Abstract
Despite the advances made in the technical availability of autonomous vehicles (AVs) for road tests [1] and even limited commercial mobility services [2], a critical challenge in the integration of AVs into the real-world transportation systems and our lives is establishing safety and ethical regulations. In particular, principles are required for an AV to make safe and ethical decisions in high-impact low-frequency situations that induce dilemmas, such as whether to hit pedestrians to spare passengers onboard? The absence of such policies can concern the potential users about safety aspects of AVs ,which is identified to negatively affect the public acceptance of the AV technology, as highlighted by the findings of the PI’s previous research [3].
This project is focused on designing these policies derived from the research on the potential autonomous system users’ expectations and perception of a safe AV through exploring how the users themselves would make decisions that entail a dilemma-inducing situation. This project will be the second Phase of the ongoing project from the previous year. In particular, this proposed work will be built on and complement the first Phase through accomplishing three tasks explained below.
Task 1 - Launching Stated Preferences (S.P.) Survey to Collect Sample Datasets on Two Groups of Individuals. The S.P. survey is designed in Phase I using experimental design methods which is demonstrated to be a rigorous and efficient tool for collecting datasets on individual persons’ opinions and preferences [5]. In Phase II, the results of the pilot dataset collected in Phase 1 will be utilized for updating the survey. Then, the survey will be fully launched on two population groups with distinctive heterogenous attitudes. The PI has the experience of designing and dissemination S.P. surveys in a different context [6].
Task 2 - Estimating Modeling Frameworks Capturing Heterogeneity of Behavior on the Datasets Collected in Task 1. This task focuses on estimating methods developed in Phase I which are built on behavioral economics, mathematical psychology, and cognitive science. These methods are capable of capturing morality dimension of decisions as well as the heterogenous behavior of individual persons. One of such methods is choice theory-based model of latent class choice, which is capable of capturing “reason-based” morality and at the same time endogenously classifies persons into groups to be homogenous with respect to attitudes within the groups and heterogenous across the groups. The PI has the experience of developing and estimating such models in different contexts [7, 8]. The models are then empirically estimated on the datasets collected in Task 1.
Task 3 - Integrating Research into Teaching. The research findings from Tasks 1 and 2 will be presented to the students of the course on Transportation Engineering. The purpose is familiarizing undergraduate students with advanced research topics through presenting the findings of this study. This will then be followed by a discussion session by groups of students who will be sharing their ideas and discussion results to all their peers.
References:
1. Traffic Lab (2024) Automated driving system testing and evaluation. Retrieved from: https://traffic.engin.umich.edu/research/automated-vehicle-system-testing-and-evaluation.
2. Waymo (2024) Ride with Waymo One. Retrieved from: https://waymo.com/waymo-one/.
3. Nazari F, Noruzoliaee M (2024) On the role of perceived safety concerns on public acceptance behavior of autonomous vehicles. https://rosap.ntl.bts.gov/view/dot/77511.
4. 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.
5. Chorus CG (2015) Models of moral decision making: Literature review and research agenda for discrete choice analysis. Journal of Choice Modelling, 16:69–85. https://doi.org/10.1016/j.jocm.2015.08.001.
6. Nazari F, Noruzoliaee M, Mohammadian A (Kouros) (2023) Electric vehicle adoption behavior and vehicle transaction decision: Estimating an integrated choice model with latent variables on a retrospective vehicle survey. Transportation Research Record: Journal of the Transportation Research Board, :1–20. https://doi.org/10.1177/03611981231184875.
7. Nazari F, Noruzoliaee M, Mohammadian AK (2018) Shared versus private mobility: Modeling public interest in autonomous vehicles accounting for latent attitudes. Transportation Research Part C: Emerging Technologies, 97(Journal Article):456–477. https://doi.org/10.1016/j.trc.2018.11.005.
8. Nazari F, Mohammadian AK (2023) Modeling vehicle-miles of travel accounting for latent heterogeneity. Transport Policy, 133:45–53. https://doi.org/10.1016/j.tranpol.2023.01.005
Description
Timeline
Strategic Description / RD&T
Section left blank until USDOT’s new priorities and RD&T strategic goals are available in Spring 2026.
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 beneficial to 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 human decision making in the era of automation into education in two ways including: (i) recruiting and mentoring the next generation engineering workforce at UTRGV; and (ii) integrating the research study into teaching through presenting the study findings to the students of the course on Transportation Engineering and moderating a follow-up discussion session.
Expected Outputs
The expected outcomes can provide: (i) policy implications which can inform stakeholders and industries as well as policy makers, as emphasized by recent studies on transportation policy and autonomous vehicle (AV) safety; (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 decision-making compass to equip artificial intelligence employed in AV.
TRID
The analysis of decision making process 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 safety 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 dilemma-inducing 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 |
Budget
Amount of UTC Funds Awarded
$50495.00
Total Project Budget (from all funding sources)
$78847.00
Documents
Match Sources
No match sources!
Partners
| Name |
Type |
| University of Texas - Rio Grande Valley |
Deployment Partner_ Deployment Partner_ |
