Citation

Wang H, Huang Y, Khajepour A, Cao D, Lv C. IEEE Trans. Vehicular Tech. 2020; 69(8): 8164-8175.

Copyright

(Copyright © 2020, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TVT.2020.2996954

PMID

unavailable

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.

Language: en

Keywords

autonomous driving; autonomous vehicles; Autonomous vehicles; decision making; Decision making; ethical aspects; Ethical decision-making; ethical decision-making platform; ethical rules; Ethics; evolutionary computation; Lexicographic Optimization; lexicographic optimization-based model predictive controller; model predictive control; obstacle avoidance; optimisation; Optimization; potential field; predictive control; predictive control framework; road traffic control; road vehicles; Tires; traditional decision-making algorithm; Vehicle crash testing