Aviation safety: modeling and analyzing complex interactions between humans and automated systems

  • Authors:

  • Neha Rungta;Guillaume Brat;William J. Clancey;Charlotte Linde;Franco Raimondi;Chin Seah;Michael Shafto

  • Affiliations:

  • NASA Ames Research Center, Moffett Field, CA;NASA Ames Research Center, Moffett Field, CA;NASA Ames Research Center, Moffett Field, CA;NASA Ames Research Center, Moffett Field, CA;Middlesex University, London, UK;NASA Ames Research Center, Moffett Field, CA;NASA Ames Research Center, Moffett Field, CA

  • Venue:
  • Proceedings of the 3rd International Conference on Application and Theory of Automation in Command and Control Systems
  • Year:
  • 2013

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Abstract

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Überlingen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.