Ideal, NIO, and Xpeng are working together to make end-to-end autonomous driving a new competitive point

Recent industry insider news revealed that China’s emerging automakers are following Tesla’s lead and actively developing end-to-end autonomous driving structure models to promote the development of autonomous driving technology. This move shows the Chinese automobile industry’s emphasis on and determination to catch up with autonomous driving technology. China's emerging automakers hope to accelerate the commercialization of autonomous driving technology and gain competitive advantages in the global market through independent research and development and innovation. This

Li Auto is actively recruiting top talents in the field of intelligent driving to prepare for the launch of new autonomous driving models. The biggest highlight of this model is its new algorithm architecture, which enables nationwide autonomous driving and is no longer limited to specific road areas. It is expected that in the first half of this year, the public will have the opportunity to meet this innovative model.

At the same time, NIO is intensively advancing research and development work and plans to launch active safety features based on end-to-end technology in the first half of this year. According to NIO insiders, if R&D progresses smoothly, NIO is expected to become the first automaker in China to achieve mass production of end-to-end technology.

Previously, Xpeng Motors founder He Xiaopeng announced that Xpeng Motors will soon fully apply the end-to-end model in the cars it produces. This series of developments shows that China's new automakers are competing fiercely in the field of autonomous driving.

End-to-end technology is a way to comprehensively revolutionize autonomous driving. It uses sensor data as input and directly outputs vehicle control instructions after processing by the neural network model. This "visual input, control output" method makes the implementation process of autonomous driving simpler.

However, some intelligent driving experts point out that it is not easy to switch the traditional autonomous driving architecture to end-to-end technology because it involves huge costs and technical difficulties. They predict that by the end of this year, only about 10% of autonomous driving functions will successfully achieve end-to-end technology transformation.

However, experts generally believe that once end-to-end technology matures and is widely used, car sales and large amounts of driving data will become new barriers to car brand competition.

Tesla recently pushed the FSD 12.1.2 update to non-employee car owners. This update marks a major upgrade for Tesla in the field of autonomous driving. According to Tesla CEO Musk, a key change in this upgrade is to reduce more than 300,000 lines of hard coding and rely more on neural networks to control vehicle steering, acceleration, braking and other functions. This means that Tesla’s autonomous driving system is changing to more intelligent neural network control.

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