Exploiting Dream-Like Simulation Mechanisms to Develop Safer Agents for Automated Driving The "Dreams4Cars" EU Research and Innovation ActionShow others and affiliations
2017 (English)In: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), IEEE, 2017Conference paper, Published paper (Refereed)
Abstract [en]
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.
Place, publisher, year, edition, pages
IEEE, 2017.
Series
IEEE International Conference on Intelligent Transportation Systems, ISSN 2153-0009, E-ISSN 2153-0017
Keywords [en]
Automated driving, Co-Driver Agent, Artificial Cognitive Systems, Learning by simulations, Simulation Hypothesis of Cognition
National Category
Civil Engineering Electrical Engineering, Electronic Engineering, Information Engineering Mechanical Engineering Other Engineering and Technologies
Research subject
Interaction Lab (ILAB); INF302 Autonomous Intelligent Systems
Identifiers
URN: urn:nbn:se:his:diva-15584DOI: 10.1109/ITSC.2017.8317649ISI: 000432373000064Scopus ID: 2-s2.0-85046269567ISBN: 978-1-5386-1526-3 (electronic)ISBN: 978-1-5386-1527-0 (print)OAI: oai:DiVA.org:his-15584DiVA, id: diva2:1218470
Conference
20th IEEE International Conference on Intelligent Transportation Systems (ITSC), Yokohama, Japan, October 16-19, 2017
2018-06-142018-06-142023-01-03Bibliographically approved