Evaluation of the Train Drivers Mental Workload to Increase Well-being

M. M., Ridlo; Gustom, Aurik · 2024 · Crossref

DOI: 10.51505/ijebmr.2024.8305

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Summary

This study addresses the critical need to assess the mental workload of train drivers at PT Angkutan Barang (PT AB), an Indonesian railway freight company. The research was motivated by the surge in coal transportation targets, which necessitated tighter schedules and increased overtime for drivers. Long working hours and strict certification requirements contribute to fatigue and stress, elevating the risk of accidents and operational losses. The primary objective was to evaluate the mental workload of freight train drivers to inform strategies for improving well-being and safety. The researchers employed the Revised NASA Task Load Index (RNASA-TLX), a multidimensional subjective assessment tool, to measure mental workload. The study sampled 181 certified train drivers from the Tanjungenim Freight Train Drivers Unit in Palembang, Indonesia, conducting the assessment between November 2 and 10, 2023. The RNASA-TLX method evaluates six subscales: mental demand, visual demand, temporal demand, auditory demand, difficulty in driving, and difficulty in understanding information. Participants rated each subscale on a scale from 0 to 100 and performed pairwise comparisons to weight the importance of each dimension. The final Overall Weighted Workload (OWL) score was calculated and categorized as Low (<50), Moderate (50–80), or High (>80). The results indicated an average OWL score of 61.03, classifying the overall mental workload as "Moderate." Specifically, 48.07% of drivers reported moderate workload, 28.73% reported low workload, and 23.20% reported high workload. Visual demand was the most influential factor, contributing 31% to the total workload, driven by the need to monitor signals and track conditions. Temporal demand (21%) and auditory demand (20%) were the second and third most significant factors, respectively, largely due to schedule uncertainties and communication requirements. Mental demand contributed 18%, while difficulty in driving and understanding information were the least influential factors at 5% each. The study noted that freight drivers experienced intermittent rest during delays, contrasting with passenger drivers who face continuous high workload due to rigid schedules. The findings suggest that workload management strategies should be tailored to individual driver profiles. For the 52 drivers with low workload, the authors recommend introducing complex routes or new competencies to prevent boredom and maintain engagement. For the 42 drivers with high workload, primarily new employees or those with personal issues, the study recommends stress management training and regular monitoring. The research concludes that visual, temporal, auditory, and mental demands are the primary drivers of workload in freight operations. Future studies should expand to diverse geographic locations and train types to generalize these findings across the broader rail industry.

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Topics

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• workload measurement
• mental demand
• stress driving
• truck driver fatigue

Information type

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• Empirical Findings: self report data, physiological data
• Theoretical Contribution: theory or model