Predicting Locomotive Crew Performance in Rail Operations with Human and Automation Assistance
Published in IEEE Transactions on Human-Machine Systems, 2019
As new technologies are introduced into rail operations, models are needed to represent the task load of operators to identify periods of extreme workload that could be mitigated through technological interventions. To this end, a computational model is described to quantitatively simulate freight rail operator workload to understand the impacts of inserting intelligent automation on different crew configurations. Read more
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