Neuronové sítě pro autonomní řízení auta

In this work, the principles of neural networks are introduced with a focus on autonomous vehicles. Based on this information, a proposal for the implementation of a system is created, which allows to drive a car without a driver. It builds on tools that allow easy creation and testing of autonomous vehicles. It is CARLA simulator and ranking.The proposal divides vehicle routes into three different situations. Each situation requires the use of different sensors, so a specific autonomous agent is created that is able to recognize the situation and switch between different neural network designs. Each such network is specific in its inputs and is taught in a specific situation.Programs are created that are able to easily collect a data set using the CARLA Leaderboard. Then, a way is introduced to how the collected data can be divided into categories so that each category can be used to learn its neural network. 

artificial intelligence, sensors, neural networks, gradient descent, backpropagation, convolutional neural networks, autonomous driving, simulators, CARLA, CARLA simulator, CARLA Leaderboard, datasets collection, neural networks design, neural networks training, implementation of autonomous agent