Abstract
AbstractSelf-driving cars or vehicles don’t require humans to take control to safely operate the vehicle. Also, popular as autonomous or driverless cars, they combine various sensors and software like radar, lidar, sonar, GPS, odometry, etc. to control, navigate, and drive the vehicle. This chapter presents the working model of the Self-driving Car: Lane detection and Collision prevention system (LDCP System) using machine learning and computer vision. In the LDCP System two processes working simultaneously based on object detection and recognition and human facial expression recognition to hold the responsibility of the car’s outer and inner environment to prevent any collision which occurs due to human errors such as lack of concentration or focus. The extraction of information about objects and face(s) is performed by capturing the live video feed through multiple cameras. The implemented algorithm is advanced enough to works in real-time which is for sure can prevent any collisions.KeywordsComputer visionMachine learningSelf-driving carDrowsinessYawningObject detectionLane detection
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