Automation Solution for Railway Crossing Safety Control: A Study on Automatic Barrier Control System

Abstract

This study focuses on the design and implementation of an automated control system aimed at optimizing safety and mitigating accident risks at unprotected railway-road intersections. The model was constructed based on a three-station distributed embedded control architecture, utilizing microcontrollers and a LoRa wireless communication network. Station 1 employed geophone sensors for seismic data acquisition to determine the presence of an approaching train. Station 2 served as the coordinator, transmitting early warning commands. Station 3, situated at the crossing, was responsible for barrier mechanism control and integrates computer vision for monitoring and detecting intrusion into the danger zone. The novel contribution is the synthesis of physical sensors and an intelligent vision system. This model incorporated a bidirectional safety mechanism, enabling Station 3 to reverse-alert the train (via Station 2) upon detecting unsafe obstacles. Experimental results demonstrated the system’s reliable operation, with a successful signal transmission/reception rate between stations reaching (1.2–1.8) km. Furthermore, the system exhibited low power consumption, quantified at approximately 81 Wh/24 hours. When connected with a 6750 mAh backup battery and photovoltaic cells, the stations were capable of continuous and autonomous operation without reliance on the power grid.