Goodness behind a wheel: moral judgment in realistic traffic simulations featuring Agents, Deeds, and Consequences.

Authors

Dario Cecchini, Michael Pflanzer, Sam Cacace, Veljko Dubljevic

Published in

Frontiers in psychology. Volume 17. Pages 1885843. Epub Sep 28, 2026.

Abstract

Investigating how different stakeholders evaluate traffic situations is essential for aligning autonomous vehicle (AV) decision-making with common-sense moral expectations. Yet, empirical studies on traffic moral judgment remain limited and almost exclusively focused on dramatic high-stakes situations. To address this gap, this paper presents two studies testing moral judgment in low-stakes ordinary traffic simulations. Drawing on the ADC model of moral judgment, both studies systematically manipulated key moral features: the character of the driver (Agent), adherence to traffic rules (Deed), and the presence or absence of a collision (Consequences). These components were embedded in a variety of stimuli, including textual vignettes, computer-generated video clips, and immersive audio-visual simulations. Data were collected from both expert ethicists (Study 1) and lay participants (Study 2). The results show that participants' moral judgments were consistently and strongly influenced by the character of the agent, whereas the effects of rule compliance and consequences were less robust. The mode of presentation (textual vs. audio-visual) significantly moderated these effects in mixed ways, suggesting that different formats may be better suited to conveying specific types of moral information. Notably, Study 1 revealed that expert ethicists tended to converge in their evaluations of low-stakes traffic scenarios, despite endorsing different moral theories. This convergence supports the feasibility of designing AV decision-making algorithms based on shared ethical judgments. Furthermore, the findings highlight that character-based considerations play a significant role in moral judgment of traffic scenarios-alongside deontological and consequentialist reasoning.

PMID:
42865575
Bibliographic data and abstract were imported from PubMed on 13 Oct 2026.

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