Workload Assessment of Human-Machine Interface: A Simulator Study with Psychophysiological Measures
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866914833904959488 |
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| author | Liu, Yuan-Cheng Figalova, Nikol Pichen, Juergen Hock, Philipp Baumann, Martin Bengler, Klaus |
| author_facet | Liu, Yuan-Cheng Figalova, Nikol Pichen, Juergen Hock, Philipp Baumann, Martin Bengler, Klaus |
| contents | Human-machine Interface (HMI) is critical for safety during automated driving, as it serves as the only media between the automated system and human users. To enable a transparent HMI, we first need to know how to evaluate it. However, most of the assessment methods used for HMI designs are subjective and thus not efficient. To bridge the gap, an objective and standardized HMI assessment method is needed, and the first step is to find an objective method for workload measurement for this context. In this study, two psychophysiological measures, electrocardiography (ECG) and electrodermal activity (EDA), were evaluated for their effectiveness in finding differences in mental workload among different HMI designs in a simulator study. Three HMI designs were developed and used. Results showed that both workload measures were able to identify significant differences in objective mental workload when interacting with in-vehicle HMIs. As a first step toward a standardized assessment method, the results could be used as a firm ground for future studies. Marie Skłodowska-Curie Actions; Innovative Training Network (ITN); SHAPE-IT; Grant number 860410; Publication date: [29 Sep 2023]; DOI: [10.54941/ahfe1004172] |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_09603 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Workload Assessment of Human-Machine Interface: A Simulator Study with Psychophysiological Measures Liu, Yuan-Cheng Figalova, Nikol Pichen, Juergen Hock, Philipp Baumann, Martin Bengler, Klaus Human-Computer Interaction Robotics Human-machine Interface (HMI) is critical for safety during automated driving, as it serves as the only media between the automated system and human users. To enable a transparent HMI, we first need to know how to evaluate it. However, most of the assessment methods used for HMI designs are subjective and thus not efficient. To bridge the gap, an objective and standardized HMI assessment method is needed, and the first step is to find an objective method for workload measurement for this context. In this study, two psychophysiological measures, electrocardiography (ECG) and electrodermal activity (EDA), were evaluated for their effectiveness in finding differences in mental workload among different HMI designs in a simulator study. Three HMI designs were developed and used. Results showed that both workload measures were able to identify significant differences in objective mental workload when interacting with in-vehicle HMIs. As a first step toward a standardized assessment method, the results could be used as a firm ground for future studies. Marie Skłodowska-Curie Actions; Innovative Training Network (ITN); SHAPE-IT; Grant number 860410; Publication date: [29 Sep 2023]; DOI: [10.54941/ahfe1004172] |
| title | Workload Assessment of Human-Machine Interface: A Simulator Study with Psychophysiological Measures |
| topic | Human-Computer Interaction Robotics |
| url | https://arxiv.org/abs/2406.09603 |