Train Frontal Obstacle Detection Method with Camera-LiDAR Fusion

Abstract

Recently, the importance of obstacle detection methods for railway has been increasing. In the field of automobiles, obstacle detection systems with sensors have been introduced on mass-produced vehicles. However, in railway, a practical detection system does not exist because railways require longer detection distances than do automobiles. Therefore, we have developed a train frontal obstacle detection method using a camera and LiDAR. We confirmed that our method detects a person 200 m away, which a camera alone cannot detect, with 45% accuracy at night. Earth retaining structures, such as bridge abutments and retaining walls, are con-structed at the boundary of bridges or embankments. There are a variety of earth retaining structure failure modes, therefore in order to be able to ensure rational aseismic reinforcement, it is necessary to develop a range of different aseismic reinforcement methods adapted to the relevant earth retaining structure’s failure mode. Moreover, there are many cases where construction work is severely restricted due to various limitations, such as land boundaries, available space, and time available for construction work. Therefore, the authors propose an aseismic reinforcement method, which can both improve seismic performance of earth retaining structures and be carried out efficiently. This paper outlines this research and describes some examples of the practical application of the newly developed reinforcement method.