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Steering Trouble

Advanced driver assistance is becoming a selling point for Chinese EV makers. But without stricter oversight, experts warn of system gaps, distracted drivers and vague standards amid a surge in ‘intelligent cars’

By Xie Ying , Chen Weishan , Wang Shihan Updated Jul.1

An intelligent driving testing system at the National Intelligent Connected Vehicles Testing Zone in Changsha, Hunan Province conducts a simulation of people walking in rain in front of cars, June 12, 2023. The test station, which has water spraying equipment in the roof and walls, can simulate all kinds of weather from heavy rain to thick fog (Photo by CNS)

Xiaomi, the Chinese smartphone brand and now EV automaker, recently renamed the intelligent driving system of its flagship SU7 model from “intelligent driving” to “assisted driving.” 

The rebranding came after a widely covered car accident late on March 29, in which an SU7 crashed into cement columns on a highway in Anhui Province. The vehicle erupted in flames, killing the driver and the two passengers, all in their 20s. 

According to media reports, the highway was under repair at the time. A sign warned drivers to change lanes, but the car was in NOA (Navigate on Autopilot) mode, traveling at 116 kilometers per hour before the crash. The NOA system did not begin to reduce speed until approximately two seconds before the collision. Although the driver managed to take control within that brief window, the vehicle still struck the columns at 97 kilometers per hour. 

The incident sparked widespread public concern over the safety of intelligent driving, which many users, due in part to marketing, mistakenly equate with autonomous driving. Netizens expressed alarm that the SU7’s system gave the driver too little time to respond and failed to take sufficient measures to avoid the hazard. 

Under China’s current road traffic safety law, intelligent driving is classified into five levels from one to five: partial assistance, combined assistance, conditional autonomy, high-level autonomy and full autonomy without a driver or steering wheel. 

The Society of Automotive Engineers International defines L3 and above as “high-end intelligent driving.” However, as Chinese law does not yet permit L3 or above systems in private vehicles, manufacturers often brand NOA systems as “L2+ intelligent driving.” 

Experts caution that manufacturers have exaggerated the capabilities of intelligent driving systems in pursuit of sales and cost efficiency while neglecting the crucial role of safety, a function highly dependent on both hardware and software such as computing power and databases. This has created significant risks for users and manufacturers alike, particularly in the absence of clear regulations and industrial standards to provide oversight and guidance.

Corner Cases 
Unlike human drivers, who typically become comfortable navigating urban roads before taking to the highway, intelligent driving systems like NOA were initially developed for highway scenarios. 

An industry insider told NewsChina on condition of anonymity that even in well-developed highway settings, such systems have clear limitations, such as weak responses to construction zones or accidents ahead, difficulty recognizing unusually shaped vehicles, and overly conservative emergency responses. 

These rare or unusual situations are referred to as “corner cases.” Experts warn that they pose substantial safety risks, constrained by the system’s limited computing power and incomplete driving databases. 

The SU7 accident occurred during such a corner case: a road under construction at night. While the chances of such scenarios are low, they are potentially fatal and demand major investment in the technology. 

“Carmakers haven’t paid enough attention to scenarios like road repairs or construction,” an academic who has studied intelligent driving for years and refused to reveal his name told NewsChina. “For example, the AEB (Autonomous Emergency Braking) system often can’t respond to obstacles like cones or water barriers because it hasn’t been adequately trained for those situations. Highway construction is a typical corner case, but manufacturers haven’t collected enough data or haven’t even addressed it yet.” 

Due to current limits in computing power, intelligent systems struggle to retain information from warning signs or digital displays. Although signs, like those advising reduced speed, are often repeated along the road to give drivers time to react, the systems cannot consistently process or remember them over time. 

It is precisely these corner cases that prevent carmakers from achieving true autonomous driving. Regardless of whether systems are marketed as L2+, L2.9 or something else, they do not meet the standards of L3 or higher autonomous driving. 

“No matter how rare corner cases are, 1 percent or even 0.01 percent, they still require human drivers,” said the anonymous industry insider. “No one really knows how many corner cases remain unresolved.”

A Xiaomi SUV7 is in flames after crashing at high speed on a highway in Anhui Province, killing three young people, March 29, 2025 (Video Clip)

The charred wreck of the Xiaomi SUV7 after the fatal collision on March 29 (Video Clip)

Cost of Safety 
In a 2025 report on intelligent driving in China, Beijing-based automobile industry platform Autohome cited data from the US Insurance Institute for Highway Safety stating that L2+ intelligent driving can reduce car accidents by 40 percent. This is because machines never tire or get distracted like human drivers. 

