Perelló-March, Jaume R., Burns, Christopher G., Birrell, Stewart A., Woodman, Roger and Elliott, Mark T. (2022) Physiological measures of risk perception in highly automated driving. IEEE Transactions on Intelligent Transportation Systems, 23 (5). pp. 4811-4822. doi:10.1109/TITS.2022.3146793

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Abstract

Highly automated driving will likely result in drivers being out-of-the-loop during specific scenarios and engaging in a wide range of non-driving related tasks. Manifesting in lower levels of risk perception to emerging events, and thus affect drivers’ availability to take-over manual control in safety-critical scenarios. In this empirical research, we measured drivers’ (N = 20) risk perception with cardiac and skin conductance indicators through a series of high-fidelity, simulated highly automated driving scenarios. By manipulating the presence of surrounding traffic and changing driving conditions as long-term risk modulators, and including a driving hazard event as a short-term risk modulator, we hypothesised that an increase in risk perception would induce greater physiological arousal. Our results demonstrate that heart rate variability features are superior at capturing arousal variations from these long-term, low to moderate risk scenarios. In contrast, skin conductance responses are more sensitive to rapidly evolving situations associated with moderate to high risk. Based on this research, future driver state monitoring systems should adopt multiple physiological measures to capture changes in the long and short term, modulation of risk perception. This will enable enhanced perception of driver readiness and improved availability to safely deal with take-over events when requested by an automated vehicle.

Item Type:	Journal Article
Alternative Title:
Subjects:	B Philosophy. Psychology. Religion > BF Psychology Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QP Physiology T Technology > TE Highway engineering. Roads and pavements T Technology > TL Motor vehicles. Aeronautics. Astronautics T Technology > TS Manufactures
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH):	Automobile drivers -- Psychology, Automated vehicles -- Psychological aspects, Human-computer interaction, Motor vehicles -- Automatic control , Intelligent transportation systems , Automated guided vehicle systems, Heart rate monitoring, Driver assistance systems, Risk perception
Journal or Publication Title:	IEEE Transactions on Intelligent Transportation Systems
Publisher:	IEEE
ISSN:	1524-9050
Official Date:	May 2022
Dates:	Date Event May 2022 Published 19 January 2022 Accepted
Volume:	23
Number:	5
Page Range:	pp. 4811-4822
DOI:	10.1109/TITS.2022.3146793
Status:	Peer Reviewed
Publication Status:	Published
Reuse Statement (publisher, data, author rights):	© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Access rights to Published version:	Restricted or Subscription Access
Description:	Special Issue on: Technologies for Risk Mitigation and Support of Incapacitated Drivers.

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