Deep Neural Network Compression for Aircraft Collision Avoidance Systems

Understand

One approach to designing decision making logic for an aircraft collision avoidance system frames the problem as a Markov decision process and optimizes the system using dynamic programming.

• The resulting collision avoidance strategy can be represented as a numeric table.
• This methodology has been used in the development of the Airborne Collision Avoidance System X (ACAS X) family of collision avoidance systems for manned and unmanned aircraft, but the high dimensionality of the state space leads to very large tables.
• To improve storage efficiency, a deep neural network is used to approximate the table.