Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality

Kweku F. Bram-Larbi; Vassilis Charissis; Ramesh Lagoo; Shu Wang; Soheeb Khan; Samar Altarteer; David K. Harrison; Dimitris Drikakis

doi:10.1007/978-3-030-90966-6_17

Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality

Kweku F. Bram-Larbi, Vassilis Charissis, Ramesh Lagoo, Shu Wang, Soheeb Khan, Samar Altarteer, David K. Harrison, Dimitris Drikakis

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

1 Citation (Scopus)

299 Downloads (Pure)

Abstract

Multiple infotainment sources can significantly overload the driver’s cognitive load and increase the collision probabilities. Current solutions provided have at-tempted to alleviate this issue with the centralization of infotainment devices to single touchscreen devices in the dashboard area. Yet this solution still requires the driver to take the eyes from the road and concentrate on operating the secondary tasks unrelated to the driving process. The paper presents a prototype Augmented Reality Head-Up Display (AR HUD) system that superimposes a selected number of infotainment data on the vehicle’s windshield only when this is safe for the driver. The selection of infotainment data and projection timing is calculated by a prototype Artificial Intelligence (AI) Co-Driver that aims to reduce the driver’s cognitive load. The proposed system was evaluated by 50 users against a typical touchscreen dashboard system. This work presents and discusses the subjective feedback related to the cognitive load that the users perceived during the trials. The paper concludes with a future plan for improving both the AI and AR HUD elements to perform in an urban environment.

Original language	English
Title of host publication	HCI International 2021 - Late Breaking Papers: HCI Applications in Health, Transport, and Industry
Editors	Constantine Stephanidis, Vincent G. Duffy, Heidi Krömker, Fiona Fui-Hoon Nah, Keng Siau, Gavriel Salvendy, June Wei
Publisher	Springer Nature
Pages	235-245
Number of pages	11
ISBN (Electronic)	9783030909666
ISBN (Print)	9783030909659
DOIs	https://doi.org/10.1007/978-3-030-90966-6_17
Publication status	Published - 20 Nov 2021
Event	HCI International 2021: 23rd International Conference on Human-Computer Interaction - Online event, Washington DC, United States Duration: 24 Jul 2021 → 29 Jul 2021 http://2021.hci.international/index.html

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	13097
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	HCI International 2021: 23rd International Conference on Human-Computer Interaction
Abbreviated title	HCII2021
Country/Territory	United States
City	Washington DC
Period	24/07/21 → 29/07/21
Internet address	http://2021.hci.international/index.html

Keywords

cognitive load
augmented reality
virtual reality
artificial intelligence
driver distraction
simulation
head-up display
smart cities
user safety
user experience
human computer interaction
user evaluation

ASJC Scopus subject areas

Experimental and Cognitive Psychology
Artificial Intelligence
Human-Computer Interaction
Transportation
Automotive Engineering
Safety Research
Computer Graphics and Computer-Aided Design
Theoretical Computer Science
General Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Documents and Links

10.1007/978-3-030-90966-6_17

Bram-Larbi, K.F. et al (2021) Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality
This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-90966-6_17. © Springer Nature Switzerland
Author accepted manuscript, 505 KB

1 Citations
5 Conference contribution
4 Article
1 Chapter (peer-reviewed)
1 Review article

Design principles and user experience of automotive head-up display development
Charissis, V., Bram Larbi, K. F., Lagoo, R., Wang, S. & Khan, S., 2 Dec 2021, Proceedings of The 28th International Display Workshops. International Display Workshops, Vol. 28. p. 662-665 4 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Employing emerging technologies to develop and evaluate in-vehicle intelligent systems for driver support: infotainment AR HUD case study
Charissis, V., Falah, J., Lagoo, R., Alfalah, S. F. M., Khan, S., Wang, S., Altarteer, S., Bram Larbi, K. & Drikakis, D., Feb 2021, In: Applied Sciences. 11, 4, p. 1-28 28 p., 1397.
Research output: Contribution to journal › Article › peer-review

Open Access
File
39 Citations (Scopus)

226 Downloads (Pure)
Virtual reality for simulation and evaluation: technology acceptance models for automotive consumer electronics
Charissis, V., Bram-Larbi, K., Lagoo, R., Wang, S., Khan, M. S., Altarteer, S., Harrison, D. & Drikakis, D., 11 Nov 2021, HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence. HCII 2021. Stephanidis, C., Kurosu, M., Chen, J. Y. C., Fragomeni, G., Streitz, N., Konomi, S., Degen, H. & Ntoa, S. (eds.). Springer Nature, p. 219-234 16 p. (Lecture Notes in Computer Science; vol. 13095).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
File
2 Citations (Scopus)

