原文传递
A Conceptual Framework for Predicting Error in Complex Human-Machine Environments
| 题名： | A Conceptual Framework for Predicting Error in Complex Human-Machine Environments |
| 作者： | Freed, Michael; Remington, Roger |
| 关键词： | framework；environment；predict；concept；human；chin；mach；comp；mechanism；designer |
| 摘要： | We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely. |
| 报告类型： | 科技报告 |
相关文献
- USMC Vertical Takeoff and Landing Aircraft: Human-Machine Teaming for Controlling Unmanned Aerial Systems.
- ANALYSIS OF DRIVER SAFETY PERFORMANCE USING SAFETY STATE MODEL.
- International Harmonized Research Activities - report of Working Group on Intelligent Transport Systems (ITS).
- Defining Collaborative Control Interactions Using Systems Theory.
- A systems approach to public transportation.
- Exploring the Potential of a Machine Teammate.
检索历史
应用推荐
