The automotive industry has been abuzz with the recent news of Tesla's Full Self-Driving (FSD) software entering the Chinese market. Since Tesla's official announcement on February 25, 2025, to roll out FSD updates in batches for Chinese customers, discussions have reached a fever pitch. Many eagerly await the legendary autonomous driving technology, while others question whether this foreign "monk" can truly grasp the nuances of China's "true scriptures" of intelligent driving.

FSD, often regarded as the "soul" of Tesla, is an advanced autonomous driving system based on a pure vision solution. It relies on cameras to capture images and uses AI for decision-making, enabling functions like lane keeping, automatic parking, and intersection assistance. In North America, FSD has undergone numerous iterations, earning praise for its performance in automatic lane changes and navigation-assisted driving. On simpler highways, FSD can maintain a steady speed and route, reacting promptly to changes in traffic flow, reducing driver fatigue.

However, China presents a unique challenge. Its traffic environment is unparalleled in complexity, with intricate road planning, frequent rule changes, and a high density of non-motorized vehicles and pedestrians. Can FSD's North American experience translate to China? Musk's "pure vision route" excels in North America but faces hurdles in China. Non-standard traffic participants like electric bicycles and tricycles dominate domestic roads, exceeding European and American levels. Moreover, China-specific driving behaviors like "ghost probing" and continuous lane changes demand extensive perception capabilities. Notably, of Tesla's 200 billion kilometers of global training data, complex Chinese scenarios account for less than 3%.

Data collection is another significant challenge. FSD's "end-to-end" architecture heavily relies on data, necessitating vast amounts of real-world driving data for model training and habit learning. However, data collection in China is restricted by policy, limiting Tesla's ability to gather data as freely as in North America. Despite China's vast user base, with Tesla selling nearly 660,000 vehicles in 2024, compliance issues hinder the utilization of this data for FSD training. Tesla currently relies on engineering vehicles for limited data collection and internet videos, which are inferior in quality.

FSD's reliance on visual perception also has limitations in China's diverse road conditions. Cities like Chongqing, known as a 5D city, present complex three-dimensional traffic that often confuses navigation systems. Special road facilities like bus lanes, diversion islands, and waiting areas pose significant recognition and response challenges for FSD. Visual sensors' performance diminishes significantly in heavy rain and fog, posing safety risks. Tesla has previously encountered fog-related accidents in North America, highlighting the potential for worse outcomes in China.

Safety remains paramount in autonomous driving. FSD's safety concerns have sparked debates in North America, with several autonomous driving-related accidents. In China's complex traffic environment, safety is even more critical. When FSD vehicles coexist with other intelligent driving systems, decision-making conflicts can introduce uncertainties, increasing accident risks due to differing decision-making logics.

Vehicle-Road-Cloud integration may offer a solution for FSD to establish a foothold in China. This integration enables data interchange and collaboration between vehicles, roads, and the cloud. Vehicles and road devices collect data, which the cloud processes and feeds back decisions to vehicles, enhancing intelligence and safety. This integration enriches data dimensions, complements FSD's perception shortcomings, and aids in complex scenarios like intersections. From a safety perspective, the Vehicle-Road-Cloud network provides multi-layer protection, monitoring vehicle and road status in real-time and issuing warnings or takeover instructions to prevent accidents.

However, integrating FSD into the Vehicle-Road-Cloud network is not straightforward. Tesla's emphasis on technology independence may raise concerns about data security and technological property rights when sharing data and interfaces. Additionally, while Vehicle-Road-Cloud integration has progressed in China, regional and enterprise differences in standards and norms require establishing unified industry standards to ensure seamless integration. Without these standards, compatibility issues could arise.

The true value of FSD's entry into China may not lie in proving the merits of a technological route but in unveiling the competitive landscape of intelligent driving. As companies like Mushroom Auto's Vehicle-Road-Cloud networks become "Chinese commanders" for FSD, and Tesla's data algorithms contribute to China's Vehicle-Road-Cloud evolution, this symbiotic relationship heralds the practical implementation of AI in the physical world. Whether FSD experiences 'culture shock' or finds 'true delight' may hinge on every intelligent road pole communicating with it.