Author(s) :

DR AKHILESH SAINI.

Volume/Issue :

Abstract :

"Self-driving cars rely on advanced computer vision techniques to perceive and interpret their surroundings, enabling safe and autonomous navigation. 1 Computer vision, a subfield of artificial intelligence, allows these vehicles to detect and recognize objects, lane markings, traffic signs, pedestrians, and other dynamic elements of the road environment. 2 Using a combination of sensors, such as cameras, LiDAR, and radar, along with deep learning algorithms, self-driving cars analyze real-time data to make informed driving decisions. 3 This paper investigates the role of computer vision in autonomous vehicles, highlighting key technologies such as convolution neural networks (CNNs), object detection models (e.g., YOLO, Faster R-CNN, crucial for real-time identification and localization of objects), and semantic segmentation for comprehensive scene understanding. Critically, this paper also addresses the challenges of achieving real-time performance in complex scenarios, including low-light conditions, occlusions, and real-time processing constraints. As advancements in computer vision continue to evolve, self-driving technology is expected to improve in accuracy, reliability, and safety, bringing us closer to fully autonomous transportation systems."

No. of Downloads :

0