Analysis of Subjective Sleepiness Considering the Influences of Driving Workload, Duration between Stations, and Driving Duration in Railway Driving

Suzuki, Daisuke; Nakagawa, Chizuru; Akatsuka, Hajime; Akiu, Naohiro · 2025 · Crossref

DOI: 10.54941/ahfe1006536

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study investigates the factors influencing subjective sleepiness in railway drivers, motivated by Japan’s labor shortage and the industry’s shift toward automated train velocity control systems. As automation reduces manual driving tasks, there is a concern that lower workloads may increase monotony and induce sleepiness, compromising safety. The research specifically examines how simulated driving workload, the duration between stations, and total driving duration affect drivers' alertness levels. The experiment utilized a railway driving simulator with 30 non-professional male participants aged 20 to 60. The study employed a within-subjects design with six experimental conditions created by combining two workload levels (high, where participants controlled velocity; low, where the system controlled velocity) and three durations between stations (1.5, 3.0, and 5.5 minutes). Participants drove an 18-minute course featuring monotonous scenery and identical stations to induce sleepiness. Subjective sleepiness was measured every minute using the Japanese version of the Karolinska Sleepiness Scale (KSS), ranging from 1 (extremely alert) to 9 (extremely sleepy). Data were analyzed using multiple regression analysis, with mean subjective sleepiness scores as the dependent variable and driving workload, driving duration after stopping at a station, and total driving duration as independent variables. The results demonstrated that all three variables significantly influenced subjective sleepiness. Specifically, low driving workload increased subjective sleepiness by 1.52 points on the KSS compared to high workload, holding other factors constant. Additionally, sleepiness increased by 0.16 points for every additional minute of driving after stopping at a station, and by 0.06 points for every additional minute of total driving duration. These findings indicate that reduced task demand, longer intervals between operational events (station stops), and prolonged continuous driving all contribute to heightened sleepiness. The study concludes that automated systems reducing driver workload may inadvertently increase sleepiness risks due to monotony. The findings align with previous research in aviation and automotive sectors, which link low-demand tasks and highway driving to decreased vigilance. However, the authors note limitations, including the use of non-professional drivers, a simulated environment that may exaggerate monotony, and a short total driving duration of only 18 minutes. The results suggest that future railway automation strategies must account for arousal maintenance, particularly during low-workload phases and long intervals between stations, to ensure operational safety.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• drowsiness
• time on task
• truck driver fatigue
• sleep deprivation
• drowsiness detection algorithms
• vigilance

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: physiological data
• Theoretical Contribution: theory or model