Kanchana, B.Peiris, R.Perera, D.Jayasinghe, D.Kasthurirathna, D.2022-02-072022-02-072021-12-0910.1109/ICAC54203.2021.9671099https://rda.sliit.lk/handle/123456789/986Computer 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.enAutonomous DrivingDeep LearningCNNComputer visionArticle