AV-TLX for measuring (mental) workload while driving AVs: Born from NASA-TLX but developed for the era of automated vehicles

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Autori principali: Mosaferchi, Saeedeh, Mortezapour, Alireza, Liebherr, Magnus, Villecco, Francesco, Naddeo, Alessandro
Natura: Preprint
Pubblicazione: 2025
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author Mosaferchi, Saeedeh
Mortezapour, Alireza
Liebherr, Magnus
Villecco, Francesco
Naddeo, Alessandro
author_facet Mosaferchi, Saeedeh
Mortezapour, Alireza
Liebherr, Magnus
Villecco, Francesco
Naddeo, Alessandro
contents The introduction of automated vehicles has redefined the level of interaction between the driver and the vehicle, introducing new tasks and so impose different workloads. Existing tools such as NASA-TLX and DALI are still used to assess driving workload in automated vehicles, despite not accounting for new tasks. This study introduces AV-TLX, a specialized tool for measuring workload in Level 3 automated driving. The development process began with a narrative literature review to identify the primary factors influencing workload. This was followed by a series of qualitative sessions during which the dimensions and later the questions of the questionnaire were designed. The tools validity was first assessed using CVR and CVI indices, and its reliability and convergent validity were evaluated using a dynamic driving simulator with high fidelity. The final version of AV-TLX comprises 19 questions across 8 subscales, demonstrating excellent reliability (0.86) and validity (CVR > 0.78). An agreement scores between the results of AV-TLX and NASA-TLX in the simulation study was 0.6, which is considered acceptable for the consistency of two questionnaires. Furthermore, this questionnaire can be utilized in two ways. First by reporting the overall workload and/or divided into 8 primary subscales, or by categorizing the questions into two groups including takeover task workload and automated driving task workload. The final version of this questionnaire, as presented in the paper, is available for use in future studies focusing on Level 3 automated driving.
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id arxiv_https___arxiv_org_abs_2503_20596
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle AV-TLX for measuring (mental) workload while driving AVs: Born from NASA-TLX but developed for the era of automated vehicles
Mosaferchi, Saeedeh
Mortezapour, Alireza
Liebherr, Magnus
Villecco, Francesco
Naddeo, Alessandro
Human-Computer Interaction
The introduction of automated vehicles has redefined the level of interaction between the driver and the vehicle, introducing new tasks and so impose different workloads. Existing tools such as NASA-TLX and DALI are still used to assess driving workload in automated vehicles, despite not accounting for new tasks. This study introduces AV-TLX, a specialized tool for measuring workload in Level 3 automated driving. The development process began with a narrative literature review to identify the primary factors influencing workload. This was followed by a series of qualitative sessions during which the dimensions and later the questions of the questionnaire were designed. The tools validity was first assessed using CVR and CVI indices, and its reliability and convergent validity were evaluated using a dynamic driving simulator with high fidelity. The final version of AV-TLX comprises 19 questions across 8 subscales, demonstrating excellent reliability (0.86) and validity (CVR > 0.78). An agreement scores between the results of AV-TLX and NASA-TLX in the simulation study was 0.6, which is considered acceptable for the consistency of two questionnaires. Furthermore, this questionnaire can be utilized in two ways. First by reporting the overall workload and/or divided into 8 primary subscales, or by categorizing the questions into two groups including takeover task workload and automated driving task workload. The final version of this questionnaire, as presented in the paper, is available for use in future studies focusing on Level 3 automated driving.
title AV-TLX for measuring (mental) workload while driving AVs: Born from NASA-TLX but developed for the era of automated vehicles
topic Human-Computer Interaction
url https://arxiv.org/abs/2503.20596