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These vehicles integrate LiDAR System (Light Detection and Ranging), GPS navigation systems, machine vision, and machine learning algorithms to interpret sensory information to transport passengers and cargo autonomously. This complex system can identify travel paths, avoid obstacles and, with the help of machine vision, read relevant markers, like road signs. Also, it performs end-to-end navigation and actions like lane following and automated parking, along with real-time reactions to unpredictable road and traffic conditions. Self-driving vehicles operate in a vehicle-to-vehicle communication that takes place in a continuously improving collective traffic intelligence, provided with live information using cloud and edge computing. Also, by connecting to the manufacturer's cloud, any issues can be resolved remotely.
Self-driving shuttles and buses could become potential improvements for public transit because they move numerous people at once, consequently improving mobility in cities in a way that would be even more efficient than self-driving cars. Since there is no need for an operator on board, autonomous vehicles could operate 24 hours a day without stopping.