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United States Department of Transportation United States Department of Transportation

The Expert Locomotive Engineer's Mental Model

Document Series
Research Results
Author
Federal Railroad Administration
Report Number
RR 21-15
Office
RPD-34
Subject Train Control
Keywords
Train control, mental models, expert engineer performance, train handling, automation, human factors

Researchers from General Electric (GE) Research and the Massachusetts Institute of Technology (MIT) Human Systems Lab are studying ways to improve the man-machine interface for the locomotive driving task and train handling with the assistance of advanced automation. This man-machine collaborative approach to the design of automated control systems promises improved locomotive control for both experienced engineers and those new to the job. The system design approach is to build-in and take advantage of expert drivers’ knowledge and skills and the machine’s ability to execute instructions more precisely than the engineer to provide better overall safety and efficiency. From October 2019 to July 2020, the team conducted the experiments at the Federal Railroad Administration’s (FRA) Cab Technology Integration Lab (CTIL). These experiments put expert and novice drivers in the simulated cab, allowing each to drive while blocking the view out the window from the driver (i.e., forcing interaction with the non-driving participant) and recording their interactions for analysis.


Last updated: Friday, August 20, 2021