A Decision Theoretic Approach to Future Aircraft Collision Avoidance
11/7/2017, 4-5pm, CS 150/151
Abstract: 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 introduction of next-generation air traffic control procedures and surveillance systems, the logic will require significant revision to prevent unnecessary alerts. Recent work on the next-generation airborne collision avoidance system, ACAS X, has explored a new approach for designing collision avoidance systems that has shortened the development cycle, improved maintainability, and enhanced 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 talk outlines the general approach and discusses the impact on development, safety, and operation.
Bio: Robert J. Moss earned a bachelor's degree in computer science from the Wentworth Institute of Technology where his research focused on the modeling of galactic rotation curves. He is an assistant staff member at MIT Lincoln Laboratory where his research focuses on the development, optimization, and analysis of the next generation airborne collision avoidance system for manned and unmanned aircraft and the specification development of prototype systems using the scientific programming language Julia.