Kanchana, BPeiris, RPerera, DJayasinghe, DKasthurirathna, D2022-02-092022-02-092021-12-09B. Kanchana, R. Peiris, D. Perera, D. Jayasinghe and D. Kasthurirathna, "Computer Vision for Autonomous Driving," 2021 3rd International Conference on Advancements in Computing (ICAC), 2021, pp. 175-180, doi: 10.1109/ICAC54203.2021.9671099.978-1-6654-0862-2https://rda.sliit.lk/handle/123456789/1039Computer vision in self-driving vehicles can lead to research and development of futuristic vehicles that can mitigate the road accidents and assist in a safer driving environment. By using the self-driving technology, the riders can be roamed to their destinations without using human interaction. But in recent times self-driving vehicle technology is still at the early stage. Mostly in the rushed areas like cities it becomes challenging to deploy such autonomous systems because even a small amount of data can cause a critical accident situation. In Order to increase the autonomous driving conditions computer vision and deep learning-based approaches are tended to be used. Finding the obstacles on the road and analyzing the current traffic flow are mainly focused areas using computer vision-based approaches. As well as many researchers using deep learning-based approaches like convolutional neural networks to enhance the autonomous driving conditions. This research paper focused on the evaluation of computer vision used in self-driving vehicles.enComputer VisionAutonomous DrivingArticle10.1109/ICAC54203.2021.9671099