Prediction improves drone traffic safety and efficiency in city skies
PB-STDG: A Prediction-Based Short-Term Decentralized Greedy Guidance Algorithm for a Drone Road System
RoboticsNetworking and Internet Architecture
Summary
As more drones fill city skies for deliveries and inspections, it's important they avoid crashing into each other. The authors created a new method that helps drones predict what nearby drones will do next, so they make smarter decisions and avoid being overly cautious. This prediction-based method was tested in simulations and it made drone traffic flow better without making it less safe. This means drones can navigate crowded skies more smoothly using this approach.
What this means in practice
- •For drone fleet operators: Manage drone routes in urban airspace to safely improve delivery and inspection efficiency using short-term prediction.
- •For emergency response teams: Coordinate multiple drones in emergency situations to avoid collisions while maintaining efficient flight paths in congested airspace.
Authors
Zhouyu Qu, Andreas Willig, Xiaobing Wu
Abstract
In recent years, Unmanned Aerial Vehicles (UAVs) or drones have been increasingly adopted in urban environments for applications such as parcel delivery, infrastructure inspection, emergency response, and drone light shows. A non-negligible issue is how to manage the increasing number of drones operated by different entities, to enable them to cooperatively avoid potential collisions and determine conflict-free short-term flight paths in urban airspace. This paper presents a Prediction-Based Short-Term Decentralized Greedy (PB-STDG) guidance algorithm for a structured Drone Road System (DRS). PB-STDG extends the original STDG algorithm by introducing a prediction mechanism that enables drones to anticipate the decisions of neighboring drones using additional information shared in beacon packets, aiming to address the over-conservative behavior observed in the STDG algorithm. Several simulation scenarios are conducted to evaluate and compare the proposed algorithm with STDG. The results show that PB-STDG improves traffic efficiency while maintaining a safety level comparable to that of STDG.