STI Paper No. 10.2514/6.2020-2863

Development of Probability Fields for Collision Avoidance

Standard Guidance, Navigation, and Control (GN&C) systems take state data from a navigation system and create a trajectory that minimizes some a-priori determined cost function. Previous work has been done to show the effectiveness of using risk as the sole objective function. However, this previous work used Poisson distributions and historical estimates to achieve this goal.

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In this paper we present:

  • The underlying statistics of a situation-risk assessment (SRA) method contained within the intelligent situation assessment and collision avoidance (iSC) platform
  • The SRA method uses data clustering, and pattern recognition to create a historical-based estimate of guidance probabilities
  • These are then used in data driven, dynamic models to create future probability fields of the situation
  • The paper includes an example creating a command decision probability function for a congested urban airspace environment

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