| description abstract | Human operators play a major role in maintaining the safety of complex systems. Although operator error is a major cause of hazardous events, operators also contribute to resilience by preventing, mitigating, and recovering from hazardous events. A key factor underlying this resilience is situation awareness—the ability of the operators to understand their environment and each other to achieve desired system functions. This remains true for fully and partially-autonomous systems, where operational responsibility is shared with designed technical functionality that also relies on (a form of) situation awareness to conduct operations. Distributed situation awareness (DSA) theory, which defines situation awareness as a system property, is best suited to represent situation awareness in systems that share situation awareness properties among (human and non-human) agents. This work proposes a framework to computationally simulate DSA to enable the study of operational resilience in complex engineered systems. Specifically, this framework enables the modeling of hazardous scenarios related to DSA in an integrated behavioral simulation. This approach advances existing DSA modeling approaches, which analyze situation awareness-related constructs alone, by enabling the analysis of the dynamic interactions between DSA-related constructs and other system elements (e.g., software glitches, human error, etc.) and their effects on overall system behavior. This framework is demonstrated using an aircraft taxiway example, where it is used to model taxiing conflicts arising due to lack of vision and poor communications from the air traffic controller. This demonstration shows the potential of using simulations to understand DSA-related hazards and thus inform the design of resilience. | |
