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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.
According to figures from the Society of Motor Manufacturers and Traders (SMMT), car production in the UK last year fell to its lowest level since 1956.
Over the last two years, the auto industry has experienced a great deal of turbulence. From the begin of the pandemic when dealerships have been pressured to shut down, to a huge bounce back in car purchases in the last year. But possibly the most surprising section was once the evolution and velocity at which auto retailers, dealerships and producers pivoted to digital options in order to serve their customers.
MCUs (microcontroller units) have a wide range of terminal applications, including home appliance controls, automotive electronics, education and entertainment, medical equipment, etc. Among them, automotive electronics and the Internet of Things are the main driving forces of the MCU industry.
When car consumers buy vehicles, in addition to considering the performance of the car, such as power, handling, and safety, they also consider the comfort of the vehicle. Noise, vibration, and harshness (NVH) has become an increasingly important factor for consumers in buying a car. A car with a high NVH rating performance will provide a more comfortable ride. In the design and development of new vehicles, car manufacturers need to evaluate and develop new models with higher performance.
The Asian region has always been the core area for global motorcycle and scooter sales, with India, China, and Indonesia being the top three markets. The Asian market has potential. The global demand for motorcycles and scooters is increasing.
The sheet metal parts, plastic parts, and lights of the car body account for the majority of car damage in car accidents. Hundreds of thousands of accidents involving damage to these parts occur every year. The repair and replacement of these parts are an important source of income for car repair shops and parts manufacturers.
A hidden important market in the automotive supply chain is the automotive after market (AM) which is used to satisfy after-sales repairs, inspections, maintenance, replacement, or modification services, and is an important part of the automotive supply chain.
Even though global automotive supply chain manufacturers have mostly invested in the development and production of electric vehicles, the old car repair market still remains. As automotive component customer demand has changed, global original car manufacturers (OEMs) are turning to the Taiwan After Market (AM) supply chain to place orders for OEM parts with companies that are originally AM manufacturers.
During the operation of a factory, the flow of materials determines the production efficiency of the factory. Recently, production lines have gradually added automation equipment, but the supply or handling of materials to and from the production line still relies on manual handling operations. This often results in unsmooth logistics and interrupted production flow. To avoid interruptions in supply, and reduce storage and production space, Automated Guided Vehicle (AGV) technology offers an unmanned management solution.
In response to energy-saving trends, the automotive industry has developed Hybrid Electric Vehicles and Electric Vehicles. Hybrid electric vehicles and electric vehicles belong to the two major trends of the current Green Car development. According to their design concepts and structural differences, in fact, HEV and EV can each be subdivided into different types.
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