An Ethical Trajectory Planning Algorithm for Autonomous Vehicles
December 16, 2022 Β· Declared Dead Β· π Nature Machine Intelligence
"No code URL or promise found in abstract"
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Authors
Maximilian Geisslinger, Franziska Poszler, Markus Lienkamp
arXiv ID
2212.08577
Category
cs.RO: Robotics
Cross-listed
cs.CY
Citations
110
Venue
Nature Machine Intelligence
Last Checked
3 months ago
Abstract
With the rise of AI and automation, moral decisions are being put into the hands of algorithms that were formerly the preserve of humans. In autonomous driving, a variety of such decisions with ethical implications are made by algorithms for behavior and trajectory planning. Therefore, 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 essential 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 the authors' knowledge, this is the first ethical algorithm for trajectory planning of autonomous vehicles in line with the 20 recommendations from the EU Commission expert group and with general applicability to various traffic situations. We showcase the ethical behavior of our algorithm in selected scenarios and provide an empirical analysis of the ethical principles in 2000 scenarios. The code used in this research is available as open-source software.
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