Comparison of Object Detection Models For Autonomous Vehicle Based on Accurracies: A Study Literature Review
Andhika Ferdiansyah, Ishvara Pranindhana Lakshamana, Adrian Maulana Rafli, Gusti Pangestu · Procedia Computer Science · 2024
Traffic accidents are a significant global problem, with human error being a major contributing factor. Autonomous vehicles have emerged as a promising solution to address this issue. Vehicle pedestrians understand the environment through sensor is crucial in this field because sensor data can be used by vehicle to drive safely such as navigate the route, avoid collision with other object such as pedestrian, car, building, animals, and many more. This paper proposed a comparison of 3D object detection models for autonomous vehicles using a study literature review technique. This technique consists of ten steps from including defining research question to produce the result. As a result, 9 papers were retrieved from 90 papers and then all object detection models are grouped into three parts to determine the best model based on dataset that being used such as KITTI, nuScenes, and Waymo Open Dataset.