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A Physiology-based Driver Readiness Estimation Model for Tuning ISO 26262 Controllability
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-6952-1053
2020 (English)In: IEEE Vehicular Technology Conference, Institute of Electrical and Electronics Engineers Inc. , 2020, article id 9129132Conference paper (Refereed)
Abstract [en]

When a hazardous situation approaches, the semi-autonomous vehicle opts for the driver as a fallback solution, unaware of the driver's readiness. During such a situation, autonomy misuse can occur when a driver becomes over-reliant on autonomous driving. For handling the hazardous event, controllability is paramount. We postulate that semi-autonomous vehicles decline their consideration in understanding the drivers' focus on the vehicle and the road. To examine the drivers' focus on the vehicle and the road we uphold that the vehicle must initiate exploring the drivers' situation awareness for the readiness, which could feasibly tune the ISO 26262 controllability. In this paper, we propose a physiology-based driver situation awareness for the readiness model through the driver's stress and drowsiness estimation. In addition, we boost the situation awareness for the readiness of the driver by enabling frequent interaction between the driver and the vehicle managing system. © 2020 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2020. article id 9129132
Keywords [en]
controllability, interaction, ISO 26262, physiological signals, situation awareness for the readiness, Hazards, Physiology, Remotely operated vehicles, Road vehicles, Roads and streets, Springs (components), Autonomous driving, Estimation models, Hazardous events, Readiness models, Semi-autonomous vehicles, Situation awareness, Autonomous vehicles
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-49493DOI: 10.1109/VTC2020-Spring48590.2020.9129132Scopus ID: 2-s2.0-85088309493ISBN: 9781728152073 (print)OAI: oai:DiVA.org:mdh-49493DiVA, id: diva2:1456737
Conference
91st IEEE Vehicular Technology Conference, VTC Spring 2020, 25 May 2020 through 28 May 2020
Note

Conference code: 161536; Conference Paper; CODEN: IVTCD

Available from: 2020-08-06 Created: 2020-08-06 Last updated: 2020-08-06Bibliographically approved

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Gallina, Barbara

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