First large-scale autonomous drone traffic solution for future smart cities trialled
17 July 2024
Hungarian researchers have demonstrated how safe and efficient drone integration in future smart cities can work.
Image: ELTE
After creating the world’s first self-organising drone flock, researchers at Eötvös Loránd University (ELTE), Budapest, Hungary have now also demonstrated the first large-scale autonomous drone traffic solution. This fascinating new system is capable of far more than what could be executed with human pilots.
The staff of the Department of Biological Physics at Eötvös University has been working on group robotics and drone swarms since 2009. In 2014, they created the world's first autonomous quadcopter flock consisting of at least 10 units.
The research group has now reached a new milestone by publishing the dense autonomous traffic of one hundred drones in the journal Swarm Intelligence.
But what is the difference between flocking and autonomous drone traffic?
In the former, the goal of the units is to get perfectly synchronised through coordinated joint movement, such as in a bird flock. In a traffic situation, however, drones may have individual routes and goals, leading to potential conflicts.
This is particularly true when traffic does not occur on designated routes, but in open spaces, when pedestrians crossing a square in arbitrary directions or drones moving freely in the open sky.
The ELTE researchers solved this problem by combining a special, forward-thinking and real-time updating route planner with the interactions of traditional bio-inspired flocking models.
Thus, the autonomous robots can optimally avoid most traffic conflicts and safely manage the remaining ones by directly coordinating with their neighbours.
The effectiveness of the completely self-organising model, without central control, was first tested in simulations.
During this process, they were able to demonstrate the continuous high-speed random traffic of up to 5,000 drones in two dimensions with identical or different speeds and/or priorities.
Even layered three-dimensional cases were mapped to illustrate the efficient solution of dense drone traffic situations for future smart cities and decentralised air traffic control concepts.
The model was then programmed onto a hundred-member drone fleet owned by CollMot Robotics Ltd – a company founded at the Department of Biological Physics with the aim of drone swarm technology commercialisation. The self-organising drone traffic was demonstrated live with a hundred drones.
Based on this solution, a new phase of automated swarm drone operations can start across a wide range of applications, from group spraying to drone-based cargo transport and defence industry applications.