Evaluation on Comfortable Arousal in Autonomous Driving Using Physiological Indexes

Naoki Sakashita, Narumon Jadram, Peeraya Sripian, Tipporn Laohakangvalvit, Midori Sugaya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

At level 3 of autonomous driving, the driver has to take over driving when the system requires. In automatic driving, the arousal level tends to decrease. Drowsiness or less arousal is the leading cause of car accidents. For safety, it is necessary to increase the arousal level before driving. Moreover, due to the emotional state effect on the driving performance, it is important to consider comfort while improving the driver's arousal level. Previous studies proposed the comfortable arousal model based on physiological signals to evaluate arousal and comfort during autonomous driving. However, the accuracy evaluation using this model has not been sufficiently performed. This study aims to construct a more accurate and reliable comfortable arousal model. We explore various physiological indexes and calculate feature importance using the random forest method to achieve our goal. Then we compare and validate the evaluation accuracy with the subjective evaluation score against the previous comfortable model proposed. The result shows that the proposed method has more accurate than the methods of the previous method. However, the improved accuracy is still not very high, so we need to consider creating a comfortable arousal model.

Original languageEnglish
Title of host publicationArtificial Intelligence in HCI - 3rd International Conference, AI-HCI 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Proceedings
EditorsHelmut Degen, Stavroula Ntoa
PublisherSpringer Science and Business Media Deutschland GmbH
Pages305-316
Number of pages12
ISBN (Print)9783031056420
DOIs
Publication statusPublished - 2022
Event3rd International Conference on Artificial Intelligence in HCI, AI-HCI 2022 Held as Part of the 24th HCI International Conference, HCII 2022 - Virtual, Online
Duration: 2022 Jun 262022 Jul 1

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13336 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Artificial Intelligence in HCI, AI-HCI 2022 Held as Part of the 24th HCI International Conference, HCII 2022
CityVirtual, Online
Period22/6/2622/7/1

Keywords

  • Arousal
  • Autonomous driving
  • Comfort
  • Physiological signals

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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