EXPERIMENTAL ANALYSIS OF ELECTRIC SOOTER DYNAMICS

In recent years, electric micromobility vehicles (e.g., electric scooters, unicycles, skateboards, onewheels, and segways) have gained significant popularity. From both traffic and environmental perspectives, micromobility vehicles have benefits, but controlling these vehicles poses a much more significant challenge for users. As a result, an increased number of road accidents involving personal injuries is realized world-wide. Therefore, exploring the dynamics of the vehicle-human system is essential for making micromobility vehicles safer. In our research, we aim to gather information about the motion of an electric scooter. Due to the small size of the vehicle, the rider’s movement significantly influences the motion of the vehicle. Therefore, it is essential to acquire data on how the riders move on the vehicle. In this study, we also examine how accurately a neural networkbased algorithm can determine the position of the rider’s center of mass based on camera footage.