Demand forecasting for Hopp's e-scooter fleet

Abstract

Cities all around the world are dealing with the adverse effects of automobile travel and are therefore moving towards a more sustainable urban transportation system. Hopp is a micromobility platform launched by a small team of software developers in Iceland in 2019. In this project, we designed, implemented, and tested a machine learning tool that predicts the locational demand for Hopp's e-scooters in the near future. This tool aims to help reduce expenses, increase the number of rented scooters, and improve the reliability of the service.