OBJECT DETECTION TECHNIQUES IN AUTONOMOUS VEHICLES, A SURVEY

Abstract

This study deeply examines the object detection techniques in autonomous vehicles. As autonomous vehicle's core is object detection, which enables self-driving cars to precisely sense their environment and react appropriately to objects they detect. But in practical settings, developing a reliable and extremely precise system still presents significant difficulties because of restrictions such fluctuating ambient conditions, sensor limitations, and computational resource constraints. Degradation of the sensor in bad weather or low light, for instance, can significantly reduce the accuracy of detection. In this manuscript we have identified the limitations in existing work followed by recommendations. In addition, a detailed literature review is included regarding object detection techniques in autonomous vehicles following with an analysis of the current work.

Keywords : Object detection; Autonomous vehicles; Yolo, Predictive maintenance, deep learning.