Micromobility is a form of transportation and an efficient urban mobility solution that can include human-powered or electric vehicles for short-distance travel such as traditional bicycles, e-bikes, and e-scooters. It refers to lightweight personal vehicles with a maximum speed of 45 km/h and a maximum weight of 350 kg. Effectively, micromobility safety represents one of the most critical concerns of vulnerable road users (VRUs) such as cyclists and employees of courier companies. Various measures and micromobility protective equipment (PE) have been used to enhance VRU safety and reduce traffic accidents involving VRUs. Therefore, evaluating the effectiveness of these PE such as high-visibility clothing and helmets is very important to ensure that they can successfully prevent or reduce the risk of accidents and injuries. In this paper, we present a data-driven approach for evaluating the effectiveness of micromobility PE. This novel method relies on data collected directly from micro-vehicles and their users by using various techniques, including a web-based questionnaire, micro-vehicle sensor kit, and micromobility hazards detector. Effectively, these data collection tools, services, and questionnaire have been developed and designed to be used for collecting real data as soon as the participants recruiting process is finalised. Therefore, synthetic data were generated and used to demonstrate that the proposed method is feasible and can work in practice. This data is solely used to show some examples of data analysis procedures and to demonstrate some results as a proof-of-concept for micromobility PE effectiveness evaluation. Hence, the all findings mentioned in this paper are not actual or empirical results but provided only for illustrative purposes to show the format of the expected results when real data is used.
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Almohammad et al. (2025) studied this question.