Ethical Decision-Making Platform in Autonomous Vehicles With Lexicographic Optimization Based Model Predictive Controller
Abstract
Ethical decision-making during inevitable crashes, especially when humans involved, has become a big and sensitive roadblock for future mass adoption of autonomous vehicles. Towards addressing this challenge, this paper proposes a predictive control framework for ethical decision-making in autonomous driving using rational ethics. For flexibly implementing of ethical rules, the Lexicographic Optimization-based model predictive controller (LO-MPC) has been designed, in which obstacles and constraints are prioritized. Simulation environment is set up in PreScan, with different edge cases. The results show that the proposed LO-MPC approach has the capability to deal with the ethical decision-making during inevitable crashes by avoiding the obstacles with the assumed priority orders compared with traditional decision-making algorithm.
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Prior ethical AV approaches often rely on pre-defined rankings, hand-tuned parameters, or fixed weighting schemes, which may not adapt well to heterogeneous, real-world traffic.
“At the same time, they often rely on pre-defined rankings, hand-tuned parameters, or fixed weighting schemes, which may not adapt well to heterogeneous, real-world traffic.”
From Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving (2026) · cites this paper as [10]
Cites
Psychological roadblocks to the adoption of self-driving vehicles
Shariff, A., Bonnefon, J.-F., & Rahwan, I. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0202-6 · Cited by 336 · see citing works
Ethical Decision Making during Automated Vehicle Crashes
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Why Ethics Matters for Autonomous Cars
Lin, P. (2015) · Autonomes Fahren · doi:10.1007/978-3-662-45854-9_4 · Cited by 189 · see citing works
Implementable Ethics for Autonomous Vehicles
Gerdes, J. C., & Thornton, S. M. (2015) · Autonomes Fahren · doi:10.1007/978-3-662-45854-9_5 · Cited by 127 · see citing works
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Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving
Li, D., & Okhrin, O. (2026) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2026.3708405
- Authors
- Wang, H., Huang, Y., Khajepour, A., Cao, D., & Lv, C.
- Affiliations
- Tsinghua University (CN)
- University of Waterloo (CA)
- Nanyang Technological University (SG)
- Venue
- IEEE Transactions on Vehicular Technology
- Published
- 2020-08
- Volume
- 69
- Issue
- 8
- Pages
- 8164-8175
- ISSN
- 0018-9545 (ISSN-L)
- 1939-9359
- OpenAlex
- W3032008066
- Cited by
- 92
- References
- 4
- Citations by year
- 2026: 11 · 2025: 10 · 2024: 25 · 2023: 17 · 2022: 18 · 2021: 11
- FWCI
- 4.12
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Vehicular Technology (publishedVersion)
- Funders
- National Natural Science Foundation of China (U1964203)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Engineering › Automotive Engineering › Vehicle Dynamics and Control Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
- Keywords
- autonomous vehicles, ethical decision-making, rational ethics, lexicographic optimization, model predictive control, obstacle avoidance, ethical rules, collision avoidance
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