Aiming at the limitation of a single sensor in intelligent vehicle target detection, a target detection algorithm based on four-layer lidar and camera fusion was proposed. The position and number information of the target is obtained by lidar, and the result obtained after point cloud clustering is projected onto the image through the parameter matrix of joint calibrated by lidar and camera to obtain the bounding box of the target. The boundary box, category and confidence of the target are obtained by the collected images through the yolov3 network. Then, the decision level fusion method is used to fuse the detection results of lidar and camera, and the final detection result is obtained. The experimental results show that the detection rate of vehicle and pedestrian is 94.8% and 96.4% respectively. Compared with other methods, this algorithm can improve the detection rate and robustness.