Song, R., Potoglou, D. ![]() ![]() ![]() ![]() ![]() ![]() |
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Abstract
The implementation of ‘Digital Roads’ initiatives in the UK promises to revolutionise transportation through the integration of cutting-edge technologies such as artificial intelligence (AI) and connected vehicles. However, this technological advancement brings with it the potential for extensive data collection pertaining to road users. Understanding the concerns of these users is important for the successful adoption of these transformative transportation technologies and provides the foundation towards building user-centred ethical frameworks. This study reports evidence from five workshops with 20 participants from diverse backgrounds including computer science and cybersecurity, business, geography and planning. Each workshop captured user narratives including concerns, questions, and suggestions against three scenarios that were likely to be implemented on UK motorways in the future. The scenarios involved a hypothetical, but realistic implementation of various technologies aimed at enhancing road safety but could also be a threat to their privacy. For example, one scenario involved AI-based identification of bad driving behaviour under which participants were in turn, either a road user or the violator. The thematic analysis of the workshop data pointed towards six primary concerns: data privacy, technology reliability, data security, awareness of data collection practices, possible consequences of data collection, and the involvement of third-party entities. Addressing these concerns will be instrumental in fostering public trust and acceptance of new technologies in transportation. These findings also suggest the importance of transparency, awareness, data security, fairness, inclusivity, and accountability in ensuring data ethics within the realm of digital transportation infrastructure.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Schools > Geography and Planning (GEOPL) Schools > Business (Including Economics) Schools > Computer Science & Informatics |
Publisher: | Elsevier |
ISSN: | 1369-8478 |
Date of First Compliant Deposit: | 31 July 2025 |
Date of Acceptance: | 30 July 2025 |
Last Modified: | 11 Aug 2025 10:24 |
URI: | https://orca.cardiff.ac.uk/id/eprint/180188 |
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