Abstract
Rail traffic controllers perform a myriad of tasks from passive monitoring of the rail traffic systems to short-term intervention to respond to an issue. Measuring their mental demands, and the effects of workload on their performance is critically important. Therefore, using eye-tracking metrics and DLR-Workload Assessment Tool (DLR-WAT) we measured and analyzed the mental workload of nine novice and nine expert traffic controllers as they performed traffic control tasks in a rail traffic simulator while managing sparse versus dense train traffic and solving safety issues on the tracks. Eye tracking metrics identified workload in high difficulty tasks whereas DLR-WAT scores signified the differences between novices and experts. DLR-WAT was also useful in identifying different functions of the tasks. Integrating eye tracking metrics with subjective measures of workload can help in better understanding the dynamic interplay between task difficulty and differences in between individuals in the control center.
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