Journal of ISMAC
IRO Journals
Volume 7 — Issue 1 — March 2025

Arduino UNO based Autonomous Train System

https://doi.org/10.36548/jismac.2025.1.006
Pages: 79-93
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Kavithamani A.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
Aakash S.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
Krithick Roshan V.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
Shobana S.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
Vigneshwari V.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
Nithish Ram K S
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
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How to Cite

A., Kavithamani, Aakash S., Krithick Roshan V., Shobana S., Vigneshwari V., and Nithish Ram K S. 2025. “Arduino UNO Based Autonomous Train System”. Journal of ISMAC 7 (1): 79-93. https://doi.org/10.36548/jismac.2025.1.006.
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Keywords

— Driverless Train
— Communication Protocols
— Obstacle Detection
— Train Control
— Satellite Communication
— GPS
— Sensors
— Transceiver Communication
Published: 24-04-2025

Abstract

This study presents the design and implementation of an “Autonomous Train System” intended to improve safety, efficiency, and reliability in modern railway operations. The proposed system integrates advanced technologies, including GPS modules, infrared and ultrasonic sensors, RF communication, and microcontroller-based control units to facilitate real-time obstacle detection, automatic braking, and inter-train communication. By continuously monitoring track conditions and nearby trains, the system can dynamically determine risk and execute timely responses, significantly reducing the chance of human error. The inclusion of GPS-based distance measurement using the Haversine formula ensures accurate positioning and collision avoidance. Additionally, the use of wireless communication allows trains to exchange location and status data, enhancing coordination and safety. The system’s compact design, cost-efficiency, and scalability support its adoption in both urban and intercity networks. This autonomous approach not only improves operational dependability but also sets the foundation for intelligent transportation systems in the future of railway infrastructure.

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