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Position estimation of the surrounding objects seen by the sensors mounted on an autonomous vehicle is a key module and it is typically carried out with the camera-lidar fusion owing to the high accuracy in depth estimation from lidar point cloud. In typical automotive LIDAR with 64 scanner points or less, at distances above 100 m, the object detection with LIDAR is not dependable as the number of LIDAR clusters will be sparse, while the high-resolution camera can offer better detection even at the distances above 100 m. ...In typical automotive LIDAR with 64 scanner points or less, at distances above 100 m, the object detection with LIDAR is not dependable as the number of LIDAR clusters will be sparse, while the high-resolution camera can offer better detection even at the distances above 100 m. ...Our proposed approach is a novel grid-based approach based on fusion of camera object detection and panoptic segmentation, which is then associated with lidar point cloud data and lidar object detections for accurate distance estimation. We take into consideration the occlusion level of the camera detected objects with the help of panoptic segmentation of the image frames and only the lidar points corresponding to the actual visible points of the object is used further for fusion and distance estimation.