The advanced railway signal system can prevent train-to-train collision automatically under normal working conditions, but the lack of perception of obstacles in front of the train has always been the pain point of the existing signal system. In this research, a design of Railway Intelligent Obstacle Detection System (RIODS) is proposed for the detection and warning of obstacles on the track, such as pedestrians, rocks, and vehicles. RIODS is a comprehensive and effective system solution. By deploying the subsystem of RIODS in the vehicle, trackside, and control center to meet the engineering application needs in different operation scenarios, the availability of the system is greatly improved, and the dependence on the performance of a single sensor is reduced. Based on multi-sensor fusion technology, deep learning algorithms, train positioning technology, and wireless communication, the system achieves information collection and analysis, and obstacle detection. Through field testing, the expected design function has been achieved. RIODS can be applied to different environments, and effectively improves the safety of train operation
|