348 Downloads (Pure)

Cite this

Bram-Larbi, K. F., Charissis, V., Lagoo, R., Wang, S., Khan, S., Altarteer, S., Harrison, D. K., & Drikakis, D. (2021). Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality. In C. Stephanidis, V. G. Duffy, H. Krömker, F. Fui-Hoon Nah, K. Siau, G. Salvendy, & J. Wei (Eds.), HCI International 2021 - Late Breaking Papers: HCI Applications in Health, Transport, and Industry (pp. 235-245). (Lecture Notes in Computer Science; Vol. 13097). Springer Nature. https://doi.org/10.1007/978-3-030-90966-6_17

Bram-Larbi, Kweku F. ; Charissis, Vassilis ; Lagoo, Ramesh et al. / Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality. HCI International 2021 - Late Breaking Papers: HCI Applications in Health, Transport, and Industry. editor / Constantine Stephanidis ; Vincent G. Duffy ; Heidi Krömker ; Fiona Fui-Hoon Nah ; Keng Siau ; Gavriel Salvendy ; June Wei. Springer Nature, 2021. pp. 235-245 (Lecture Notes in Computer Science).

@inproceedings{250c330b0ed44f8f95f11da050979022,

title = "Reducing driver{\textquoteright}s cognitive load with the use of artificial intelligence and augmented reality",

abstract = "Multiple infotainment sources can significantly overload the driver{\textquoteright}s cognitive load and increase the collision probabilities. Current solutions provided have at-tempted to alleviate this issue with the centralization of infotainment devices to single touchscreen devices in the dashboard area. Yet this solution still requires the driver to take the eyes from the road and concentrate on operating the secondary tasks unrelated to the driving process. The paper presents a prototype Augmented Reality Head-Up Display (AR HUD) system that superimposes a selected number of infotainment data on the vehicle{\textquoteright}s windshield only when this is safe for the driver. The selection of infotainment data and projection timing is calculated by a prototype Artificial Intelligence (AI) Co-Driver that aims to reduce the driver{\textquoteright}s cognitive load. The proposed system was evaluated by 50 users against a typical touchscreen dashboard system. This work presents and discusses the subjective feedback related to the cognitive load that the users perceived during the trials. The paper concludes with a future plan for improving both the AI and AR HUD elements to perform in an urban environment. ",

keywords = "cognitive load, augmented reality, virtual reality, artificial intelligence, driver distraction, simulation, head-up display, smart cities, user safety, user experience, human computer interaction, user evaluation",

author = "Bram-Larbi, {Kweku F.} and Vassilis Charissis and Ramesh Lagoo and Shu Wang and Soheeb Khan and Samar Altarteer and Harrison, {David K.} and Dimitris Drikakis",

note = "Acceptance in SharePoint AAM: no embargo; HCI International 2021: 23rd International Conference on Human-Computer Interaction, HCII2021 ; Conference date: 24-07-2021 Through 29-07-2021",

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language = "English",

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series = "Lecture Notes in Computer Science",

publisher = "Springer Nature",

pages = "235--245",

editor = "Constantine Stephanidis and Duffy, {Vincent G.} and Heidi Kr{\"o}mker and {Fui-Hoon Nah}, Fiona and Keng Siau and Gavriel Salvendy and June Wei",

booktitle = "HCI International 2021 - Late Breaking Papers: HCI Applications in Health, Transport, and Industry",

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Bram-Larbi, KF, Charissis, V, Lagoo, R, Wang, S, Khan, S, Altarteer, S, Harrison, DK & Drikakis, D 2021, Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality. in C Stephanidis, VG Duffy, H Krömker, F Fui-Hoon Nah, K Siau, G Salvendy & J Wei (eds), HCI International 2021 - Late Breaking Papers: HCI Applications in Health, Transport, and Industry. Lecture Notes in Computer Science, vol. 13097, Springer Nature, pp. 235-245, HCI International 2021: 23rd International Conference on Human-Computer Interaction, Washington DC, District of Columbia, United States, 24/07/21. https://doi.org/10.1007/978-3-030-90966-6_17

Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality. / Bram-Larbi, Kweku F.; Charissis, Vassilis; Lagoo, Ramesh et al.
HCI International 2021 - Late Breaking Papers: HCI Applications in Health, Transport, and Industry. ed. / Constantine Stephanidis; Vincent G. Duffy; Heidi Krömker; Fiona Fui-Hoon Nah; Keng Siau; Gavriel Salvendy; June Wei. Springer Nature, 2021. p. 235-245 (Lecture Notes in Computer Science; Vol. 13097).

