The cognitive systems engineering laboratory has pursued the ideal environment for life and work to realize a human centered, safe, and secure social system by studies of principles and methodology of system design with consideration to human.
- Social System Modelling and Resilience Assessment
- Understanding and Application of Team Cognition
- Service Cognition and Cognitive System Analysis
- Cognitive Behavior Analysis of Tourists
- Modeling Vulnerable People in Disaster
- Support for Creating Incident Reports
- Design of Crisis Response Training
- Network Analysis and Simulation
- Human Modeling and Simulation
- Social Simulation in Disaster
- Risk Communication
- Interviewer Agent
- Air Traffic Control
Effective training is essential for continuous improvement of resilience in organization/society to large-scale natural disasters. However, there is little research on findings and support tools for designing efficient training programs. Our laboratory is aiming to develop a disaster context database that enables efficient development and sharing of training scenario and develop a support system for making training scenarios. Our laboratory is developing a support system and platform shared by different organization and communities, contributing to an evolutionary design of training scenarios and innovative design of regional training scenario and cooperation between multiple organizations.
Globally, air traffic demand is increasing at a rapid rate, and thus, due to the safe and effective operation of air traffic control (ATC) while dealing with the increasing demand, the workload of ATC systems and air traffic controllers will increase more than ever before. Air traffic controllers’ operation error can cause a severe accident of the whole of ATC systems. Our laboratory aims to create a cognitive model of air traffic controllers that can contribute to system design and crew resource training, based on experimental analyses of air traffic controllers’ situation awareness and cognitive processes behind decision making and task analyses of ATC. In addition, the safety assessment and system design for improving the present ATC system in terms of human factors are studied.
In many cases, there are many small and avoidable mistakes (incidents) behind a big accident in artificial systems. In order to prevent big accidents, many companies have tried to collect and analyze incident information to share the information and make preventive measures; in many cases, however, because they have limited time to analyze each incident, the incident reports are piled up without further analysis. To break through this situation, we are attempting to develop a system which can automatically and accurately analyze an outline and backgrounds of incidents using a conceptual structure of knowledge (ontology).
Understanding of cooperation and collaboration among people and developing reliable human models useful for evaluation and design of team and organization are big issues in engineering. To do that, it is necessary not only to analyze observable behaviors and data related to cooperation but also to analyze cognitive processes behind them. Our laboratory has developed a cognitive model behind cooperation based on mutual belief that considers conscious and unconscious images of others. Our laboratory verifies the cognitive model by experiments, cognitive simulation, and communication analyses and applies it to developing team and organizational performance measurements, bottleneck detection methods in cooperation, and interface assessment methods.
To minimize the damage caused by natural disasters or facility disasters, a smooth communication and cooperation between various related stakeholders such as governments, local governments, polices, fire companies, and residents are required. In order to enable these, it is indispensable to make an incremental improvement of disaster prevention systems in times of peace and to evaluate and familiarize them in emergency drills; it is impossible, however, to repeatedly conduct such large-scale evacuation training in real life. The present study aims to develop a simulator of human behavior in emergency situations making full use of distributed multi-agent simulation technologies in order to estimate and evaluate the behaviors of individuals and organizations in emergency situations, and design disaster prevention systems.
On social decision-making that requires much discussion about possible problems caused by scientific technologies, it is necessary to provide accurate risk information about the technologies to citizens; however, risk perception of citizens and the lack of knowledge for correct understanding of risk information sometimes obstruct such communication. The present study aims to clarify factors that inhibit the social acceptance of decision making on the basis of risk information, develop risk communication methods corresponding the needs and understanding of receivers, establish an ontology about the safety for an easy access to risk information, and develop an information retrieval technique implementing the ontology.
Because the complexity of socio-technical systems is caused by human factors, human models are often required to design them. Our laboratory has created human models in different fields using field survey, interview, case studies, data mining, and experiment and developed a computer simulation using the developed human models. For example, our laboratory has developed a ground air traffic control simulation of Haneda airport considering human models of air traffic controllers and pilots and then predicted the effects of building a new runway and terminals on performance and proposed improvements of the ground air traffic control.
The quality of services depends on different factors such as society, environment, providers, cognition of receivers, behavior characteristic, and their interactions. The present study aims to understand cognition of service providers and develop analysis methods, especially, in nursing care activities at the time of disaster. It also aims to construct an ontology of nursing care activities at the time of disaster based on the data from real experiences of nurses who took part of nursing care activity at the time of disaster in order to describe and organize the contexts and findings by a cognitive task analysis.
In the unstable social and political situations after the tragic September 11th terrorist attacks on the U.S., and in a possible great earthquake in urban areas, it is required to assess the service resilience in emergency situations and in the rehabilitation phase of service systems. In order to assess the resilience, it is necessary to consider not only infrastructures supporting services but also people’s activities in the services and interdependencies among them. The present study aims to develop reconstruction plan formulation methods for improving the service resilience that assess the service resilience in terms of service activities and infrastructures supporting them by modeling both the service activities and the infrastructures using multi agent systems and multilayer networks based on the case of a dialysis medical service.
