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Ethical decision-making in older drivers during critical driving situations: An online experiment

Authors :
Amandeep Singh
Sarah Yahoodik
Yovela Murzello
Samuel Petkac
Yusuke Yamani
Siby Samuel
Source :
Journal of Intelligent and Connected Vehicles, Vol 7, Iss 1, Pp 30-37 (2024)
Publication Year :
2024
Publisher :
Tsinghua University Press, 2024.

Abstract

The present study examined the impact of aging on ethical decision-making in simulated critical driving scenarios. 204 participants from North America, grouped into two age groups (18–30 years and 65 years and above), were asked to decide whether their simulated automated vehicle should stay in or change from the current lane in scenarios mimicking the Trolley Problem. Each participant viewed a video clip rendered by the driving simulator at Old Dominion University and pressed the space-bar if they decided to intervene in the control of the simulated automated vehicle in an online experiment. Bayesian hierarchical models were used to analyze participants’ responses, response time, and acceptability of utilitarian ethical decision-making. The results showed significant pedestrian placement, age, and time-to-collision (TTC) effects on participants’ ethical decisions. When pedestrians were in the right lane, participants were more likely to switch lanes, indicating a utilitarian approach prioritizing pedestrian safety. Younger participants were more likely to switch lanes in general compared to older participants. The results imply that older drivers can maintain their ability to respond to ethically fraught scenarios with their tendency to switch lanes more frequently than younger counterparts, even when the tasks interacting with an automated driving system. The current findings may inform the development of decision algorithms for intelligent and connected vehicles by considering potential ethical dilemmas faced by human drivers across different age groups.

Details

Language :
English
ISSN :
23999802
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Journal of Intelligent and Connected Vehicles
Publication Type :
Academic Journal
Accession number :
edsdoj.9e64982e35554fcf8074da9fade0aff6
Document Type :
article
Full Text :
https://doi.org/10.26599/JICV.2023.9210031