Micro Mobility

Micromobility, encompassing e-scooters, e-bikes, and other small personal vehicles, aims to provide sustainable and efficient urban transportation alternatives. Current research focuses on improving safety through collision avoidance systems (using sensors and control algorithms), enhancing user behavior via feedback mechanisms, and optimizing energy consumption modeling with data-driven machine learning approaches, often employing convolutional neural networks. These advancements are crucial for increasing the societal acceptance and effectiveness of micromobility, impacting urban planning, transportation management, and the development of safer, more efficient personal mobility solutions.