Angelo Domenico Vella

AijRaw acceleration at the human–vehicle interface i along direction ja¯ijISO-filtered acceleration at the human–vehicle interface i along direction jaijRMSRoot mean square of the ISO-filtered acce...

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.

Electric kick scooters have recently emerged in the urban scenario as a key solution to the mobility challenges of big city centers. While some studies have explored e-scooter dynamics, the complex interaction between the vehicle and its rider remains insufficiently understood. This study presents a numerical analysis of e-scooter braking maneuvers using a multibody modeling approach. A detailed in-plane multibody system is developed in Matlab/Simscape environment, including a high-fidelity model of a commercial electric kick scooter equipped with a front wheel motor and a rear braking disc system. To describe the human body response to the braking stimulus and its influence on vehicle dynamics, a semi-active anatomical dummy model is integrated. The multibody system is tuned and validated through a dedicated and comprehensive experimental campaign, specifically set-up to encompass three braking intensities and to measure key characteristics involving the dynamics of both vehicle and rider. The tuning process is based on an optimization algorithm designed to minimize the discrepancies between experimental and numerical signals. The developed multibody model provides a robust tool for analyzing the e-scooter dynamics in various driving scenarios, offering valuable insights to enhance safety and comfort.