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Using Recurrent Neural Networks for Action and Intention Recognition of Car Drivers
Chalmers University of Technology, Gothenburg, Sweden.
RISE Viktoria, Gothenburg, Sweden.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Viktoria, Gothenburg, Sweden.ORCID iD: 0000-0002-1043-8773
2019 (English)In: ICPRAM 2019 - Proceedings of the 8th International Conferenceon Pattern Recognition Applications and Methods, Setúbal, 2019, p. 232-242Conference paper, Published paper (Refereed)
Abstract [en]

Traffic situations leading up to accidents have been shown to be greatly affected by human errors. To reduce these errors, warning systems such as Driver Alert Control, Collision Warning and Lane Departure Warning have been introduced. However, there is still room for improvement, both regarding the timing of when a warning should be given as well as the time needed to detect a hazardous situation in advance. Two factors that affect when a warning should be given are the environment and the actions of the driver. This study proposes an artificial neural network-based approach consisting of a convolutional neural network and a recurrent neural network with long short-term memory to detect and predict different actions of a driver inside a vehicle. The network achieved an accuracy of 84% while predicting the actions of the driver in the next frame, and an accuracy of 58% 20 frames ahead with a sampling rate of approximately 30 frames per second. © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved

Place, publisher, year, edition, pages
Setúbal, 2019. p. 232-242
Keywords [en]
CNN, Optical Flow, RNN
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hh:diva-41105Scopus ID: 2-s2.0-85064628843ISBN: 978-9-897-58351-3 (print)OAI: oai:DiVA.org:hh-41105DiVA, id: diva2:1375177
Conference
8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019, Prague, Czech Republic; 19-21 February, 2019
Funder
Knowledge Foundation, 20140220Available from: 2019-12-04 Created: 2019-12-04 Last updated: 2019-12-19Bibliographically approved

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Englund, Cristofer

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf