Exploiting Dream-Like Simulation Mechanisms to Develop Safer Agents for Automated Driving

Mauro Da Lio, Alessandro Mazzalai, David Windridge, Serge Thill, Mehmed Yüksel, Andrea Saroldi, Luisa Andreone, Kevin Gurney, Sean R. Anderson, Hermann-Josef Heich

In: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC). IEEE Intelligent Transportation Systems Conference (IEEE ITSC-2017) October 16-19 Yokohama Japan IEEE 11/2017.


Automated driving needs unprecedented levels of reliably and safety before marked deployment. The average human driver fatal accident rate is 1 every 100 million miles. Automated vehicles will have to provably best these figures. This paper introduces the notion of dream-like mechanisms as a simulation technology to produce a large number of hypothetical design and test scenarios – especially focusing on variations of more frequent dangerous and near miss events. Grounded in the simulation hypothesis of cognition, we show here some principles for effective simulation mechanisms and an artificial cognitive system architecture that can learn from the simulated situations.


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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence