Özet:

When we look at the rates of traffic accidents in daily life, it is seen that driver errors are quite high. Newly launched vehicle models come to the market with control methods such as lane tracking, autonomous or semi-autonomous driving support, especially intelligent driving and driving assistant. In this study, it is aimed to develop a system for the correct recognition of traffic signs and warning the driver in order to assist the driver while autonomous vehicles are in traffic. In this study Recognition and classification of the signs and traffic lights on the roads were made by using the image processing methods of the road image videos taken from a camera mounted on a personal vehicle, and the appropriate classification technique was determined by using different artificial intelligence methods. In this context, a training data set was created to create an artificial neural network (ANN) model and to develop it for this structure. In order to create the training data set, video camera data were obtained from the traffic lights on the roads of Selçuklu and Meram districts in Konya and from the signs on the traffic signs with a road camera placed on the windshield of the personal vehicle. An ANN training was conducted using the data set obtained from the personal tool. In this experimental study, the accuracy rate of 90% was achieved. After the traffic signs and lights recognition system, a lane recognition and a road curve calculation system has been developed for an autonomous vehicle platform. Thus, the steering angle of the vehicle was calculated and it was controlled autonomously with a PID controller.

Anahtar Kelimeler: