Driving assistant using generative AI pre-generated messages in simulator-based driving assessment: A step towards low-cost simulator-based driving assessment

This paper presents a novel approach for a low-cost simulator-based driving assessment system incorporating a speech-based assistant, using pre-generated messages from Generative AI to achieve real-time interaction during the assessment. Simulator-based assessment is a crucial apparatus in the research toolkit for various fields. Traditional assessment approaches, like on-road evaluation, though reliable, can be risky, costly, and inaccessible. Simulator-based assessment using stationary driving simulators offers a safer evaluation and can be tailored to specific needs. However, these simulators are often only available to research-focused institutions due to their cost. To address this issue, our study proposes a system with the aforementioned properties aiming to enhance drivers' situational awareness, and foster positive emotional states, i.e., high valence and medium arousal, while assessing participants to prevent subpar performers from proceeding to the next stages of assessment and/or rehabilitation. In addition, this study introduces the speech-based assistant which provides timely guidance adaptable to the ever-changing context of the driving environment and vehicle state. The study's preliminary outcomes reveal encouraging progress, highlighting improved driving performance and positive emotional states when participants are engaged with the assistant during the assessment.

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Publication Details

Journal
Heliyon
Published
2024-08-01
DOI
https://doi.org/10.1016/j.heliyon.2024.e35941
Citations
3
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
1.93

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article

Driving assistant using generative AI pre-generated messages in simulator-based driving assessment: A step towards low-cost simulator-based driving assessment

Piyapat Dajpratham, Ruck Thawonmas, Gunt Chanmas, Chakarida Nukoolkit et al.
3 citations
Heliyon
Human-Automation Interaction and Safety
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article

Driving assistant using generative AI pre-generated messages in simulator-based driving assessment: A step towards low-cost simulator-based driving assessment

Piyapat Dajpratham, Ruck Thawonmas, Gunt Chanmas, Chakarida Nukoolkit, Pittawat Taveekitworachai, Xiao You
article en
3 citations

Abstract

This paper presents a novel approach for a low-cost simulator-based driving assessment system incorporating a speech-based assistant, using pre-generated messages from Generative AI to achieve real-time interaction during the assessment. Simulator-based assessment is a crucial apparatus in the research toolkit for various fields. Traditional assessment approaches, like on-road evaluation, though reliable, can be risky, costly, and inaccessible. Simulator-based assessment using stationary driving simulators offers a safer evaluation and can be tailored to specific needs. However, these simulators are often only available to research-focused institutions due to their cost. To address this issue, our study proposes a system with the aforementioned properties aiming to enhance drivers' situational awareness, and foster positive emotional states, i.e., high valence and medium arousal, while assessing participants to prevent subpar performers from proceeding to the next stages of assessment and/or rehabilitation. In addition, this study introduces the speech-based assistant which provides timely guidance adaptable to the ever-changing context of the driving environment and vehicle state. The study's preliminary outcomes reveal encouraging progress, highlighting improved driving performance and positive emotional states when participants are engaged with the assistant during the assessment.

HeliyonVol. 10(16)
Siriraj Hospital (TH), Ritsumeikan University (JP), Mahidol University (TH), King Mongkut's University of Technology Thonburi (TH)
Ritsumeikan University, Japan Society for the Promotion of Science
Openalex Percentile: Top 14%
Human-Automation Interaction and Safety
1.93
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