Autonomous driving is developing and evolving rapidly in the recent years. Both the scientific community and industry are making significant efforts to develop the necessary sophisticated technology and ultimately to achieve autonomous driving. Autonomous vehicle technology is expected to provide several advantages compared to traditional vehicles, as in the coming years, it will dramatically increase citizens’ safety, reduce transportation time and road congestion. In order to develop such a solution, it is necessary for the autonomous vehicles to have an excellent perception of the surrounding space, be able to adapt to it, and respond instantly to any changes of the surrounding environment. The vehicle must safely navigate on the road and properly respond to static and dynamic obstacles. In addition, it should evaluate decision scenarios and then, according to the cir cumstances, select the appropriate response. Thus, autonomous vehicles need to be equipped with appropriate state-of-the-art sensors and also with the appropriate control and decision-making system. This dissertation focuses on the design and development of such an autonomous driving system. The purpose of the system is to safely navigate on the road recog nized via optical means. The Computer Vision OpenCV library is extensively used throughout the project for preprocessing the received RGB image, so as to make it suitable for analysis. The perception system uses the programming interface of the CARLA simulator to integrate an RGB camera. For the identification of dynamic ob stacles, visual information is analyzed by the deep learning model YOLO (You Only Look Once) while using Optical Character Recognition (OCR) to export information from road traffic signals and a histogram analysis is performed for traffic light color recognition. In the global path construction system, a guided graph of the map is created and the algorithm A* is used to search for the optimal route. Finally, a Lane Keeping Assistance system and a PID controller are used for the navigation control system.