Machine learning in Autonomous vehicles

Autonomous vehicles (AVs) have been developing at a very high rate in recent years. They are expected to reach a full level of autonomy (level 5) very soon. The main technology for creating autonomous vehicles is Artificial Intelligence (AI) and in particular its subcategories Machine Learning (ML) and Deep Learning (DL). In this article we will look at the application of Machine learning algorithms in autonomous vehicles.

For a better understanding of the ML algorithms used in AVs, first information about the device and the principle of operation of autonomous cars is presented. Then the methods of machine learning and their application in various tasks of self-driving cars are presented. Finally, we have presented some popular simulators for autonomous vehicles, where you can test and train algorithms and make different scenarios.

About the Autonomous vehicles Autonomous cars aim to eliminate the need for a driver. They will be able to take us from one location to another completely independently. To be able to accomplish this complex task, these cars have additional hardware and software systems that help them understand the environment, make decisions, and take action.

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