Research Article | Open Access | CC Attribution Non-commercial | Published online: 09 June 2025 Anti-Collision Drone Traffic Control System Using Swarm Technology

Sushilkumar S. Salve,* Sanskruti Y. Chaudhari, Ashwini R. Dandekar and Punam Gaikwad

Department of Electronics and Telecommunications Engineering, Sinhgad Institute of Technology, Lonavala, Affiliated by SPPU, Maharashtra, 410401, India

*Email: sushil.472@gmail.com

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

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. Future research plans involve carrying out tests in both make-believe and actual situations. These tests aim to assess how effectively the system performs across a range of working environments. This approach will help understand the system's strengths and weaknesses, ensuring it functions reliably under different conditions. The research achieved an accuracy exceeding 97%, indicating high reliability and performance.

Graphical Abstract

Novelty statement

New way to help avoid of drone crashing into each other’s.