本文へ移動

論文 ·日本語 ·未確認

Effects of visual and auditory warnings during driving on mental workload

Akane Sato Takanori CHIHARA Jiro Sakamoto

刊行年
2024-01-01
収録
『Transactions of the JSME (in Japanese)』 90(940) pp. 24-00062
出版
Japan Society Mechanical Engineers
言語
英語
OpenAlex
W4403176172
DOI
10.1299/transjsme.24-00062
ISSN
2187-9761
URL
https://www.jstage.jst.go.jp/article/transjsme/90/940/90_24-00062/_pdf

要旨

The aim of this study was to investigate the effects of visual and auditory warnings on mental workload (MWL) during driving to induce drivers’ attention to safe driving. Twelve students (6 males and 6 females) who had Japanese driver’s licenses participated in this study. A total of four types of warnings, two each of visual and auditory, were presented during driving with a driving simulator. The N-back task was taken as a secondary task simultaneously with the driving task to control the MWL. Four eye movement parameters (i.e., standard deviation of eye rotation angle, standard deviation of gaze angle, head movement sharing ratio, and blink frequency) were used to estimate MWL. The Mahalanobis distance of four eye movement parameters between the four warning conditions and reference condition (i.e., without warning and N-back task) was calculated to estimate the MWL and investigate the effect of waring. The results showed that estimated MWL after warning tended to decrease when estimated MWL at warning presentation was high. Conversely, estimated MWL after warning tended to increase when estimated MWL at warning presentation was low. Therefore, it is suggested that warning presentation when MWL is high can be expected to be effective in inducing attention to safe driving.

主題

この書誌の出所

  • openalex— W4403176172(2026-08-14取得)

引用

Akane Sato・Takanori CHIHARA・Jiro Sakamoto(2024-01-01) Effects of visual and auditory warnings during driving on mental workload 『Transactions of the JSME (in Japanese)』 90(940) pp. 24-00062 Japan Society Mechanical Engineers

Sato2024EffectsVisualAuditory
書誌 67,320件 語別索引 17,251件 資源 113件 研究者 303名 JSON