Autonomous Transport

Autonomous transport, based on artificial intelligence (AI) technologies, represents one of the most promising areas of modern industry development. From self-driving cars already being tested on public roads to autonomous drones for cargo delivery and self- управляed trains, AI is the driving force behind these innovations.

The key role in the operation of autonomous transport is played by environmental perception systems built on computer vision, lidars, and radars. AI processes vast amounts of data from these sensors in real time to identify other vehicles, pedestrians, cyclists, road signs, markings, and obstacles. The ability to accurately recognize and classify objects in a wide variety of weather conditions and traffic scenarios is critically important for safe navigation.

Decision-making in autonomous vehicles is also entirely dependent on AI. Machine learning and deep learning algorithms analyze the current road situation, predict the actions of other road users, and plan the optimal trajectory, speed, and maneuvers. These systems constantly learn from accumulated experience and simulation data, increasing their reliability and safety.

In addition to directly controlling movement, AI in autonomous transport is used to optimize routes, manage energy consumption, diagnose vehicle condition, and interact with passengers or cargo. The development of this field promises a significant increase in road safety by eliminating the human factor, reducing traffic congestion through movement optimization, and creating new logistics models.