DHB Collaborative Research: Human Decision Making Dynamics and its Impact on Infrastructure Systems

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Modern socioeconomic systems depend critically on communications and power distribution network infrastructures. When these infrastructures are vulnerable, so is society as a whole. Both the social and the engineered infrastructural systems are complex in their own right and since the systems are interconnected (coupled), the combined system is even more complex. Much of the complexity stems from the humans. Infrastructural failures are often studied primarily as technical engineering matters, missing the human element. Understanding the dynamics and vulnerabilities of these coupled systems is becoming more important as the degree of coupling increases and as they are put under increasing stress. As this occurs, there is a concomitant increase in the flow of information, which can make the human element even more significant.To advance understanding of the dynamics in human/infrastructure systems: 1. We will investigate the dynamics of an integrated system comprised of power networks, communication networks, and a dynamic model of social interactions with these other infrastructure systems. This will build on previous work on the complex system dynamics of the individual power transmission networks, communication networks and human decision-making systems. 2. Simultaneously, we will develop a hierarchy of simple models to represent the key human reaction and decision-making dynamics identified in the observations of the real systems. These will be coupled to models of the complex engineering infrastructure. 3. Finally we will develop tools to analyze the real systems and to quantify and predict regimes of behavior, both to understand the real systems and to assess the validity of our models. Coupled system behavior is of basic scientific interest as a problem in complex systems dynamics. Complementing the scientific goal of improving understanding of coupled system behavior is the practical goal of developing predictive models of these systems, since their dynamics have major implications for society as a whole. The improvement in basic understanding will allow for improved risk analysis as well as the development of operational techniques to reduce the risks of major disruptions to the infrastructure.