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Automated Vehicle Regulation Needs to Speak to Code, not to Humans: Keeping Safety and Ethics in the Public Domain
RISE Research Institutes of Sweden, Digital Systems, Data Science.ORCID iD: 0000-0003-3995-8833
RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.
Bundeswehr University Munich, Germany.
2025 (English)In: Philosophy & Technology, ISSN 2210-5433, E-ISSN 2210-5441, Vol. 38, no 1, article id 15Article in journal (Refereed) Published
Abstract [en]

In anticipation of the market introduction of highly and fully automated vehicles, regulations for their behavior in public road traffic are emerging in various countries and regions. Yet, as we show using the example of EU and German regulations, these rules are both incomplete and exceptionally vague. In this paper we introduce three traffic scenarios highlighting conflicting ethical, legal, and utility-related claims, and perform a legal analysis with regards to the expected behavior of AVs in these scenarios. We show that the existing regulatory framework disregards the realities of algorithmic decision-making in automated vehicles, such as the incomplete and imprecise perception of their environment and the probabilistic nature of their predictions. Importantly, the current regulations are written in abstract language addressing human interpreters rather than the precise logical-numerical computer code. We argue that the required interpretation and translation of the abstract legal language into the logical-numerical domain is so ambiguous that the regulations as they stand fail to guide or limit automated vehicle behavior in any meaningful way. This comes with significant ethical implications, as the interpretation and translation is unavoidable and, if not provided by regulatory bodies, will have to be performed by manufacturers. We argue that ethical decisions with significant impact on public safety must not be delegated to private companies, and thus, regulatory frameworks need significant improvements. 

Place, publisher, year, edition, pages
Springer Science and Business Media B.V. , 2025. Vol. 38, no 1, article id 15
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-78041DOI: 10.1007/s13347-025-00846-zScopus ID: 2-s2.0-85217447957OAI: oai:DiVA.org:ri-78041DiVA, id: diva2:2000432
Available from: 2025-09-24 Created: 2025-09-24 Last updated: 2025-09-24Bibliographically approved

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Sütfeld, Leon

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