Obstacle Detection Algorithm of Fully Automatic Train Considering Reflection Intensity

Abstract:

Aiming at the problem of obstacle detection in front of rail transit train， this paper proposes an obstacle detection algorithm based on LiDAR and considering laser reflection intensity for fully automatic train. This algorithm uses the Euclidean clustering method to cluster the point clouds， and combines the adaptive threshold processing of reflection intensity， VGF， clustering radius differentiation and other methods to improve the speed and accuracy of obstacle detection. The experiments show that the algorithm has a good detection performance.