A Review of Object Detection Algorithms for Autonomous Vehicles: Trends and Developments

This review article compares many object detection techniques that are routinely employed in autonomous cars. The study’s goal is to give insights into current trends and advancements regarding the industry as well as to emphasize the virtues of each algorithm. The study evaluates the performance of many cutting-edge algorithms, including YOLO, SSD, RCNN, and Faster R-CNN, on several parameters like accuracy, speed, and robustness. The paper also covers the constraints and restrictions that these algorithms confront in real-world circumstances, as well as recent breakthroughs in this field. Overall, this review gives a thorough overview of the object recognition algorithms utilised in autonomous cars, as well as valuable insights for academics and researchers working in this field.