research-article

How different mental workload levels affect the take-over control after automated driving

Authors:

A. GuillaumeAuthors Info & Claims

2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)

Pages 2040 - 2045

https://doi.org/10.1109/ITSC.2016.7795886

Published: 01 November 2016 Publication History

Abstract

Automated driving represents a new way of driving and, therefore, significant changes in driver behaviour are expected. In this study, we analysed the impact of different levels of mental workload associated with a non-driving task in response to a take-over request (TOR). Thirty participants drove in a driving simulator through three experimental conditions: once in manual driving and twice following an automated driving during which a non-driving task was performed. The impact of the mental workload was evaluated by manipulating the mental workload induced by the non-driving task (low versus high mental workload). The results showed a negative effect of automated driving on take-over performance regardless of the level of mental workload. These results point out that engagement in non-driving task leads to reduced situation awareness. Interpretations of results and research prospects are discussed.

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Cited By

Singh UAhirwal M(2023)Improved Classification of Mental Workload Using One Dimensional Convolutional Neural Network and SMOTE TechniqueProceedings of the 2023 7th International Conference on Graphics and Signal Processing10.1145/3606283.3606291(50-55)Online publication date: 23-Jun-2023
https://dl.acm.org/doi/10.1145/3606283.3606291
Meteier QCapallera MDe Salis EAngelini LCarrino SAbou Khaled OMugellini ESonderegger A(2023)Effect of Obstacle Type and Cognitive Task on Situation Awareness and Takeover Performance in Conditionally Automated DrivingProceedings of the 34th Conference on l'Interaction Humain-Machine10.1145/3583961.3583966(1-12)Online publication date: 3-Apr-2023
https://dl.acm.org/doi/10.1145/3583961.3583966
Zhu JMa YZhang YZhang YLv C(2023)Takeover quality prediction based on driver physiological state of different cognitive tasks in conditionally automated drivingAdvanced Engineering Informatics10.1016/j.aei.2023.10210057:COnline publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1016/j.aei.2023.102100
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Index Terms

How different mental workload levels affect the take-over control after automated driving
1. Human-centered computing
  1. Human computer interaction (HCI)

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2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)

2678 pages

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IEEE Press

Publication History

Published: 01 November 2016

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Cited By

Singh UAhirwal M(2023)Improved Classification of Mental Workload Using One Dimensional Convolutional Neural Network and SMOTE TechniqueProceedings of the 2023 7th International Conference on Graphics and Signal Processing10.1145/3606283.3606291(50-55)Online publication date: 23-Jun-2023
https://dl.acm.org/doi/10.1145/3606283.3606291
Meteier QCapallera MDe Salis EAngelini LCarrino SAbou Khaled OMugellini ESonderegger A(2023)Effect of Obstacle Type and Cognitive Task on Situation Awareness and Takeover Performance in Conditionally Automated DrivingProceedings of the 34th Conference on l'Interaction Humain-Machine10.1145/3583961.3583966(1-12)Online publication date: 3-Apr-2023
https://dl.acm.org/doi/10.1145/3583961.3583966
Zhu JMa YZhang YZhang YLv C(2023)Takeover quality prediction based on driver physiological state of different cognitive tasks in conditionally automated drivingAdvanced Engineering Informatics10.1016/j.aei.2023.10210057:COnline publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1016/j.aei.2023.102100
Yousfi EMalin SHalit LRoger SDogan E(2021)Driver experience and safety during manual intervention in a simulated automated vehicleProceedings of the 32nd European Conference on Cognitive Ergonomics10.1145/3452853.3452888(1-7)Online publication date: 26-Apr-2021
https://dl.acm.org/doi/10.1145/3452853.3452888
Dogan EYousfi EBellet TTijus CGuillaume A(2021)Manual takeover after highly automated drivingProceedings of the 32nd European Conference on Cognitive Ergonomics10.1145/3452853.3452880(1-6)Online publication date: 26-Apr-2021
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Pakdamanian ESheng SBaee SHeo SKraus SFeng LKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)DeepTake: Prediction of Driver Takeover Behavior using Multimodal DataProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445563(1-14)Online publication date: 6-May-2021
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Du NZhou FTilbury DRobert LYang X(2021)Designing Alert Systems in Takeover Transitions: The Effects of Display Information and Modality13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3409118.3475155(173-180)Online publication date: 9-Sep-2021
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de Salis ECapallera MMeteier QAngelini LAbou Khaled OMugellini EWidmer MCarrino S(2020)Designing an AI-Companion to Support the Driver in Highly Autonomous CarsHuman-Computer Interaction. Multimodal and Natural Interaction10.1007/978-3-030-49062-1_23(335-349)Online publication date: 19-Jul-2020
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