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Yayuan Mo

Peng Gao

Zhen Zhang

Vehicle production has long been a symbol of national technological prowess and the manufacturing capability of countries such as the United States, Japan and Germany in the 20th century. As a result, China’s rapid global expansion in electric vehicles (EVs) in recent years has been a hot topic.
While the winner of the EV competition is yet to be determined, the next chapter of the contest is to achieve autonomous driving, which relies on artificial intelligence (AI), semiconductor technology and data-driven intelligence. This underscores a broader geopolitical contest where leadership in this domain equates to shaping the global balance of tech power.
Progress in autonomous driving is continuing steadily. The Society of Automotive Engineers categorises automation from Level 0 to Level 5, with Level 0 involving full human control and Level 5 representing complete machine control. Currently, Tesla operates at Level 2, or partial automation.
Some companies have blamed regulation for keeping them from achieving Level 3 certification. So far, Level 4 automation is primarily seen in robotaxis approved for experimental services, such as Waymo in Phoenix, Arizona, and Baidu’s Apollo Go in Wuhan. As of the end of 2024, no commercial vehicle has been certified for Level 5 automation.
The US currently has an advantage when it comes to the development of AI chips for vehicles. Although Chinese companies have shown excellent performance in the global EV market, only 10 per cent of the chips used in vehicles made in China are developed domestically, with the other 90 per cent imported from the US, Europe and elsewhere. This has raised valid concerns that the US could tighten restrictions on the export to China of AI chips used in vehicle manufacturing.


These high-end chips are difficult to develop independently. By limiting Chinese access to such critical technologies, the US could weaken China’s competitive edge in the global EV market. This aligns with broader US efforts to curb China’s technological rise in sensitive sectors such as AI and semiconductors.
In response, China has launched a two-pronged strategy to challenge US dominance in autonomous driving technology. First, it is championing the vehicle-to-cloud (V2C) model, which shifts computational demands from in-vehicle systems to external infrastructure. This approach prioritises robust communication networks over in-car processing power, mitigating reliance on high-performance chips.
Simultaneously, China is making massive investments in domestic semiconductor manufacturing and innovation, seeking to close the gap with the US and Europe in the next decade. However, these efforts are seriously constrained by the export controls maintained by the US and its allies.
The US has also put forward some preventive plans to curb China’s autonomous driving development. The proposal to ban Chinese-made hardware and software for automotive driving systems and vehicle connectivity systems could protect the US domestic system market and restrict Chinese product expansion. Moreover, US regulation often has a ripple effect, which can be seen in Canada announcing plans to ban vehicle software from China soon after the US proposal.


Like the human brain processing complex information to make decisions, advanced AI chips handle huge computational tasks at rapid speed under complex road situations. Advanced driving models cannot be built without a large amount of reliable data. Like blood inside a body, data is a fundamental component of the autonomous driving model.
For instance, Tesla has used driving videos captured from its vehicles to provide valuable insights into safe driving practices, training its model to better anticipate and react to real-time situations. Moreover, as the V2C model develops, data will expand beyond individual vehicles to include road conditions, traffic signals, infrastructure and nearby vehicles.
However, driving data is difficult to obtain because of increasingly stringent data regulation compliance. The European Union’s General Data Protection Regulation (GDPR), for example, imposes rigorous requirements on automotive companies to ensure transparency, traceability and security throughout the data life cycle. GDPR stipulates that all personal data generated by electric vehicles must be stored in facilities compliant with EU data security standards, either locally or on EU-approved servers.
In the US, there are state-level data security regulations such as the California Consumer Privacy Act. Similarly, China’s Cybersecurity Law mandates that driving and road data generated within the country be stored domestically.




These regulatory frameworks underline the fragmented nature of global data regulation, driven by varying national security and privacy considerations. Non-compliance with these laws could subject companies to operational restrictions or financial penalties, significantly complicating multinational corporations’ efforts to harmonise their systems and increasing operational costs across multiple markets.
Under such a fragmented global regime, negotiations between governments and multinational companies are often iterative. For example, when Tesla entered the Chinese market, it initially faced restrictions on its camera systems because of security concerns, limiting access to sensitive areas. Over time, as Tesla complied with local regulations and improved its standing in the market, it was eventually included in the government procurement list, demonstrating the dynamic nature of such negotiations.
Ultimately, autonomous driving represents far more than the next transport frontier. It is a strategic battlefield where AI, semiconductor capabilities and geopolitical ambitions converge. EVs have evolved into an outstanding showcase of cutting-edge technology.
For major players such as the US, China and Germany, dominance in autonomous driving will extend beyond economic benefits. It is a declaration of strategic and technological sovereignty in the 21st century.


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Autonomous driving is not just the next frontier; it is a strategic arena where AI, semiconductor capabilities and geopolitics converge


Autonomous driving is not just the next frontier; it is a strategic arena where AI, semiconductor capabilities and geopolitics converge.


Electric & new energy vehicles

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US-China tech war

Expresses the views, ideas and conclusions of the author. (Eg. Enough of Crazy Rich Asians, think of crazy poor Hongkongers.)


US-China tech war’s next front will be autonomous vehicles

.css-1c6uqr6{color:inherit;font-weight:inherit;font-size:inherit;font-family:inherit;line-height:inherit;overflow-wrap:break-word;}Autonomous driving is not just the next frontier; it is a strategic arena where AI, semiconductor capabilities and geopolitics converge

Autonomous driving is not just the next frontier; it is a strategic arena where AI, semiconductor capabilities and geopolitics converge