Case Study: Federal Aviation Administration improves airborne collision avoidance with Julia Computing

Federal Aviation Administration cuts ACAS-X computation time by years with Julia Computing

The Federal Aviation Administration (FAA) faced the monumental challenge of developing the next-generation Airborne Collision Avoidance System (ACAS-X) to improve safety and allow aircraft to fly closer together. The project required an exhaustive search over 650 billion decision points, and the FAA's previous process, which involved partners like Lincoln Labs, was extremely inefficient and costly due to a two-language problem using both MATLAB and C++.

Partnering with Julia Computing, the FAA implemented Julia as the solution. This eliminated the need for multiple languages and types of documentation, allowing for algorithm development, testing, and large-scale execution in a single, high-performance language. Julia Computing's solution reduced the computation time by several years, dramatically cut costs and time to market, reduced errors, and significantly increased air safety.

Federal Aviation Administration