Cognitive behavior modeling of manual rendezvous and docking based on the ACT-R cognitive architecture

  • Authors:

  • Chunhui Wang;Yu Tian;Yanfei Liu;Shanguang Chen;Zhiqiang Tian;Junsong Li

  • Affiliations:

  • National Key Laboratory of Human Factors Engineering, Astronaut Research and Training Center of China, Beijing, China;National Key Laboratory of Human Factors Engineering, Astronaut Research and Training Center of China, Beijing, China;Zhejiang Sci-Tech University, Hangzhou, China;National Key Laboratory of Human Factors Engineering, Astronaut Research and Training Center of China, Beijing, China;National Key Laboratory of Human Factors Engineering, Astronaut Research and Training Center of China, Beijing, China;Zhejiang Sci-Tech University, Hangzhou, China

  • Venue:
  • DHM'13 Proceedings of the 4th international conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics, and Risk Management: human body modeling and ergonomics - Volume Part II
  • Year:
  • 2013

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Abstract

Astronauts are exposed to numerous stressors during spaceflights, to reduce the faulty operations and improve human performance in manually controlled rendezvous and docking (manual RVD) of space vehicles, a method, which applies sophisticated cognitive architecture Adaptive control of thought---rational (ACT-R ) to model astronaut's cognitive behaviors and investigate the cognitive components influencing human performance, is proposed in this paper . To model the cognitive behaviors in completing manual RVD task, the declarative knowledge of the cognitive processes was obtained from experiments, the procedural knowledge was acquired by analyzing the relationship between cognitive processes and behaviors, and the model parameters were set up according to the boundary conditions and task characteristics. Manual RVD cognitive behavior model is then built up based on the declarative knowledge, the procedural knowledge and the model parameters. Comparisons of model running results and manual control results were performed to test the model's validation. ACT-R control panel tool was also used to analyze the process of model's running and manual control behaviors. Results of the comparisons indicate that the ACT-R model proposed in this paper is in accordance with human cognitive behaviors.