Conflict Resolution in the Sky: Mechanical Engineering Student Programs Drones to Bid for Best Route

As researchers send more unmanned aerial vehicles (UAVs), commonly known as drones, into the sky, traffic problems inevitably surface. Without the right planning, what once was an open airspace will quickly become a congested mess of drones that rivals rush hour on I-75.

UAV path-planning and sense-and-avoid technologies help combat these traffic jams, but these technologies are not end-all solutions. University of Cincinnati (UC) mechanical engineering student Drew Scott is spending his summer cooperative education (co-op) rotation in UC’s UAV Master Lab, focusing on one aspect of UAV simulation: monetary bidding systems.

“If two UAVs are going to collide at one spot at the same time, they will essentially bid for keeping the same path,” says Scott. “Whichever one bids the highest keeps the original route.”

Ideally, Scott says, drones will stick to assigned paths; however, the bidding systems are a necessary backup procedure when conflicts arise. Essentially, the drones operate on a cost-benefit scale. As paths intersect, two drones can communicate with each other by bidding to determine which drone will keep the original path.

Most of these drones will be used for package delivery, so they are inherently connected to a monetary value. Think of it like spending money on shipping when you purchase items online. You are willing to spend up to a certain amount on shipping costs, but after that, the product is not worth the additional money. Scott is writing an algorithm to determine that point and then programming to act appropriately based on those calculations.

Depending on the route and the cargo, each drone sets a maximum value on the chosen path. When it encounters another drone, it bids for that path. The second drone recalculates based on the new bid and counters. At a certain point, if the price climbs high enough, it becomes more profitable for one of the drones to take the recalculated alternate route.

At its basic level, the project is completed. Scott is now adding more variables to the code to make the system more realistic in application. For example, if the drone has less battery life, the system can push the bid a little higher.

Scott is an ACCEND student and plans to complete his master’s thesis under UC mechanical engineering professor Manish Kumar, PhD, his adviser on this project. Using what he’s learned on co-op and in the classroom, Scott hopes to lay the groundwork for a long career in controls and robotics after UC.