Journal of Information and Communications Technology: Algorithms, Systems And Applications
A single-blind peer-reviewed, quarterly, open-access journal committed to advancing cutting-edge research across the full spectrum of ICT.
Anti-Collision Drone Traffic Control System Using Swarm Technology
J. Inf. Commun. Technol. Algorithms Syst. Appl., 2025, 1(1), 25303 https://doi.org/10.64189/ict.25303
Received: 02 May 2025 | Revised: 27 May 2025 | Accepted: 05 June 2025
Cite article
S. S. Salve, S. Y. Chaudhari, A. R. Dandekar, P. Gaikwad, Anti-collision drone traffic control system using swarm technology, Journal of Information and Communications Technology: Algorithms, Systems and Applications, 2025, 1(1), 25303, doi: . https://doi.org/10.64189/ict.25303
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(c) The Author(s) 2025.
Open Access
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Abstract
This article introduced new way to help avoid of drone crashing into each other's. The suggested system facilitates communication between drones, enabling them to exchange their current location and planned flight path. By working together, drones can anticipate and avoid potential collisions. The technique utilizes the principle of repulsion forces, enabling drones to autonomously alter their trajectories in response to nearby obstacles, such as other drones. The collision avoidance behavior adapts dynamically to the distance between vehicles, guaranteeing both safety and coordination. Created with simplicity and computational efficiency in mind, the system is well-suited for lightweight, cost-effective drones. To assess performance, two simulations were carried out: one with two groups of nine drones approaching each other, and another with 25 drones executing formation changes. The findings revealed that the system was able to prevent collisions, maintain appropriate spacing between vehicles, and adjust to different environmental conditions. This approach improves swarm coordination and shows potential for practical applications like managing air traffic in cities, delivering packages autonomously, responding to emergencies, and monitoring defense operations. The research achieved an accuracy exceeding 97%, indicating high reliability and performance.
Novelty Statement
New way to help avoid of drone crashing into each other's.