Lea Pődör
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Publications - 2
Unanswered Questions on the Registration of Electric Scooters from the Perspective of the Automotive Industry and the Law
Publication Name: Periodica Polytechnica Transportation Engineering
Publication Date: 2025-08-15
Volume: 53
Issue: 4
Page Range: 364-370
Description:
The rise of micromobility has brought increased use of low-speed transport devices such as electric scooters, Segways, and e-bikes. Despite their global popularity, the legal status of electric scooters remains unclear. A key regulatory question is whether e-scooters should be classified as vehicles. While some European countries consider them vehicles, others place them under existing categories like mopeds or bicycles, or even classify them as pedestrian devices. This classification affects all subsequent regulatory considerations. This study focuses on the registration of electric scooters, a topic with limited information despite its potential to address legal issues like theft and liability. The analysis examines regulatory frameworks in select European countries, compares them with practices in certain U.S. states, and highlights successful approaches in Asia, notably Singapore. The findings emphasize the role of vehicle databases in legal problem-solving and evaluate the effectiveness of existing systems. It may also be an incentive for the legislator to consider whether appropriate solutions can be found for the registration of other means of transport (e.g., bicycles, mopeds) and whether the adoption of these options could be appropriate for electric scooters.
Open Access: Yes
DOI: 10.3311/PPtr.38788
The Role of Vehicle Diagnostics in Supporting the Law-Abiding “Behavior” of Self-Driving Vehicles †
Publication Name: Engineering Proceedings
Publication Date: 2024-01-01
Volume: 79
Issue: 1
Page Range: Unknown
Description:
The aim of this paper is to look at the pillars for developing the law-abiding “behavior” of self-driving cars. The paper will analyze the potential of artificial intelligence, machine learning mechanisms, and the transformation of rules into algorithms for self-driving cars, and highlight the vehicle diagnostics context. The analysis is expected to demonstrate that the transformation of rules into algorithms alone is not sufficient for unhindered transport, as there is a strong need for the application of vehicle diagnostics to support and enhance obstacle and accident-free transport. The technological revolution in the field of self-driving vehicles calls for the development of common ground between technical sciences and law, which are trying to make the idea of safe and sustainable transport part of everyday life.
Open Access: Yes