Publications

The Traffic Alert and Collision Avoidance System significantly reduces the risk of mid-air collision and is mandated worldwide on transport aircraft. Engineering the avoidance logic was costly and spanned decades. The development followed an iterative process where the logic was specified using pseudocode, evaluated in simulation, and revised based on performance against a set of metrics. Modifying the logic is difficult because the pseudocode contains many heuristic rules that interact in complex ways. With the introduction of next-generation air traffic control procedures and surveillance systems, the logic will require significant revision to prevent unnecessary alerts. Recent work has explored an approach for designing collision avoidance systems that will shorten the development cycle, improve maintainability, and enhance safety with fewer false alerts. The approach involves computationally deriving optimized logic from encounter models and performance metrics. This paper outlines the approach and discusses the anticipated impact on development, safety, and operation.

Unmanned Aircraft Systems require an ability to sense and avoid other air traffic to gain access to civil airspace and meet requirements in civil aviation regulations. One sense and avoid function is self separation, which requires that aircraft remain well clear. An approach is proposed in this paper to treat well clear as a separation standard, thus posing it as a relative state between aircraft where the risk of collision first reaches an unacceptable level. By this approach, an analytically-derived boundary for well clear can be derived that supports rigorous safety assessment. A preliminary boundary is proposed in both time and distance for the well clear separation standard, and recommendations for future work are made.

The Traffic Alert and Collision Avoidance System (TCAS) has been shown to significantly reduce the risk of mid-air collision and is currently mandated worldwide on all large transport aircraft. Engineering the collision avoidance logic was a very costly undertaking that spanned several decades. The development followed an iterative process where the logic was specified using pseudocode, evaluated on encounters in simulation, and revised based on performance against a set of metrics. Modifying the logic to get the desired behavior is difficult because the pseudocode contains many heuristic rules that interact with each other in complex ways. Over the years, the TCAS logic has become challenging to maintain. With the anticipated introduction of next-generation air traffic control procedures and surveillance systems, the logic will require significant revision to prevent unnecessary alerts. Recent work has explored a new approach for designing collision avoidance systems that has the potential to shorten the development cycle, improve maintainability, and enhance safety with fewer false alerts. The approach involves leveraging recent advances in computation to automatically derive optimized collision avoidance logic directly from encounter models and performance metrics. This paper outlines the general approach and discusses the anticipated impact on development, safety, and operation.

Unmanned Aircraft Systems require an ability to sense and avoid other air traffic to gain access to civil airspace and meet requirements in civil aviation regulations. One sense and avoid function is self separation, which requires that aircraft remain "well clear." An approach is proposed in this paper to treat well clear as a separation standard, thus posing it as a relative state between aircraft where the risk of collision first reaches an unacceptable level. By this approach, an analytically-derived boundary for well clear can be derived that supports rigorous safety assessment. A preliminary boundary is proposed in both time and distance for the well clear separation standard, and recommendations for future work are made.