Integrating trust in automation into driver state monitoring systems

Jaume Perello-March; Christopher Burns; Mark Elliott; Stewart Birrell

doi:10.1007/978-3-030-25629-6_53

Integrating trust in automation into driver state monitoring systems

Jaume Perello-March^*, Christopher Burns, Mark Elliott, Stewart Birrell

^*Corresponding author for this work

Sport, Exercise and Rehabilitation Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Inappropriate trust in highly automated vehicles (HAVs) has been identified as one of the causes in several accidents [1–3]. These accidents have evidenced the need to include a Driver State Monitoring System (DSMS) [4] into those HAVs which may require occasional manual driving. DSMS make use of several psychophysiological sensors to monitor the drivers’ state, and have already been included in current production vehicles to detect drowsiness, fatigue and distractions [5]. However, DSMS have never been used to monitor Trust in Automation (TiA) states within HAVs yet. Based on recent findings, this paper proposes a new methodology to integrate TiA state-classification into DSMSs for future vehicles.

Original language	English
Title of host publication	Human Interaction and Emerging Technologies - Proceedings of the 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019
Editors	Tareq Ahram, Redha Taiar, Serge Colson, Arnaud Choplin
Publisher	Springer Verlag
Pages	344-349
Number of pages	6
ISBN (Print)	9783030256289
DOIs	https://doi.org/10.1007/978-3-030-25629-6_53
Publication status	Published - 2020
Event	1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019 - Nice, France Duration: 22 Aug 2019 → 24 Aug 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1018
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019
Country/Territory	France
City	Nice
Period	22/08/19 → 24/08/19

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

Driver State Monitoring Systems
Highly automated vehicles
Machine learning
Trust in Automation

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-030-25629-6_53

Cite this

Perello-March, J., Burns, C., Elliott, M., & Birrell, S. (2020). Integrating trust in automation into driver state monitoring systems. In T. Ahram, R. Taiar, S. Colson, & A. Choplin (Eds.), Human Interaction and Emerging Technologies - Proceedings of the 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019 (pp. 344-349). (Advances in Intelligent Systems and Computing; Vol. 1018). Springer Verlag. https://doi.org/10.1007/978-3-030-25629-6_53

Perello-March, Jaume ; Burns, Christopher ; Elliott, Mark et al. / Integrating trust in automation into driver state monitoring systems. Human Interaction and Emerging Technologies - Proceedings of the 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019. editor / Tareq Ahram ; Redha Taiar ; Serge Colson ; Arnaud Choplin. Springer Verlag, 2020. pp. 344-349 (Advances in Intelligent Systems and Computing).

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abstract = "Inappropriate trust in highly automated vehicles (HAVs) has been identified as one of the causes in several accidents [1–3]. These accidents have evidenced the need to include a Driver State Monitoring System (DSMS) [4] into those HAVs which may require occasional manual driving. DSMS make use of several psychophysiological sensors to monitor the drivers{\textquoteright} state, and have already been included in current production vehicles to detect drowsiness, fatigue and distractions [5]. However, DSMS have never been used to monitor Trust in Automation (TiA) states within HAVs yet. Based on recent findings, this paper proposes a new methodology to integrate TiA state-classification into DSMSs for future vehicles.",

keywords = "Driver State Monitoring Systems, Highly automated vehicles, Machine learning, Trust in Automation",

author = "Jaume Perello-March and Christopher Burns and Mark Elliott and Stewart Birrell",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019 ; Conference date: 22-08-2019 Through 24-08-2019",

year = "2020",

doi = "10.1007/978-3-030-25629-6_53",

language = "English",

isbn = "9783030256289",

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publisher = "Springer Verlag",

pages = "344--349",

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Perello-March, J, Burns, C, Elliott, M & Birrell, S 2020, Integrating trust in automation into driver state monitoring systems. in T Ahram, R Taiar, S Colson & A Choplin (eds), Human Interaction and Emerging Technologies - Proceedings of the 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019. Advances in Intelligent Systems and Computing, vol. 1018, Springer Verlag, pp. 344-349, 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019, Nice, France, 22/08/19. https://doi.org/10.1007/978-3-030-25629-6_53

Integrating trust in automation into driver state monitoring systems. / Perello-March, Jaume; Burns, Christopher; Elliott, Mark et al.
Human Interaction and Emerging Technologies - Proceedings of the 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019. ed. / Tareq Ahram; Redha Taiar; Serge Colson; Arnaud Choplin. Springer Verlag, 2020. p. 344-349 (Advances in Intelligent Systems and Computing; Vol. 1018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Burns, Christopher

AU - Elliott, Mark

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AB - Inappropriate trust in highly automated vehicles (HAVs) has been identified as one of the causes in several accidents [1–3]. These accidents have evidenced the need to include a Driver State Monitoring System (DSMS) [4] into those HAVs which may require occasional manual driving. DSMS make use of several psychophysiological sensors to monitor the drivers’ state, and have already been included in current production vehicles to detect drowsiness, fatigue and distractions [5]. However, DSMS have never been used to monitor Trust in Automation (TiA) states within HAVs yet. Based on recent findings, this paper proposes a new methodology to integrate TiA state-classification into DSMSs for future vehicles.

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Perello-March J, Burns C, Elliott M, Birrell S. Integrating trust in automation into driver state monitoring systems. In Ahram T, Taiar R, Colson S, Choplin A, editors, Human Interaction and Emerging Technologies - Proceedings of the 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019. Springer Verlag. 2020. p. 344-349. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-25629-6_53

Integrating trust in automation into driver state monitoring systems

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this