Measuring Drivers’ Physiological Response to Different Vehicle Controllers in Highly Automated Driving (HAD): Opportunities for Establishing Real-Time Values of Driver Discomfort

Vishnu Radhakrishnan*, Natasha Merat, Tyron Louw, Michael G. Lenné, Richard Romano, Evangelos Paschalidis, Foroogh Hajiseyedjavadi, Chongfeng Wei, Erwin R. Boer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)
84 Downloads (Pure)

Abstract

This study investigated how driver discomfort was influenced by different types of automated vehicle (AV) controllers, compared to manual driving, and whether this response changed in different road environments, using heart-rate variability (HRV) and electrodermal activity (EDA). A total of 24 drivers were subjected to manual driving and four AV controllers: two modelled to depict "human-like" driving behaviour, one conventional lane-keeping assist controller, and a replay of their own manual drive. Each drive lasted for ~15 min and consisted of rural and urban environments, which differed in terms of average speed, road geometry and road-based furniture. Drivers showed higher skin conductance response (SCR) and lower HRV during manual driving, compared to the automated drives. There were no significant differences in discomfort between the AV controllers. SCRs and subjective discomfort ratings showed significantly higher discomfort in the faster rural environments, when compared to the urban environments. Our results suggest that SCR values are more sensitive than HRV-based measures to continuously evolving situations that induce discomfort. Further research may be warranted in investigating the value of this metric in assessing real-time driver discomfort levels, which may help improve acceptance of AV controllers.

Original languageEnglish
Article number390
JournalInformation (Switzerland)
Volume11
Issue number8
DOIs
Publication statusPublished - 08 Aug 2020
Externally publishedYes

Bibliographical note

Funding Information:
The work described in this paper was undertaken as part of the HumanDrive project, which is co-funded by the Centre for Connected and Automated Vehicles (CCAV) and Innovate UK, the UK's innovation agency. The lead author's Ph.D. is funded by EPSRC CASE studentship in partnership with Seeing Machines Ltd. This paper is published with kind permission from the HumanDrive consortium: Nissan, Hitachi, Horiba MIRA, Atkins Ltd., Aimsun Ltd., SBD Automotive, University of Leeds, Highways England, Cranfield University, and the Connected Places Catapult. The data collection for this paper was feasible due to the help and technical support provided by the University of Leeds Driving Simulator (UoLDS) team.

Publisher Copyright:
© 2020 by the authors.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Discomfort
  • Driver state
  • Heart-rate variability (HRV)
  • Highly automated driving (HAD)
  • Psychophysiology
  • Skin conductance response (SCR)

ASJC Scopus subject areas

  • Information Systems

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