1998 Fiscal Year Final Research Report Summary
Analysis of Human behavior in High-Tech Man-Machine Systems
| Project/Area Number |
08044127
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| Research Category |
Grant-in-Aid for international Scientific Research
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| Allocation Type | Single-year Grants |
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| Section | Joint Research |
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| Research Field |
社会システム工学
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| Research Institution | TOKYO INSTITUTE OF TECHNOLOGY |
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Principal Investigator |
ITOH Kenji Tokyo Institute of Technology, Professor, 大学院・社会理工学研究科, 教授 (80159871)
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| Co-Investigator(Kenkyū-buntansha) |
LIND Morter Technical University of Denmark, Professor, 自動制御システム研究所, 教授
NIELSEN Fiun ルソ国立研究所, システム分析部門, 研究員
LOVBORG Leif Riso National Laboratory, Group Leader, システム分析部門, グループ長
HANSEN John Paulin Multimedia Design School of Denmark, Hecd master, マルチメディア芸術学院, 学校長
UMEMURO Hiroyuki Tokyo Institute of Technology, Lecturer, 大学院・社会理工学研究科, 講師 (80251651)
NIELSEN Firr R. Riso National Laboratory, Scientist
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| Project Period (FY) |
1996 – 1998
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| Keywords | Cognitive Modeling / Cognitive Task Analysis / Cognitive Simulation / Ship Navigation / Risk Analysis / Mental Workload / Task Network / Man-Machine System |
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| Research Abstract |
The objectives of the present project is to develop a methodology on cognitive modeling which can be applied to risk analysis for the ship navigation tasks. The following outcomes were obtained by the present project for the last three years :
(1) A methodology for cognitive task analysis was proposed and applied to a basic manoeuvring task, socalled course tracking task. The proposed method was based on synchronized data from eye-movement recordings and verbal protocols of ship navigators as well as operation and ship motion logs. From results of the task analysis, cognitive processes of a captain or a navigator could be acquired.
(2) Based on the cognitive processes mentioned above, a navigator model was built for the course tracking task. The model describes a dynamic interaction between a navigator's cognitive processes and the states in manoeuvre. It represents attention allocation patterns, i.e., eye-gaze transitions, in a task network with a prototypical task probability and task
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time. The navigator model was validated its descriptive facility through some simulation runs using the identical scenarios to the experimental navigation sessions.
(3) In addition to simple course tracking tasks, experimental sessions of collision avoidance with other ships were analyzed using the proposed method mentioned in (1). Based on the results of analysis, we elicited the navigator's cognitive processes during the collision avoidance task. A prototypical cognitive model was also built for this task.
(4) A feature for estimating the navigator's mental workload in manoeuvring was equipped into the navigator model. This feature was based on the trace of the states in the navigator's short term memory.
(5) The navigator model built by the present project, which was implemented on a PC platform, has an interactive graphical interface as well as with specific analytical features for the risk analysis. Simulated track plots and mental states of the navigator can be displayed on a computer screen. Simulation conditions such as environmental factors and the navigator's individual factors, which are changeable through the interface. Less
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