Coordinated Dense Aerial Traffic with Self-Driving Drones

Abstract

In this paper we present a general, decentralized air traffic control solution using autonomous drones. We challenge some of the most difficult dense traffic situations, namely, crosswalk and package-delivery scenarios, where intelligent collective collision avoidance and motion planning is essential for a jam-free optimal traffic flow. We build up a force-based distributed multi-robot control model using a tunable selection of interaction terms: anisotropic repulsion, behaviour-driven velocity alignment, self-organized queueing and conflict-avoiding self-driving. We optimize the model with evolution in a realistic simulation framework and demonstrate its applicability with 30 autonomous drones in a coordinated outdoor flight within a densely packed virtual arena.