Abstract

Ethical morality is one of the significant issues in self-driving cars. The paper provides a newer approach to solve the ethical decision problems in self-driving cars until there is no concrete ethical decision to all problems. This paper gives a two-way approach to solve a problem, with first being the mapping of problem to the solution already known or which has a fixed set of solutions and action priorities defined to a problem previously. Now, if no solution is found or mapping is unsuccessful, then the second stage activates, where the solution from Deep Q-learning model is calculated. It estimates the best Q value and returns that solution or action which maximizes the reward at that instance. The reward function is designed with decreasing priorities and acts accordingly, where the users can change or define their priorities if needed. The case study and results show that the solution that is present in the paper will lead to solving ethical morality problems in self-driving cars up to a great extent.