However, their intelligence is highly dependent on the training they receive, training that relies heavily on both tech and cost. Currently, large-scale models and inference models are difficult to install in cars, making it even harder to solve corner cases. 

That is why experts believe that intelligent driving systems that combine both cameras and lidar (laser radar) are much safer than systems relying on cameras alone, despite the higher cost of lidar. 

“The two modes differ in how they assess irregular and uncommon obstacles. The camera-only mode depends on the model’s generalization capabilities, which may fail to recognize certain obstacles, especially in low or overly bright lighting conditions,” said Sun Hui, technical director at the Suzhou Automotive Research Institute, Tsinghua University. “They are at a disadvantage in depth perception, in responding to high-dynamic scenarios like reflected or backlight, and in performance during special conditions such as dark nights, rain or smoke.”

Hands Off the Wheel 
The SU7 car involved in the recent crash was an economy model equipped only with a camera-based intelligent driving system. Upgraded SU7 models are equipped with both camera and lidar systems and offer higher computing power thanks to more advanced hardware. According to the industry insider, a lidar unit used in intelligent vehicles typically costs between 3,000 and 7,000 yuan (US$428-1,000). 

Although the camera-only approach is now US EV company Tesla’s primary configuration, experts noted that Chinese car brands lag behind Tesla in both camera performance and computing power. For instance, Tesla’s latest Model Y vehicles are equipped with eight 5-megapixel Sony cameras capable of functioning in near darkness, or 1 lux, a unit of light sensitivity 

Although domestic brands may use higher-pixel cameras, they often are less light sensitive. Experts also believe that Tesla, as a global pioneer, has superior computing capabilities and a more comprehensive data infrastructure. 

“Some domestic brands haven’t even established a closed-loop user data system yet,” said the anonymous academic. “Tesla’s V12 FSD (Full-Self Driving) system uses data from 10 million segments, each containing one minute of user driving data... Such enormous data volumes can’t be obtained just through collection. It costs about 7 to 8 billion yuan (US$1-1.3b) to collect and label this kind of data.” 

To cut costs and capture more market share, some Chinese automakers are pushing to install intelligent driving systems in budget models. 

In February, leading Chinese automaker BYD announced at a launch event that it would equip all of its vehicles with “high-end intelligent driving systems,” with 21 new models set to debut. Wang Chuanfu, BYD’s chairman and CEO, stated that high cost is the biggest barrier to making intelligent driving accessible to the public, and that BYD aims to allow most of its customers to use these technologies. 

Wang predicted that 2025 would be “the first year of intelligent driving for all people,” and that high-end intelligent driving would become standard equipment on all vehicles within two to three years. 

His comments sparked heated debate in the industry. Yu Chengdong, a member of Huawei’s standing board and head of its intelligent car division, claimed on Weibo that “A usable intelligent driving system is totally different from one that is truly good and safe.” Similarly, Great Wall Motors CEO Wei Jianjun commented that intelligent driving “is not about putting on a show, it’s about each user and their family’s safety and experience.” 

Despite the controversy, intelligent driving systems have seen rapid growth in China over the past two years. Data from the Gaogong Intelligent Automobile Research Institute showed that in 2024, about 8.67 million vehicles with L2 intelligent driving systems (excluding NOA) were launched in China, a 25.33 percent year-on-year increase. Meanwhile, the NOA segment saw 1.97 million cars launched, a staggering 162.31 percent increase from the previous year. 

Figures from the Ministry of Public Security indicated that by the end of 2024, China had 31.4 million energy vehicles on the road, 11.25 million of which were registered that year. Among those new vehicles, 57.3 percent were equipped with L2 intelligent driving systems. A research report by CITIC Securities in December 2024 projected that the number of cars in China equipped with NOA systems will reach around five million in 2025 – three million with urban NOA and two million with highway NOA. 

At the 2025 Auto Shanghai show in late April, Chinese automaker Chery unveiled a new model priced at about 66,000 yuan (US$9,400), equipped with an intelligent driving system. 

Due to the lack of a clear definition from authorities on what exactly constitutes “high-end intelligent driving,” automakers have flooded the market with exaggerated advertising slogans, such as “ceiling-level quality,” “a revolutionary version,” “have a meeting while driving,” and “relax throughout your long journey.” Companies often highlight the highest-level features of a vehicle without clarifying that these apply only to premium configurations, misleading consumers into thinking that all models share the same capabilities. 

