Abstract
The unparalleled technological advances in vehicle automation and artificial intelligence have made autonomous vehicle (AV) technically available for extensive road tests [1] and, even recently, for limited commercial mobility services [2]. Notwithstanding these advances, a critical challenge to integration of AV into the real-world transportation systems as well as our personal and professional lives is establishing ethical regulations for AV. In particular, such ethical principles would determine how an AV makes moral decisions in dilemma-inducing situations, for instance, whether it should hit a teenager pedestrian to spare two senior passengers onboard.
This research project looks at this problem not from the philosophical perspective, which prescribes moral behavior of an AV [3]. Instead, this project describes the public expectation and perception of a moral AV, which is the perspective of econom(etr)ics, psychology, and cognitive science disciplines. To do so, the studies in economics and psychology explore the process of human decision making focusing on the morality dimension of decisions, since many of decisions humans routinely make can have a moral aspect. A recent example is the decision of receiving vaccination at a cost (e.g., side effects for the receiver) to immune the community and the society. This research project aims at understanding the public expectations of moral AVs by unravelling the cognitive process of human decisions making considering the decisions’ morality aspect. This objective will be accomplished in two consecutive tasks explained below.
Task 1: Designing and Conducting a Survey Using Stated Preferences (SP) Experiment. For the purpose of analyzing consumers’ choice behavior (e.g., travel behavior), the SP experimental design method provides a rigorous and efficient tool, which is extensively applied in the relevant literature. Applying this tool, this task designs a survey to collect an empirical dataset on human subjects. The PI plans to accomplish the required IRB certificate for data collection.
Task 2: Developing a Modeling Framework on Humans’ Decision Making. This task focuses on developing methods built on econom(etr)ics, psychology, and cognitive science disciplines, to be capable of capturing morality dimension of decisions. One of such methods is choice theory-based model of latent class choice, which is capable of capturing “reason-based” morality. Another example is random regret model, which can capturie “emotion-based” morality (since regret is an emotion). The models are then empirically estimated on the dataset collected in Task 1.
References:
1. Zoellick JC, Kuhlmey A, Schenk L, Schindel D, Blüher S (2019) Amused, accepted, and used? Attitudes and emotions towards automated vehicles, their relationships, and predictive value for usage intention. Transportation Research Part F: Traffic Psychology and Behaviour, 65:68–78. https://doi.org/10.1016/j.trf.2019.07.009
2. Waymo (2020) Waymo is opening its fully driverless service to the general public in Phoenix. Retrieved from: https://blog.waymo.com/2020/10/waymo-is-opening-its-fully-driverless.html.
3. Geisslinger M, Poszler F, Betz J, Lütge C, Lienkamp M (2021) Autonomous driving ethics: From Trolley problem to ethics of risk. Philosophy & Technology, :1–23. https://doi.org/10.1007/s13347-021-00449-4
Description
Timeline
Strategic Description / RD&T
Page 17 of the USDOT’s RD&T Plan: Table 3: “Data-Driven System Safety”
Deployment Plan
Expected Outcomes/Impacts
By eliciting the public preferences for a moral autonomous vehicle (AV), the expected outcomes of this research project will be beneficial to society through providing policy implications which can be intriguing for stakeholders, industries, and policy makers. The research findings will be disseminated to the broader community via publications in journals and presentations at conferences. Finally, this project will integrate the research on understanding morality in humans’ decision making in the era of automation into education by recruiting and mentoring minority (under)graduate students and women to engineering at UTRGV.
Expected Outputs
The expected outcomes can provide: (i) policy implications which can be intriguing for stakeholders and industries as well as policy makers, as emphasized by recent studies on transportation policy and autonomous vehicle (AV) ethics; (ii) a critical component of travel behavior analysis investigating users’ trust in and acceptance of AV; and (iii) an essential input for the research efforts beyond transportation area searching for a moral compass to equip artificial intelligence employed in AV.
TRID
The analysis of decision making process with a particular attention to the morality aspect has been the focus of a variety of disciplines such as economics, psychology, criminology, political science, and recently neuroscience. The related works of this project are in the areas of behavioral econom(etr)ics and behavioral psychology. In the area of travel behavior research, the ignorance of morality of autonomous vehicle (AV) decisions is striking, in light of the fact that the (potential) users’ preferences for AV ethics influences their trust in and acceptance of AV. One relevant study [25] investigates how consumers’ willingness-to-pay for AV is affected by their attitude towards morality. This calls for a rigorous research which is the objective of this project on an in-depth understanding of individuals’ perception of morality when AVs face a moral versus non-moral choice task.
References:
1. Morita T, Managi S (2020) Autonomous vehicles: Willingness to pay and the social dilemma. Transportation Research Part C: Emerging Technologies, 119:102748. https://doi.org/10.1016/j.trc.2020.102748
Individuals Involved
| Email |
Name |
Affiliation |
Role |
Position |
| fatemeh.nazari@utrgv.edu |
Nazari, Fatemeh |
University of Texas - Rio Grande Valley |
PI |
Faculty - Untenured, Tenure Track |
| h.noruzoliaee@utrgv.edu |
Noruzoliaee, Mohamadhossein |
University of Texas Rio Grande Valley |
Other |
Faculty - Untenured, Tenure Track |
Budget
Amount of UTC Funds Awarded
$
Total Project Budget (from all funding sources)
$110633.00
Documents
Match Sources
No match sources!
Partners
| Name |
Type |
| University of Texas - Rio Grande Valley |
Deployment & Equity Partner Deployment & Equity Partner |
