UC student combats drone traffic with fuzzy logic

Unmanned aerial vehicles (UAVs), commonly known as drones, have been at the forefront of research across the country, and it's no surprise why: Drones have the potential to revolutionize our everyday lives. From package delivery to traffic management to emergency response, drones are changing society as we know it.

But just as we saw with airplanes in the last century, as more vehicles enter air zones, society must adjust to the difficulties that come with them. Crowded and congested airspace can present real issues for drones, and without air traffic control centers, these drones need ideas that makes air travel safe.

This summer, University of Cincinnati student Zoe Lee (mechanical engineering '20) is spending her cooperative education (co-op) rotation in the UAV Master Lab, working on developing solutions for these crowded airspaces. Her focus is in fuzzy logic.

"Fuzzy logic is a way of thinking that's more human than computer," says Lee. "It's an alternative to binary logic. Instead of zeros and ones, you're essentially talking about subcategories within variables."

As with most things in life, fuzzy logic doesn't deal with everything in black and white, like a binary system would. Lee uses a blade of grass as an example.

"You may say a blade of grass is green, but that's not technically accurate," she says. "There's some green, yes, but there's also brown and yellow."

Fuzzy logic works in a similar way. Drones are not just far apart or close together; they operate within variables of speed, angles and trajectory.

Take a math problem that we're all familiar with: Train A, traveling at 60 miles per hour, leaves Chicago heading toward St. Louis, 300 miles away. At the same time, Train B, traveling at 70 miles per hour, leaves St. Louis heading toward Chicago. When do the two trains meet?

In this problem, you only have to address two variables to find the answer: distance and speed. With drones, it's much more complicated. Drones do not always go the same speed in a straight line. Add weather, battery life and a couple hundred other drones to the mix, and you can start to see the appeal of an alternative to binary logic.

In a sense, fuzzy logic allows UAVs to make their own decisions, based on human reasoning.