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

TY - GEN

T1 - Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality

AU - Bram-Larbi, Kweku F.

AU - Charissis, Vassilis

AU - Lagoo, Ramesh

AU - Wang, Shu

AU - Khan, Soheeb

AU - Altarteer, Samar

AU - Harrison, David K.

AU - Drikakis, Dimitris

N1 - Acceptance in SharePoint AAM: no embargo

PY - 2021/11/20

Y1 - 2021/11/20

N2 - Multiple infotainment sources can significantly overload the driver’s cognitive load and increase the collision probabilities. Current solutions provided have at-tempted to alleviate this issue with the centralization of infotainment devices to single touchscreen devices in the dashboard area. Yet this solution still requires the driver to take the eyes from the road and concentrate on operating the secondary tasks unrelated to the driving process. The paper presents a prototype Augmented Reality Head-Up Display (AR HUD) system that superimposes a selected number of infotainment data on the vehicle’s windshield only when this is safe for the driver. The selection of infotainment data and projection timing is calculated by a prototype Artificial Intelligence (AI) Co-Driver that aims to reduce the driver’s cognitive load. The proposed system was evaluated by 50 users against a typical touchscreen dashboard system. This work presents and discusses the subjective feedback related to the cognitive load that the users perceived during the trials. The paper concludes with a future plan for improving both the AI and AR HUD elements to perform in an urban environment.

AB - Multiple infotainment sources can significantly overload the driver’s cognitive load and increase the collision probabilities. Current solutions provided have at-tempted to alleviate this issue with the centralization of infotainment devices to single touchscreen devices in the dashboard area. Yet this solution still requires the driver to take the eyes from the road and concentrate on operating the secondary tasks unrelated to the driving process. The paper presents a prototype Augmented Reality Head-Up Display (AR HUD) system that superimposes a selected number of infotainment data on the vehicle’s windshield only when this is safe for the driver. The selection of infotainment data and projection timing is calculated by a prototype Artificial Intelligence (AI) Co-Driver that aims to reduce the driver’s cognitive load. The proposed system was evaluated by 50 users against a typical touchscreen dashboard system. This work presents and discusses the subjective feedback related to the cognitive load that the users perceived during the trials. The paper concludes with a future plan for improving both the AI and AR HUD elements to perform in an urban environment.

KW - cognitive load

KW - augmented reality

KW - virtual reality

KW - artificial intelligence

KW - driver distraction

KW - simulation

KW - head-up display

KW - smart cities

KW - user safety

KW - user experience

KW - human computer interaction

KW - user evaluation

U2 - 10.1007/978-3-030-90966-6_17

DO - 10.1007/978-3-030-90966-6_17

M3 - Conference contribution

SN - 9783030909659

T3 - Lecture Notes in Computer Science

SP - 235

EP - 245

BT - HCI International 2021 - Late Breaking Papers: HCI Applications in Health, Transport, and Industry

A2 - Stephanidis, Constantine

A2 - Duffy, Vincent G.

A2 - Krömker, Heidi

A2 - Fui-Hoon Nah, Fiona

A2 - Siau, Keng

A2 - Salvendy, Gavriel

A2 - Wei, June

PB - Springer Nature

T2 - HCI International 2021: 23rd International Conference on Human-Computer Interaction

Y2 - 24 July 2021 through 29 July 2021

ER -

Bram-Larbi KF, Charissis V, Lagoo R, Wang S, Khan S, Altarteer S et al. Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality. In Stephanidis C, Duffy VG, Krömker H, Fui-Hoon Nah F, Siau K, Salvendy G, Wei J, editors, HCI International 2021 - Late Breaking Papers: HCI Applications in Health, Transport, and Industry. Springer Nature. 2021. p. 235-245. (Lecture Notes in Computer Science). doi: 10.1007/978-3-030-90966-6_17

Reducing driver’s cognitive load with the use of artificial intelligence and augmented reality

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

Documents and Links

Fingerprint

Research output

Design principles and user experience of automotive head-up display development

Employing emerging technologies to develop and evaluate in-vehicle intelligent systems for driver support: infotainment AR HUD case study

Virtual reality for simulation and evaluation: technology acceptance models for automotive consumer electronics

Cite this