In preparation for a possible great earthquake, medical institutions holding the key to lifesaving are required to establish the initial motion system of the organization and make quick and proper decisions under uncertainty in emergency situations. Disaster response training can practically enhance the disaster response capability. The present study aims to develop support tools for designing different disaster training programs by modelling of disaster contexts. It is expected to contribute to reducing the cost of preparing the training programs, bring diversity to the training programs, and support a person who is unfamiliar with professional knowledge and experience to make useful training programs.
Interviewing is often used to elicit cognitive processes in performing tasks, problem solving, and decision making by experts as a cognitive task analysis. The present study aims to develop an interviewer agent for a cognitive task analysis for effective information gathering about human behavior. It has implemented cognitive task analysis methods, findings of linguistics, and skills of interviewing proposed an overall assessment model for the interviewer agent.
A supply chain between different business enterprises has recently become a complex network because of the complication and globalization of markets. Although it is important to understand the actual supply chain network because of its structure-function relationship, the research on the supply chain is far behind that of other domain in the actual network analysis because it is difficult to obtain the actual data. This study focuses on a supply chain network on automobile parts, which has been discussed without any actual data in past studies, to investigate the past theories of the supply chain network and to simulate their changes in disaster and new entry using actual data and complex network analyses.
All systems requiring high safety demand effective Safety Management System (SMS). An incident report system is quite important for SMS because it contributes to data collection for SMS. Our laboratory has developed a support tool for making a high quality incident report for airline cabin crew, collaborating with a commercial airline company. It has also proposed a cause analysis framework based on human reliability evaluation and developed a prototype of its input interface.
Sustainable tourism growth requires development of a resilient social economic system that continues to develop related sectors based on the experiences of attracting tourists. Most studies on tourist behavior have developed a tourist behavior model from the perspective of general consumers, rather than from the perspective of services affected by the tourist experience. Our research aims to develop a decision making process model of tourist in consideration of framing effects and contrast effects and develop a verification method of tourist behavior models.
It is necessary to triage and assist vulnerable people in disaster, including patients with incurable diseases or internal troubles, elderly people, pregnant women, and persons with disabilities as well as casualties in a disaster. However, there is little research on a triage method of vulnerable people in disaster. Our laboratory develops a triage criteria and method for vulnerable people in disaster based on interviews on responses in the Great East Japan Earthquake and experts’ view. Our laboratory also develops a human model of vulnerable people in disaster and a support tool for triage education based on the human model.
Research Topics
Our main research topics are …
- Understanding of human cognition, behavior, interaction, and cooperation in realistic situations.
- Design methods of human centered socio-technical system.
- Supporting human thought, decision making, and learning, using advanced information technology.
- Service design considering human factors.
- Sociotechnical system required to realize a society with consideration of risks.
In the research, we have used and improved multiple methods such as field studies, case studies, cognitive experiments, multi-scale human modeling, and computer simulation.
- Professor: Kazuo FURUTA (Resilience Engineering Research Center, Department of Technology Management for Innovation)
- Associate Professor: Taro KANNO (Department of Systems Innovation)
Introduction of the members.
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Prof. Furuta's Office
Prof. Furuta's Office (Room 231)
Engineering Bld.3, 7-3-1, Hongo
Bunkyo-ku, Tokyo, 113-0033, JAPAN
TEL:+81-3-5841-6965(ext.26965)
Mail:
Web:link
Assc. Prof. Kanno's Office
Assc. Prof. Kanno's Office (Room 331)
Engineering Bld.8, 7-3-1, Hongo,
Bunkyo-ku, Tokyo, 113-0033, JAPAN
TEL:+81-3-5841-8355(ext.28355)
Mail:
Web:link
Laboratory
CSE Lab. (Room 513, Room 521)
Engineering Bld.8, 7-3-1, Hongo
Bunkyo-ku, Tokyo, 113-0033, JAPAN
TEL・FAX:+81-3-5841-8923(ext.28923)
The University of Tokyo
- The University of Tokyo
- School of Engineering
- Department of Systems Innovation
- Department of Technology Management for Innovation
- Resilience Engineering Research Center
- Faculty of Engineering, Department of Systems Innovation
- System Design and Management Course
Conferences
- The Institute of Electrical and Electronics Engineers, Inc.
- American Association for Artificial Intelligence
- European Safety and Reliability Association
- Human Factors and Ergonomics
- Human Interface Society
- The Japan Society of Disaster Nursing (JSDN)
- The Society of Instrument and Control Engineers
- The Japanese Society for Artificial Intelligence
In the face of a possible great earthquake, assessment and design of social system resilience such as a sustainable service in disaster and recovery management of urban functions are urgent issues. Social modelling requires not only a model of social infrastructures (hard infrastructure) but also a model of people in life (economic activity and daily life). Our laboratory tries to create a social system model that considers multiple interdependency of inter- and intra- systems based on multiple perspectives, including the perspectives of life, service and economic activity, and infrastructure. This study aims to develop a resilience evaluation method using simulation based on multi agents and multi-layer network model in order to make a detailed resilience assessment of Tokyo.