Chinese autonomous driving startup Zhuoyu Technology is making a calculated push into commercial vehicles, arguing that fleet operators will adopt driver-assist systems only if they can prove a quick return on investment. In a group interview after its October 29 product launch, CEO Shen Shaojie and commercial vehicle business vice president Liu Sikang laid out the company's strategy, according to Chinese outlet D1EV.
One-year payback as the sales pitch
Shen said the fuel-saving data Zhuoyu disclosed translates to annual savings of 20,000 to 30,000 yuan (about $2,800 to $4,200) per truck, with a system payback period of roughly one year. For commercial customers, he said, this is not an experience purchase but an investment decision. The company is targeting two main segments: large fleets in the express and freight market, and individual truck owners in the less-than-truckload segment, who are more cost-sensitive because they spend their own money.
Zhuoyu announced partnerships with six of China's top heavy-truck brands, including XCMG, Shaanxi Auto, Sinotruk, FAW Jiefang, Foton and Dongfeng Commercial Vehicle, covering more than 93% of the domestic heavy-truck market. Shen attributed the wins to product performance, noting that legacy players' solutions cost several times more and lag in energy-saving capabilities. However, he acknowledged that competition will intensify once the market proves viable.
Liu said commercial vehicle ADAS penetration was likely below 1% last year, compared with over 30% for L2+ in passenger cars. The low rate is mainly due to cost, he said, but once the economics work, adoption will rise. Zhuoyu is keeping its business model open, exploring outright purchase, subscription and insurance-linked options, though Shen stressed that the underlying math must be sound.
Technology transfer and safety concerns
Zhuoyu is leveraging its passenger-car end-to-end foundation model for commercial vehicles, adapting it rather than writing new algorithms. Liu said the company spent two to three months tuning the system for heavy trucks last year and three to four months for buses this year. But he cautioned that it is not simply installing software; the vehicle's control characteristics differ greatly, requiring additional sensors and calibration.
Data training mixes passenger-car and commercial-vehicle data, with adjustments in model structure and data ratios, Liu explained. For example, the company uses two rear-view cameras to monitor trailer status, a feature unique to trucks. Fuel-saving algorithms are a key focus, as they are both difficult and critical for trucking economics.
On the question of urban NOA (city advanced driver assistance) for heavy trucks, Liu was pragmatic: 99% of long-haul logistics runs on highways, so urban capability has little demand and faces technical hurdles. It is more suited to light trucks and buses. Shen added that while handling red lights and scooters on national roads is necessary, navigating urban villages is not a core scenario for heavy trucks.
Safety remains the biggest concern. Shen warned that a single fatal accident could destroy the business, noting that suppliers in automotive history have collapsed after such incidents. He said the company's development cycle for commercial vehicles is much longer, with truck MPI (miles per intervention) requirements more than ten times those of passenger cars, and design life of trucks starting at 1.5 million kilometers (about 932,000 miles) versus 200,000-300,000 kilometers for cars.
Looking ahead, Zhuoyu sees a potential boom in commercial vehicle ADAS within two to three years, but also expects intense competition. Shen said the key metric for success is the proportion of highway NOA usage; if over 90% of miles are driven with the system engaged, that indicates the product has taken hold. The company's immediate goal, he said, is to scale up delivery and accumulate real-world operating data.
