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Abstract: Increasing safety, reducing traffic accidents, and saving lives are significant concerns in the automation of self-driving cars. To improve the safety precautions in self-driving automobiles, this project detects the lanes and vehicles in traffic. The fact that lane detection is essential in identifying which behaviours contribute to errors and accidents presents one of the challenges faced by self-driving car manufacturers that are now creating large numbers of autonomous vehicles for consumers. A more compelling case may be made for the development of intelligent vehicles by emphasising the improvement of safety conditions through full or partial automation of driving operations. Lane segmentation is a challenging topic because there are so many various sorts of road conditions that one could encounter when driving. We use the Yolov3 and CNN algorithms to segment the lane and detect the vehicles in the lane in order to ensure safe driving practises.