A Multi-sensor Information Fusion Method for Autonomous Vehicle Perception System

Abstract

Within the context of the environmental perception of autonomous vehicles (AVs), this paper establishes a sensor model based on the experimental sensor fusion of lidar and monocular cameras. The sensor fusion algorithm can map three-dimensional space coordinate points to a two-dimensional plane based on both space synchronization and time synchronization. The YOLO target recognition and density clustering algorithms obtain the data fusion containing the obstacles’ visual information and depth information. Furthermore, the experimental results show the high accuracy of the proposed sensor data fusion algorithm.