Campus Units

Industrial and Manufacturing Systems Engineering, Agricultural and Biosystems Engineering

Document Type

Conference Proceeding

Publication Version

Published Version

Publication Date


Journal or Book Title

Proceedings of the 2015 Conference on Autonomous and Robotic Construction of Infrastructure

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Last Page


Conference Title

Conference on Autonomous and Robotic Construction of Infrastructure

Conference Date

June 2-3, 2015


Ames, IA


Greater understanding of how highly skilled operators achieve high machine performance and productivity can inform the development of automation technology for construction machinery. Current human operator models, however, have limited fidelity and may not be useful for machinery automation. In addition, while physical modeling and simulation is widely employed in product development, current operator simulation models may be a limiting factor in assessing the performance envelope of virtual prototypes. A virtual operator modelling approach for construction machinery was developed. Challenges to the development of human operator models include determining what cues and triggers human operators use, how human operators make decisions, and how to account for the diversity of human operator responses. Operator interviews were conducted to understand and build a framework of tasks, strategies, cues, and triggers that operators commonly use while controlling a machine through a repeating work cycle. In particular, a set of operation data were collected during an excavator trenching operation and were analyzed to classify tasks and strategies. A rule base was derived from interview and data analyses. Common nomenclature was defined and is explained. Standard tasks were derived from operator interviews, which led to the development of task classification rules and algorithm. Task transitions were detected with fuzzy transition detection classifiers.


This is a paper from Proceedings of the 2015 Conference on Autonomous and Robotic Construction of Infrastructure, which can be found in full at:

Copyright Owner

Iowa State University



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