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Assessment and monitoring of mental workload in subway train operations using physiological, subjective, and performance measures
Author(s) -
Jafari MohammadJavad,
Zaeri Farid,
Jafari Amir H.,
Payandeh Najafabadi Amir T.,
AlQaisi Saif,
HassanzadehRangi Narmin
Publication year - 2020
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20831
Subject(s) - workload , task (project management) , driving simulator , simulation , technician , computer science , engineering , transport engineering , reliability engineering , electrical engineering , systems engineering , operating system
Subway train operation is a complex, sociotechnical system that involves a variety of cognitively demanding tasks. The train operators are responsible for continuously monitoring the surrounding environment, maintaining awareness, processing information, and making decisions under risk. The resulting mental strain on operators can negatively affect their performance and the interaction of the human–machine system. The objective of this study was to evaluate if physiological, subjective, and performance measures could identify the level of mental workloads arising from routine and nonroutine operations in the subway system. A total of 11 subway train operators underwent different driving scenarios in a high‐fidelity simulator. The simulated tasks were divided into two categories: routine operations (preparing to drive and driving between stations without interruptions or emergencies) and nonroutine operation (responding to a tunnel fire, dealing with a high density of passengers, encountering a passenger/technician on the track, and responding to train failure). The mental workload was monitored and evaluated in these tasks using an electrocardiogram, subjective self‐rating scales, and driving performance. Both heart rate variability and performance measures (including reaction time and error rate) detected mental workload variations in the different operations. On the other hand, the subjective ratings (including NASA‐TLX) assessed the overall mental workload associated with a task, without explaining the mental demand variations within the task over time. Subway train drivers experienced different levels of mental workload during routine and nonroutine driving conditions. The findings of this study can be used to extract mental workload limits to optimize workload levels during train operations.