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Utilizing machine learning and neural networks, artificial intelligence (AI) plays a crucial role in enabling the autonomous operation of self-driving cars. These vehicles leverage a combination of sensors, cameras, radar, and AI to navigate between destinations without the need for human intervention. For a car to be considered fully autonomous, it should demonstrate the capability to independently navigate predetermined routes without human input, even on roads that have not been specifically modified for autonomous vehicle use.

The wave of electric vehicles has allowed the commercialization of self-driving technology, and has more room for imagination. 91视频官网ever, the director of Berkeley's DeepDrive artificial intelligence and automatic system research center, believes that we must first accept the imperfection of technology.

Self-driving cars rely on technologies such as Advanced Driver Assistance Systems (ADAS) and the Internet of Vehicles.

Through machine learning and neural networks, AI technologies power self-driving car systems that can drive autonomously. A self-driving car is a vehicle that uses a combination of sensors, cameras, radar and artificial intelligence (AI) to travel between destinations without a human operator. To qualify as fully autonomous, a vehicle must be able to navigate without human intervention to a predetermined destination over roads that have not been adapted for its use.

Light Detection and Ranging is abbreviated as LiDAR or laser radar. It is an optical remote sensing technology that uses light to measure the distance of a target. LiDAR can measure the distance with high precision, recognize the appearance of objects, and build a 3D geographic information model around it. The advantages of distance measurement, high precision, and high recognition etc., are not affected by the brightness of the environment. It can sense the shape and distance of surrounding obstacles day and night. The scanning range is 100-200 meters, which can meet the needs of self-driving cars’ more precise sensing needs.

Under the leading policy of "Industry 4.0" in Germany, the manufacturing industry followed the concept of "smart manufacturing", and introduced the digital application of machinery into the factory. Based on the information technology services that belong to the energy economy category, it was imported from cloud software. Optimize the process. This kind of service platform is built on a modular structure that can be flexibly combined and uses AI to assist in providing strategic recommendations to achieve the energy-saving benefits of IoT machines.