At present, unmanned driving technology has made great progress, while those research on its related ethical issues, laws, and traffic regulations are relatively lagging. In particular, it is still a problem how unmanned vehicles make a decision when they encounter ethical dilemmas where traffic collision is inevitable. So it must hinder the application and development of unmanned driving technology. Firstly, 1048575 survey data collected by Moral Machine online experiment platform is analyzed to calculate the prior probability that the straight being protector or sacrificer in ethical dilemmas with single feature. Then, 116 multifeature ethical dilemmas are designed and surveyed. The collected survey data are analyzed to determine decision-making for these ethical dilemmas by adopting the majority principle and to calculate correlation coefficient between attributes, then an improved Naive Bayes algorithm based on attribute correlation (ACNB) is established to solve the problem of unmanned driving decision in multifeature ethical dilemmas. Furthermore, these ethical dilemmas are used to test and verify traditional NB, ADOE, WADOE, CFWNB, and ACNB, respectively. According to the posterior probability that the straight being protector or sacrificer in those ethical dilemmas, classification and decision are made in these ethical dilemmas. Then, the decisions based on these algorithms are compared with human decisions to judge whether these decisions are right. The test results show that ACNB and CFWNB are more consistent with human decisions than other algorithms, and ACNB is more conductive to improve unmanned vehicle’s decision robustness than NB. Therefore, applying ACNB to unmanned vehicles has a good role, which will provide a new research point for unmanned driving ethical decision and a few references for formulating and updating traffic laws and regulations related to unmanned driving technology for traffic regulation authorities.

No abstract

At present, many scholars found many influencing factors in self-driving ethical decision by the way of questionnaire and theoretical researches. However, the important influencing factors can’t still be extracted and determined in self-driving ethical decision, which is not conducive to construct decision model and framework in moral dilemmas and causes information overlap and interference by multi-variable and multi-collinearity. Therefore, it is necessary to extract a few important factors from these influencing factors in self-driving ethical decision. 116 normal dilemmas and 10 comparative dilemmas, in which there are only two influencing factors to be compared, are designed to be surveyed in this paper. According to the probability of the straight choosing as protector, the comparative result and location in decision tree model, the importance is determined in self-driving ethical decision, then a few important influencing factors are extracted and determined in self-driving ethical decision. Eventually, these factors of species, harm, traffic laws, number, age and self-interests are regard as the important influencing factors in self-driving ethical decision, which provide a few theoretical guidance to construct and design model and framework in self-driving ethical decision for car manufactures. Furthermore, they provide a few references to formulate traffic laws and regulations related to self-driving technology for traffic management authentication.