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.

In recent years, significant improvements in the design of leg blade prosthetics have been carried out. After several advances in material and topological optimisations, sport-purpose feet prosthetics have reached high-level performances, allowing athletes with limb loss to participate in various sport activities at a competitive level. Since the knowledge of prosthetic mechanical behaviour is crucial for its optimal design, specific studies are required to meet the anthropometric characteristics of the athlete. This research work is focused on investigating the dynamic behaviour of a running blade prosthetic and developing a validated prosthetic model, placing particular emphasis on the definition of suitable material properties. An experimental modal analysis is performed on the Cheetah Xcel, Össur lower limb prosthetic. In contrast with what has already been presented in the literature, a roving hummer test under free–free conditions is proposed here to avoid the uncertainties due to constraint conditions. For the first time, blade prosthetic dynamic characteristics in free–free conditions are presented. Additionally, a novel Finite Element model of the prosthetic is developed and tuned on the basis of the experimental results. The modal assurance criterion index is exploited to compare experimental and numerical mode shapes. Starting from frequency response functions, the first six mode shapes are experimentally identified in the frequency range up to 750 Hz, including both bending and torsion. As expected, the bending in the vertical plane constitutes the primary mode shape: this kind of flexion enhances energy storage, enabling athletes to achieve an optimal running gait. This study shows the dynamic modal behaviour of a lower limb prosthetic in free–free conditions and demonstrates that a traditional isotropic material is not suitable in describing its dynamic features. The development of a model that exploits orthotropic material properties improves the alignment between experimental and numerical outcomes. This result is in agreement with the material composition of the prosthetic, which consists of carbon fibre layers.

The development of control strategies for autonomous vehicles requires a reliable and cost-effective validation approach. In this context, testbeds enabling repeatable experiments under controlled conditions are gaining relevance. Scaled vehicles have proven to be a valuable alternative to full-scale or simulation-based testing, enabling experimental validation while reducing costs and risks. This work presents a 1:5 scale modular vehicle platform, derived from a commercial Radio-Controlled (RC) vehicle and adapted as experimental testbed for control strategy validation and vehicle dynamics studies. The vehicle features an electric powertrain, operated through a Speedgoat Baseline Real-Time Target Machine (SBRTM). The hardware architecture includes a high-performance Inertial Measurement Unit (IMU) with embedded Global Navigation Satellite System (GNSS). An Extended Kalman Filter (EKF) is implemented to enhance positioning accuracy by fusing inertial and GNSS data, providing reliable estimates of the vehicle position, velocity, and orientation. Two path-following algorithms, i.e., Stanley Controller (SC) and the Linear Quadratic Regulator (LQR), are designed and integrated. Outdoor experimental tests enable the evaluation of tracking accuracy and robustness. The results demonstrate that the proposed scaled testbed constitutes a reliable and flexible platform for benchmarking autonomous vehicle controllers and enabling experimental testing.