This marketing hype has led many consumers to equate “high-end intelligent driving” with autonomous driving. As a result, some now mistakenly believe that drivers can safely take their hands off the wheel thanks to these systems.

The 2024 National Intelligent Driving Test Event, China’s most important test for intelligent driving, is held on December 19, 2024 in Wuhan, Hubei Province (Photo by VCG)

Road Ahead 
The SU7 crash was a wake-up call for China’s intelligent driving craze. As automakers rush to roll out so-called L2+ systems, it has become increasingly clear that many have yet to strike the necessary balance between offering convenience and ensuring drivers remain alert behind the wheel. 

In a March report, China Automotive News cited Wang Fang, director of the reporting department at the China Consumers Association, as saying that 73 percent of complaints related to auto driving involve distracted driving caused by over-reliance on intelligent systems. 

“When drivers start treating the seat like a sofa, it’s a misunderstanding more dangerous than any algorithmic flaw,” she said. 

While DMS (driver monitoring systems) are capable of tracking driver alertness through facial cues, privacy concerns have made many drivers resistant to such monitoring. At the same time, carmakers are hesitant to promote or enhance these systems for fear of undermining user confidence in their technologies. 

Experts argue that timely and effective “handover” from machine to human is essential for L2+ systems. 

According to Zhu Xichan, a professor at the College of Automotive Studies at Tongji University in Shanghai, there is an average of just 1.7 seconds between a system warning and an actual accident, far too short for drivers to react. Human response time under normal conditions typically requires at least 2.3 seconds, and the delay is even longer if drivers are not fully engaged while the system is active. 

So far, Chinese regulators have not issued clear requirements for when or how L2+ systems should return control to human drivers. 

International standards for L3 systems recommend giving drivers at least 10 seconds to respond once a warning is issued, but no mandatory “time to collision” (TTC) thresholds have been set for L2+ systems. 

“The hardware in most current vehicles simply can’t meet that standard,” said the anonymous industry insider. “At 120 kilometers per hour, a 10-second TTC would require a sensor range of 300 meters. But few existing vehicles are equipped with laser radars that can detect that far. If a system can offer even five seconds, that should be part of a mandatory standard.” 

Sun Hui agrees, attributing the regulatory gap to the ambiguous definition of L2+ systems, especially given the wide range of capabilities between carmakers. 

“We’re participating in a long-term test by the China Automotive Engineering Research Institute,” said the anonymous academic. “We’ve grouped cars with high-speed NOA into six price categories and are evaluating their performance feature by feature. Our goal is to help fill the void in national standards and lay the foundation for more effective oversight. If a vehicle underperforms, stricter intervention may be necessary.” 

On February 28, the Ministry of Industry and Information Technology (MIIT) and the State Administration for Market Regulation released a document on further strengthening the management of intelligent connected vehicles’ market entry, recall and software upgrading. 

For the first time, the guidance outlines baseline requirements for operating intelligent systems. Automakers must now test vehicles in varied road, infrastructure and weather conditions and must trigger human handover – through sound, lights or speed reduction – when a situation exceeds system capabilities. 

The document also cracks down on misleading and exaggerated advertising. 

The move is seen as a positive step toward the healthy development of the intelligent vehicle sector, especially as companies set their sights on L3 systems and beyond. 

At the China EV100 Forum 2025, held in March in Beijing, an MIIT official revealed plans to conditionally approve L3 vehicles for production and market entry. 

Also at the forum, Wan Gang, chairman of the China Association for Science and Technology, called for the establishment of dedicated safety legislation and market-entry testing standards tailored to high-level intelligent vehicles. 

He emphasized that L3 represents a turning point not only for technical innovation, but also for user expectations and responsibility frameworks. Although current laws hold drivers at fault for car accidents involving intelligent driving systems rated L2 or lower, the new document proposes further clarification based on accident details. 

Beijing’s new Regulation on Autonomous Vehicles, which came into effect on April 1, is viewed as a milestone for the industry’s healthy development. It is the first regulation in China to support autonomous functions in privately owned vehicles, and experts say it could accelerate national-level policymaking around intelligent driving. 

“I don’t believe interest in intelligent driving will fade because of these safety debates,” said Zhu Xichan with Tongji University. “But I do believe the industry’s narrative will shift, from emphasizing intelligence to emphasizing safety.”

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