Review of current approaches in the area of object detection for autonomous vehicles
Published in Institute of Electronics and Information Engineers (IEIE), 2024
Accurate object detection is crucial for autonomous vehicle operation. For the past decade, object detection for autonomous driving has been significantly improved by a great number of research papers and new methods. However, developing solutions that allow vehicles to function without human intervention is an ongoing area of research. A robust algorithm should be coupled with a comprehensive sensor setup to ensure the reliability of the autonomous vehicle system.
Taxonomy diagram of object detection approaches for autonomous vehicles, categorizing current research trends and methodologies
Development of such safe system is especially important for successfully dealing with adverse weather scenarios and safely guiding the vehicle through rain, snow, haze, and other natural phenomena. In this survey, we classify existing methods regarding object detection that are specifically used in the area of autonomous driving. Furthermore, we briefly describe ideas used in the current state-of-the-art methods. Finally, we present a taxonomy diagram created based on our observations of the current state of research in this area.
Recommended citation: Khairulov, Timur, Sanghyuck Lee, and Jaesung Lee. "Review of current approaches in the area of object detection for autonomous vehicles." 대한전자공학회 학술대회 (2024): 2836-2839.
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