Deep learning based autonomous vehicle systems

Developments in Machine Learning and in particular Deep Learning focuses on the complexity of applications in a wide range of areas and in various issues related to solving problems. Machine learning has a significant impact on the automotive industry and in the development of autonomous vehicles. The autonomous vehicle is a vehicle which can drive itself without human intervention. Over the last two decades, autonomous vehicles have been receiving considerable interest from both academia and industry, with potential applications in military, logistics and industrial production. The development of autonomous vehicles provides social benefits in many aspects, such as reducing the number of deaths and reducing the environmental impact of today's traffic. The autonomous vehicle can steer itself without any human interaction. Autonomous vehicles use various technologies such as GPS for navigation, sensors to avoid collisions, and cameras for object detection. Autonomous driving can be performed with Deep Learning and PID control. In this study, autonomous vehicle training was conducted in a simulation environment. At the same time, the autonomous movement of the vehicle is achieved with PID control and the performances of the autonomous movement of PID control and the autonomous movement of the vehicle trained with deep learning are compared.