ABSTRACT
Modeling human cognition, and understanding the manner in which humans use information, are becoming increasingly important as system designers develop automation to support the human operators. Tasks that were traditionally manual and physical in nature are being replaced with tasks that are cognitive in nature. Th is is exemplifi ed in the aviation community where automation is being adopted to increase effi ciency and safety. It is also becoming more important in surface transportation where increasing levels of automation are placing the human into a role of supervising the automobile’s performance and manually controlling the vehicle intermittently (e.g., adaptive cruise control, autonomous cruise control and vehicle guidance; Sheridan, 1992; Seppelt & Lee, 2007). Furthermore, nuclear power plant design, medical system design and operation, UAV and other telerobotic operations and manufacturing systems are all increasingly placing the human into similar supervisory roles (Sheridan & Ferrell, 1974; Miller, 2000; Zhai & Milgram, 1991, 1992; Sheridan, 1992; Boring et al., 2006). In these environments, it is important to model both the physical human as well as human cognition. Incorrectly modeling any of these performance factors, or ignoring one in favor of the other, may lead to incorrect predictions. It is important that the design community, including the digital human modeling community, include appropriately verifi ed and validated human physical geometric models and human cognitive models. Focusing on human physical geometric models alone, while rather salient and very important for specifi c anthropometric and biomechanic considerations, is insuffi cient for fully representing the human as they solely generate a physical geometric representation of a given model (either
32.1 Introduction ........................................................................ 32-1 32.2 Models of Human Performance ....................................... 32-2
32.3 Integrated Model Example: Man-Machine Integration Design and Analysis System (MIDAS)....... 32-6
32.4 Integrated Model Development Process ......................... 32-7 Model Creation Stage • Model Validation Stage
32.5 Interpreting Complex Integrated Models .................... 32-11 32.6 Conclusion ......................................................................... 32-13 Acknowledgments ....................................................................... 32-15 References ..................................................................................... 32-15Brian F. Gore
the human form, or other physical feature in an environment) but ignore important cognitive representations such as perception, attention, decision making, and memory. On the other hand, focusing solely on the cognitive models is in itself insuffi cient because human cognition interacts with an outside world in a closed-loop manner. Furthermore, human cognition is oft en not directly observable, and integrating physical models with cognitive models provides an opportunity to visualize the complex interaction among the various interacting components in a modeled human’s environment providing a system designer or an analyst the ability to see situations where the design as proposed may not be adequate for the operational conditions.
