge batteries, relocate vehicles, and swap batteries.

The results are of great potential to resolve the current chaos in cities that are inundated by e-bikes/e-scooters, and realize a highly accessible, energy-efficient, and complementary operation of EmmS.