Predicting Locomotive Crew Performance in Rail Operations with Human and Automation Assistance
Published in IEEE Transactions on Human-Machine Systems, 2019
Recommended citation: Nneji, V. C., Cummings, M. L., & Stimpson, A. (2019). Predicting Locomotive Crew Performance in Rail Operations with Human and Automation Assistance. In IEEE Transactions on Human-Machine Systems. http://victorianneji.github.io/files/ieee_predictinglocomotivecrewperformance.pdf
A detailed task analysis served as the basis for identifying tasks performed during transit. Utilizing task characteristics and operating conditions as inputs, a discrete event simulation was designed to predict human operator workload. Results show that during heavy traffic conditions, the presence of automation can impact locomotive engineer performance more than the presence of a freight conductor in a short-haul freight rail setting. However, under typical conditions, assistance may not be as beneficial for human operator performance.