Statistical Analysis of the Vibrations Transmitted From an Electric Kick Scooter to Riders

In recent years, micro-vehicles have been increasingly involved in urban mobility following the actual trend towards light, more affordable, and eco-friendly means of transportation. Among this vehicle category, the electric kick scooters (e-scooters) represent the most popular example driven by app-based sharing mobility services. Despite the positive implications, poor safety requirements and issues of discomfort are also related to this new segment. The recent spread of e-scooters is motivating the scientific community in investigating performance and ride comfort, in the attempt of improving vehicle design and safety regulations. The aim of this study is to evaluate e-scooter vibrations in driving in a realistic environment, constituted by bike path with seven speed bumps. Fourteen healthy young participants (seven males and seven females) are asked to conduct the test at two different constant velocities ( \(5\) $5$ km/h and \(25\) $25$ km/h). Accelerations are acquired at the main human body segments as well as on the e-scooter. The assessment is based on identifying maxima and root mean squares from signal time histories. A non-parametrical statistical analysis is performed focusing on vibrations transmitted from vehicle to human body, e-scooter velocity, and some rider’s characteristics such as gender, mass, dominant arm, and dominant foot. Root mean squares and tests at low velocity generally underline a larger number of significant differences. Moreover, the parameter which mostly influences the system is the rider’s mass. Overall, the proposed methodology proves to be an efficient tool to investigate the vehicle-rider vibrational influence.