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 (\(5\) km/h and \(25\) 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.

近年来，微型汽车越来越多地参与城市交通，追随轻型、更实惠、环保的交通方式的实际趋势。在此类车辆中，电动滑板车（e-scooters）代表了基于应用程序的共享移动服务驱动的最受欢迎的示例。尽管有积极的影响，但不良的安全要求和不适问题也与这一新领域有关。电动滑板车最近的普及促使科学界研究性能和乘坐舒适性，试图改进车辆设计和安全法规。本研究的目的是评估电动滑板车在由七个减速带组成的现实环境中行驶时的振动。要求 14 名健康的年轻参与者（七名男性和七名女性）以两种不同的恒定速度（ \(5\) km/h 和\(25\) km/h）进行测试。人体主要部位以及电动滑板车都会获得加速度。该评估基于从信号时间历史中识别最大值和均方根。进行非参数统计分析，重点关注从车辆传递到人体的振动、电动滑板车的速度以及一些骑手的特征，例如性别、质量、惯用手和惯脚。均方根和低速测试通常强调大量显着差异。此外，对系统影响最大的参数是骑手的质量。总体而言，所提出的方法被证明是研究车辆骑手振动影响的有效工具。