Exploring the effect of driver drowsiness on takeover performance during automated driving: An updated literature review DOI Creative Commons
Hengyan Pan, David Logan, Amanda N. Stephens

et al.

Accident Analysis & Prevention, Journal Year: 2025, Volume and Issue: 216, P. 108023 - 108023

Published: April 3, 2025

Vehicle automation technology has considerable potential for reducing road crashes associated with human error, including issues related to driver drowsiness. However, before full becomes available on public roads, it will be essential drivers take back control from automated driving systems when requested. This poses a challenge drivers, particularly as may further exacerbate paper aims update systematic review published in 2022 (Merlhiot & Bueno, Accident Analysis and Prevention, 170, 106536), discuss factors affecting drowsiness takeover performance particular focus those not identified previous review. Following the Preferred Reporting Items Systematic Reviews Meta-analyses guidelines, three databases: Web of Science, PubMed Scopus were searched studies between March 2021 October 2024. The following eligibility criteria applied study inclusion: 1) participants must have interacted simulated or real-world vehicle featured Level 2 above; 2) at least one measurement indicator drowsiness; 3) performance; 4) conducted within controlled experimental design. From an initial selection 182 articles databases, total twelve obtained after removing duplicates, title, abstracts texts checking. Additionally, 17 included, resulting 29 this study. Driver (e.g, increased Karolinska Sleepiness Scale levels, blink frequency) tended increase both duration levels. Engaging non-driving tasks (NDRTs) alleviates lower heart rate percentage eye closure), but reduces (e.g., longer braking reaction times, stronger longitudinal acceleration, shorter minimal time collision). Compared older younger more susceptible drowsiness, while had worse delayed steering time, higher collision rates). Sleep inertia circadian rhythms also influencing performance. monitoring task helps prevent excessive participation NDRTs improves reduced brake times maximum velocity, minimum Digital voice assistants scheduled manual help maintain alertness decreased duration) enhance resume steering). There several limitations methodologies existing studies, among which were: lack verification through experiments; insufficient diversity singularity scenarios; failure reveal mechanism by affects Factors such driving, NDRT engagement, age, sleep-related levels influence development subsequent literature highlights necessary directions future research: what underlying affect over how occurrence alleviate once occurs; assist drowsy regain safely quickly.

Language: Английский

Exploring the effect of driver drowsiness on takeover performance during automated driving: An updated literature review DOI Creative Commons
Hengyan Pan, David Logan, Amanda N. Stephens

et al.

Accident Analysis & Prevention, Journal Year: 2025, Volume and Issue: 216, P. 108023 - 108023

Published: April 3, 2025

Vehicle automation technology has considerable potential for reducing road crashes associated with human error, including issues related to driver drowsiness. However, before full becomes available on public roads, it will be essential drivers take back control from automated driving systems when requested. This poses a challenge drivers, particularly as may further exacerbate paper aims update systematic review published in 2022 (Merlhiot & Bueno, Accident Analysis and Prevention, 170, 106536), discuss factors affecting drowsiness takeover performance particular focus those not identified previous review. Following the Preferred Reporting Items Systematic Reviews Meta-analyses guidelines, three databases: Web of Science, PubMed Scopus were searched studies between March 2021 October 2024. The following eligibility criteria applied study inclusion: 1) participants must have interacted simulated or real-world vehicle featured Level 2 above; 2) at least one measurement indicator drowsiness; 3) performance; 4) conducted within controlled experimental design. From an initial selection 182 articles databases, total twelve obtained after removing duplicates, title, abstracts texts checking. Additionally, 17 included, resulting 29 this study. Driver (e.g, increased Karolinska Sleepiness Scale levels, blink frequency) tended increase both duration levels. Engaging non-driving tasks (NDRTs) alleviates lower heart rate percentage eye closure), but reduces (e.g., longer braking reaction times, stronger longitudinal acceleration, shorter minimal time collision). Compared older younger more susceptible drowsiness, while had worse delayed steering time, higher collision rates). Sleep inertia circadian rhythms also influencing performance. monitoring task helps prevent excessive participation NDRTs improves reduced brake times maximum velocity, minimum Digital voice assistants scheduled manual help maintain alertness decreased duration) enhance resume steering). There several limitations methodologies existing studies, among which were: lack verification through experiments; insufficient diversity singularity scenarios; failure reveal mechanism by affects Factors such driving, NDRT engagement, age, sleep-related levels influence development subsequent literature highlights necessary directions future research: what underlying affect over how occurrence alleviate once occurs; assist drowsy regain safely quickly.

Language: Английский

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