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Cognitively-inspired episodic imagination for self-driving vehicles
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Interaction Lab (ILAB))ORCID iD: 0000-0003-0093-3655
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Interaction Lab (ILAB))
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, Netherlands. (Interaction Lab (ILAB))ORCID iD: 0000-0003-1177-4119
2019 (English)In: Towards Cognitive Vehicles: perception, learning and decision making under real-world constraints. Is bio-inspiration helpful?: Proceedings, 2019, p. 28-31Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

The controller of an autonomous vehicle needsthe ability to learn how to act in different driving scenariosthat it may face. A significant challenge is that it is difficult,dangerous, or even impossible to experience and explore variousactions in situations that might be encountered in the realworld. Autonomous vehicle control would therefore benefitfrom a mechanism that allows the safe exploration of actionpossibilities and their consequences, as well as the ability tolearn from experience thus gained to improve driving skills.In this paper we demonstrate a methodology that allows alearning agent to create simulations of possible situations. Thesesimulations can be chained together in a sequence that allowsthe progressive improvement of the agent’s performance suchthat the agent is able to appropriately deal with novel situationsat the end of training. This methodology takes inspirationfrom the human ability to imagine hypothetical situations usingepisodic simulation; we therefore refer to this methodology asepisodic imagination.An interesting question in this respect is what effect thestructuring of such a sequence of episodic imaginations hason performance. Here, we compare a random process to astructured one and initial results indicate  that a structuredsequence outperforms a random one.

Place, publisher, year, edition, pages
2019. p. 28-31
National Category
Robotics
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-18175OAI: oai:DiVA.org:his-18175DiVA, id: diva2:1388926
Conference
TCV2019: Towards Cognitive Vehicles: perception, learning and decision making under real-world constraints. Is bio-inspiration helpful? Workshop held as part of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019). Macau, China, November 8, 2019.
Funder
EU, Horizon 2020, 41365Available from: 2020-01-28 Created: 2020-01-28 Last updated: 2020-02-24Bibliographically approved

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Mahmoud, SaraSvensson, HenrikThill, Serge
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