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Law and order

Investigating the effects of conflictual situations in manual and automated driving in a German sample

Bibliographic Data

ID21642927
AuthorsAnnika Stampf (0000-0001-5539-4957, Universität Ulm, corresponding author), Ann-Kathrin Knuth (0009-0002-5927-9096, Universität Ulm), Mark Colley (0000-0001-5207-5029, Universität Ulm), Enrico Rukzio (0000-0002-4213-2226, Universität Ulm)
Year2024
Volume187
Pages103260
Publication date2024-07-01
Open AccessYes
TypeARTICLE
VenueInternational Journal of Human-Computer Studies (JOURNAL)
Journal identifiersISSN: 1071-5819 • E-ISSN: 1095-9300
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.ijhcs.2024.103260
OpenAlexW4393132091
LanguageEN
References cited46

Minor violations of traffic regulations are common today and partially socially accepted. Automated vehicles (AVs), however, will be obliged to keep to the letter of the law. This can lead to situations where user requests cause the AV to reach its legal boundaries, creating novel user-vehicle conflicts. To investigate whether traffic-violating driver interests are transferred to the automated context, we conducted an online survey with three conflict-prone scenarios (N=49). The results indicate that legally compliant AV behavior is desired but that users would intervene in the vehicle’s behavior to enforce interests. In a subsequent Virtual Reality study (N=30), we evaluated the effect of legal boundary-handling strategies (Responsibility and Control Shift, Responsibility Shift, No Shift) and other traffic participants’ violating traffic regulations on behavior, conflict, and trust in a legally conflict-prone parking scenario. Results show that conflict is perceived significantly higher in all strategies compared to the manual baseline, while situational trust in the vehicle is higher in the automated conditions but independent of the handling strategy

Business · Computer security · German · Political science · Situation awareness · Situational ethics · Computer Science · Engineering · Ethics and Social Impacts of AI · Human-Automation Interaction and Safety · Law · Psychology · Traffic and Road Safety · Artificial Intelligence

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