The unnamed software isolates issues involving multiple drones and formulates alternative flight paths for selected pairs. A server then coordinates each of these solutions and gives a joint collision avoidance order.
To establish just how many drones could be contacted at once, researchers ran more than one million simulations where between two and ten unmanned aircraft encountered each other while in flight, risking collision. The paired strategy was compared to other strategies, including one where the drone only reacts to its closest threat. The solution with paired drones proved to be safer, and offered faster decision times and decreased alert rates.
The new software can predict and prevent drone collisions.
The UTM system is projected to take over many of the responsibilities and functions currently performed by air traffic control. Requiring air traffic control operators monitoring all the actions of drone operations would be unfeasible.
Stanford University calculates that the Federal Aviation Administration has approximately 15,000 human controllers who manage about 87,000 pilot-driven flights daily. When these numbers are compared to what it would take to monitor potentially hundreds of thousands of unmanned aircraft flights a day, it’s simply impractical.
Collisions between more than two aircraft are not very common, but flights in small and crowded urban areas create an opportunity for multiple aircrafts to have a collision. Researchers believe that automated conflict avoidance is the best solution to regulate traffic and prevent collisions.
The new software hopes to ensure safer flight for drones in crowded urban areas.
NASA estimates the final builds of the UTM will be completed by 2019. For more information on the UTM system, visit their website.