NNL.20.001 – Perceptive acting under uncertainty: safety solutions for autonomous systems
Recent technologies like GPS, smartphones, smart wearables, drones, or self-driving vehicles are changing the way we interact with others in our environment. While smartphones have already become ubiquitous and indispensable, others technologies, like drones and self-driving cars, are much more difficult to integrate, also for society at large. Developing self-driving cars behave annoyingly unpredictable for other drivers, and can fail dramatically in complex city environments, and similar problems exist with drones. How do we make the behavior of autonomous vehicles predictable for humans, to avoid conflict and dangerous situations for other traffic participants? Humans are very good at predicting and adequately responding to behaviors of other humans, even in demanding environments; machines lack this human-predictable behavior needed to make urban mobility safe. This project will chart out these human behaviors and implement them as ‘neuroware’ to artificial intelligence systems that can guide autonomous vehicles, like drones and self-driving cars, in a safe way. Scientific, industrial, and societal partners capitalize on a combination of psychology, neuroscience, artificial intelligence, engineering and robotics to develop integrated solutions for the interactions between humans and autonomous systems, and design protocols, rules and innovative systems for urban mobility and safety.
action and motion planning under uncertainty, autonomous vehicles, predictability., seamless human-machine interaction
2Getthere, Eindhoven University of Technology (TU/e), NLR, NXP, Radboud Universiteit Nijmegen (RU), Technische Universiteit Delft (TUD), TNO, UvA
|Organisation||Centrum Wiskunde & Informatica (CWI)|
|Name||Prof.dr. S.M. (Sander) Bohté|