Application and design of a decision-making model in ethical dilemma for self-driving cars
Abstract Artificial intelligence (AI) has promoted application and development of self-driving cars. However, when self-driving cars encounter ethical dilemma, it is still hard to make a satisficing and clear decision-making by these present moral rules and mechanisms, which makes people distrust in...
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Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-91921-0 |
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| author | Guoman Liu Jing Sheng Zhen Tao |
| author_facet | Guoman Liu Jing Sheng Zhen Tao |
| author_sort | Guoman Liu |
| collection | DOAJ |
| description | Abstract Artificial intelligence (AI) has promoted application and development of self-driving cars. However, when self-driving cars encounter ethical dilemma, it is still hard to make a satisficing and clear decision-making by these present moral rules and mechanisms, which makes people distrust in self-driving cars in real life. It is necessary to design a computational and multi-factor decision-making model for self-driving cars. ACWADOE (WADOE Based on Attribute Correlation) is proposed to achieve probabilities of going straight and swerving in ethical dilemmas from more influencing factors to make satisficing and clear decision-making as far as possible. In order to construct ACWADOE model, the prior probability between influencing factor and decision-making is calculated by survey data in moral machine, which can express human preferences and tendencies, align with the requirements of the majority. Then 116 dilemmas are designed and chosen to solve correlation coefficient between influencing factors. Moreover, 84 comparative dilemmas are designed to achieve information gain ratio between influencing factors, then the weight of each factor in decision-making can be calculated by constructing pairwise comparison matrix. Lastly, 40 dilemmas are used to test and verify NB (Naive Bayes), ADOE (Averaged One-Dependence Estimators), WADOE (Weighted ADOE) and ACWADOE respectively. The test results show that ACWADOE is more suitable with human requirements than other models, its accuracy is 92.5%. Furthermore, ACWADOE not only provides a computational decision-making model in ethical dilemma for self-driving cars, but also provides a few references for other AI systems to solve ethical dilemma, which is conducive to make satisficing and clear decisions. |
| format | Article |
| id | doaj-art-1b682a0ca65044b6892f5ba4a88aba74 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-1b682a0ca65044b6892f5ba4a88aba742025-08-20T02:56:16ZengNature PortfolioScientific Reports2045-23222025-03-011511910.1038/s41598-025-91921-0Application and design of a decision-making model in ethical dilemma for self-driving carsGuoman Liu0Jing Sheng1Zhen Tao2Jiangxi Province Key Laboratory of Precision Drive and Equipment, Nanchang Institute of TechnologyJiangxi Province Key Laboratory of Precision Drive and Equipment, Nanchang Institute of TechnologyJiangxi Province Key Laboratory of Precision Drive and Equipment, Nanchang Institute of TechnologyAbstract Artificial intelligence (AI) has promoted application and development of self-driving cars. However, when self-driving cars encounter ethical dilemma, it is still hard to make a satisficing and clear decision-making by these present moral rules and mechanisms, which makes people distrust in self-driving cars in real life. It is necessary to design a computational and multi-factor decision-making model for self-driving cars. ACWADOE (WADOE Based on Attribute Correlation) is proposed to achieve probabilities of going straight and swerving in ethical dilemmas from more influencing factors to make satisficing and clear decision-making as far as possible. In order to construct ACWADOE model, the prior probability between influencing factor and decision-making is calculated by survey data in moral machine, which can express human preferences and tendencies, align with the requirements of the majority. Then 116 dilemmas are designed and chosen to solve correlation coefficient between influencing factors. Moreover, 84 comparative dilemmas are designed to achieve information gain ratio between influencing factors, then the weight of each factor in decision-making can be calculated by constructing pairwise comparison matrix. Lastly, 40 dilemmas are used to test and verify NB (Naive Bayes), ADOE (Averaged One-Dependence Estimators), WADOE (Weighted ADOE) and ACWADOE respectively. The test results show that ACWADOE is more suitable with human requirements than other models, its accuracy is 92.5%. Furthermore, ACWADOE not only provides a computational decision-making model in ethical dilemma for self-driving cars, but also provides a few references for other AI systems to solve ethical dilemma, which is conducive to make satisficing and clear decisions.https://doi.org/10.1038/s41598-025-91921-0Self-driving carsEthical dilemmasDecision-makingComparison matrix |
| spellingShingle | Guoman Liu Jing Sheng Zhen Tao Application and design of a decision-making model in ethical dilemma for self-driving cars Scientific Reports Self-driving cars Ethical dilemmas Decision-making Comparison matrix |
| title | Application and design of a decision-making model in ethical dilemma for self-driving cars |
| title_full | Application and design of a decision-making model in ethical dilemma for self-driving cars |
| title_fullStr | Application and design of a decision-making model in ethical dilemma for self-driving cars |
| title_full_unstemmed | Application and design of a decision-making model in ethical dilemma for self-driving cars |
| title_short | Application and design of a decision-making model in ethical dilemma for self-driving cars |
| title_sort | application and design of a decision making model in ethical dilemma for self driving cars |
| topic | Self-driving cars Ethical dilemmas Decision-making Comparison matrix |
| url | https://doi.org/10.1038/s41598-025-91921-0 |
| work_keys_str_mv | AT guomanliu applicationanddesignofadecisionmakingmodelinethicaldilemmaforselfdrivingcars AT jingsheng applicationanddesignofadecisionmakingmodelinethicaldilemmaforselfdrivingcars AT zhentao applicationanddesignofadecisionmakingmodelinethicaldilemmaforselfdrivingcars |