Alaska Airlines

Assembly Line

AI: how it’s delivering sharper route planning

📅 Date:

✍️ Author: Karen kwon

🔖 Topics: Machine Learning

🏭 Vertical: Aerospace

🏢 Organizations: Alaska Airlines, Air Space Intelligence

Creating a route requires a dispatcher to answer a host of questions such as: “What is the wind today?”, “What is the best altitude for this flight?” and “Is there any military training?” Before the Flyways software, the 100 or so dispatchers at the NOC had to find answers to these questions by visiting multiple websites. These included FAA websites designed specifically for dispatchers, but that information was available only as strings of text that were hard to read.

Having decided to focus on the aviation industry, the team started spending an obscene amount of time at the NOC in an effort to understand how dispatching works and to create a user-friendly product — one that a real dispatcher could seamlessly operate when under pressure. Alaska Airlines’ employees would joke that the team was basically camping in their operations center with sleeping bags, Buckendorf says.

Flyways improves itself further by learning from a human dispatcher’s acceptance or rejection of its recommendations. When the dispatcher dismisses a suggestion, Flyways asks why: Was it because of the weather? Was the route putting an airplane uncomfortably close to somewhere it shouldn’t be? The idea is that Flyways learns from those decisions and evolves — though certain data points need to be filtered out so that the software does not simply emulate human dispatchers’ choices, stifling innovation.

Read more at Aerospace America