Assessing e-scooters safety and drivability: a quantitative analysis

Abstract

E-scooters are now massively present in urban environments as a shared last-mile solution. Their apparent ease of drivability favored their diffusion, but also actually raises safety concerns. In this work, we propose a data-driven approach to map e-scooters mechanical specifications to drivability and safety metrics, the latter appropriately defined and computed based on experimental data. An ad-hoc HW/SW platform was designed for this purpose, so as to be portable and installed on seven different e-Scooters that were tested in trips carried out in the city of Milan. The proposed approach allowed us to characterize both stability and comfort metrics on the different vehicles, and compare them also with a qualitative driving test carried out by a journalist making driving tests. The quantitative analysis matched the impressions of the human driver, and it disclosed an interesting mapping between the perceived risk and the vehicle characteristics evaluated according to the two metrics proposed.