Advanced machine learning algorithms enable our autonomous system to define objects within the vehicle field of vision and calculate the confidence level of the detection. It can recognize various objects like cars, people, buses, trams, luggage, animals, and road signs. Segmenting the track in front of the vehicle allows precise risk analysis, especially in urban rail traffic. Train cameras continuously capture images to evaluate risks like people crossing the track or stray animals. This information helps adjust speed or apply brakes.

In high-risk areas like crossings, tunnels, and accident-prone spots, the autonomous system automatically sends early warnings. It alerts the train about potential dangers, even remotely stopping it when necessary, through the VS87 cab radio station. Integrating segmentation and object detection technology in railway infrastructure enhances safety and operational efficiency. It reduces repair costs and minimizes delays caused by accidents. With continuous track monitoring and real-time risk assessment, the system improves transportation reliability.