An ethical trajectory planning algorithm for autonomous vehicles

In situations where some risk of injury is unavoidable for self-driving vehicles, how risk is distributed becomes an ethical question. Geisslinger and colleagues have developed a planning algorithm that takes five ethical principles into account and aims to comply with the emerging EU regulatory recommendations. With the rise of artificial intelligence and automation, moral decisions that were formerly the preserve of humans are being put into the hands of algorithms. In autonomous driving, a variety of such decisions with ethical implications are made by algorithms for behaviour and trajectory planning. Therefore, here we present an ethical trajectory planning algorithm with a framework that aims at a fair distribution of risk among road users. Our implementation incorporates a combination of five ethical principles: minimization of the overall risk, priority for the worst-off, equal treatment of people, responsibility and maximum acceptable risk. To the best of our knowledge, this is the first ethical algorithm for trajectory planning of autonomous vehicles in line with the 20 recommendations from the European Union Commission expert group and with general applicability to various traffic situations. We showcase the ethical behaviour of our algorithm in selected scenarios and provide an empirical analysis of the ethical principles in 2,000 scenarios. The code used in this research is available as open-source software.