Driver-Activity Recognition in the Context of Conditionally Autonomous Driving

Christian Braunagel, Enkelejda Kasneci, Wolfgang Stolzmann, Wolfgang Rosenstiel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

98 Scopus citations

Abstract

This paper presents a novel approach to automated recognition of the driver's activity, which is a crucial factor for determining the take-over readiness in conditionally autonomous driving scenarios. Therefore, an architecture based on head-and eye-tracking data is introduced in this study and several features are analyzed. The proposed approach is evaluated on data recorded during a driving simulator study with 73 subjects performing different secondary tasks while driving in an autonomous setting. The proposed architecture shows promising results towards in-vehicle driver-activity recognition. Furthermore, a significant improvement in the classification performance is demonstrated due to the consideration of novel features derived especially for the autonomous driving context.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 18th International Conference on Intelligent Transportation Systems
Subtitle of host publicationSmart Mobility for Safety and Sustainability, ITSC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1652-1657
Number of pages6
ISBN (Electronic)9781467365956, 9781467365956, 9781467365956, 9781467365956
DOIs
StatePublished - 30 Oct 2015
Externally publishedYes
Event18th IEEE International Conference on Intelligent Transportation Systems, ITSC 2015 - Gran Canaria, Spain
Duration: 15 Sep 201518 Sep 2015

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2015-October

Conference

Conference18th IEEE International Conference on Intelligent Transportation Systems, ITSC 2015
Country/TerritorySpain
CityGran Canaria
Period15/09/1518/09/15

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