Object detection is a very prominent task in autonomous vehicle domain. Evolution in the area of deep learning provides an edge for object detection. In this chapter, we have worked on traffic object detection using YOLO V8 with model X version on KITTI dataset with Adam optimizer, batch size 8, epoch 150, and learning rate 0.001. We used 80% images for training, which is around 5000, and for the remaining 20%, around 1500 were used for validation. In this experimentation, we used NVIDIA RTX A5000 GPU for model training and achieved a mAP accuracy of 80%.