China and the U.S. are expanding their smart heavy-truck logistics networks, with autonomous driving expected to first replace truck drivers.

Due to the fixed nature of freight logistics routes and relatively straightforward road conditions, the demands on mapping and sensing technologies are lower compared to those for passenger vehicles. As a result, numerous autonomous driving startups around the globe are already exploring commercialization opportunities in the freight logistics sector. Before fully replacing human drivers, autonomous technology may first target truck drivers—again, thanks to the predictable routes and simpler road environments that place fewer stringent requirements on advanced map and sensor systems than those needed for passenger cars.

On October 19, China's smart contract logistics enterprise Rongqing Logistics and autonomous heavy-truck company PlusAI Technology announced the launch of China's first mass-produced intelligent heavy-truck dedicated freight route. According to plans, once fully operational, Rongqing Logistics will gradually acquire smart heavy trucks equipped with PlusAI Technology's PlusDrive system, while expanding its operational network across the country. It was noted that the two companies have initially chosen a major trunk-line logistics route in East China—region, where freight demand is particularly robust—as their pilot route. This two-way dedicated line will cater to various types of cargo, including general goods and cold-chain products, and will initially rely on FAW Jiefang’s mass-produced, autonomous J7 Super Truck for transportation. This route connects three key economic hubs: the Yangtze River Delta, the Beijing-Tianjin-Hebei region, and the Jinan commercial area, spanning critical highways such as the busy Beijing-Shanghai and Shenyang-Haikou corridors—both of which handle substantial volumes of high-value goods. As a result, this route demands the highest standards of safety and efficiency.
Rong Li, General Manager of ZhiJia Technology China, told a reporter from First Finance that ZhiJia is a company equipped with L4-level full-stack autonomous driving technology. This particular application represents the first real-world implementation of L4 technology—albeit in a scaled-down form—on intelligent heavy-duty trucks supervised by human operators. Rong Li emphasized that in the trillion-dollar trunk logistics market, the adoption of autonomous driving technologies can significantly reduce costs and enhance efficiency for the logistics industry. According to data from the National Bureau of Statistics, China's total social logistics expenses in 2020 reached 14.9 trillion yuan, accounting for 14.67% of GDP. Within China's logistics transportation structure, road freight transportation remains overwhelmingly dominant, consistently representing more than 70% of the country's total freight volume.
In the United States, PlusAI has already signed an order with e-commerce giant Amazon to supply at least 1,000 sets of its PlusDrive smart system, upgrading Amazon’s long-haul logistics fleet. Meanwhile, U.S. trucking operator Ryder System announced on Tuesday a partnership with autonomous driving startup Gatik to develop a short-haul autonomous logistics network across the country. Gatik has already collaborated with companies like Walmart to deliver goods from warehouses directly to retail stores. Autonomous heavy-truck startup TuSimple Future is also leveraging Ryder’s logistics network in the U.S. TuSimple Future is poised to launch a fully driverless autonomous technology in Arizona later this year—marking the fourth quarter—and plans to expand its U.S. autonomous heavy-truck testing network. However, mass production of self-driving trucks still has a long way to go. According to TuSimple Future’s roadmap, the company aims to begin delivering its autonomous heavy trucks to customers—including UPS—by 2024.
ZhiJia Technology also told a reporter from Caixin that the smart heavy-truck project launched in China currently does not yet achieve true autonomous driving functionality—it merely features a software system that lays the groundwork for future autonomous capabilities. Compared to many previous autonomous driving test vehicles, the key difference is that the ZhiJia smart heavy trucks now on the road are automotive-grade, pre-installed mass-produced vehicles legally qualified for on-road operations. There has never before been a precedent of mass-produced smart heavy trucks being deployed on dedicated trunk-line logistics routes.
ZhiJia Technology did not disclose to a reporter from Caixin about its plans for mass-producing future intelligent heavy-duty trucks. "It's still too early to discuss mass-production targets at this stage," the company's spokesperson told a Caixin reporter. In recent years, self-driving heavy-duty trucks have attracted significant attention from capital markets. Over the past year, autonomous driving startups such as Plus, TuSimple, and Embark Trucks have either already entered or are poised to enter the U.S. stock market. Investors are particularly optimistic about self-driving heavy-duty trucks because, compared to self-driving passenger vehicles like Robotaxis, the business models for autonomous heavy-duty trucks are clearer and more likely to achieve profitability.
Zhang Mingtang, a partner at Fangyuan Capital, told a reporter from Caijing: "Benefiting from the advancements in AI technology over the past few years, autonomous vehicles are becoming increasingly intelligent. However, compared to passenger cars, commercial vehicles are likely to see their business models implemented more quickly." That said, he acknowledged that the development of self-driving heavy-duty trucks is still in the early stages of exploring viable business models—and we're not yet at the point of discussing pricing. Relevant research data reveals that, currently, fuel costs account for 30% of mainline logistics expenses, while labor costs make up another 30%. As the most critical productivity tool, heavy-duty trucks have become a key factor influencing the sustainable growth of logistics companies.
Industry insiders believe that although the cost of self-driving heavy trucks may be higher than that of conventional trucks—due to components like sensors and software—the long-term cost advantage remains, thanks to the potential to significantly reduce human drivers' working hours in the future. For instance, TuSimple's autonomous heavy trucks can complete a journey from California to Florida’s coast in approximately 36 hours, cutting the driving time nearly in half compared to what human drivers would typically require. Moreover, the technology needed to enable automated freight services on fixed routes is simpler, placing fewer demands on detailed map data.
This June, Cainiao, Alibaba's logistics subsidiary, also announced it will develop self-driving heavy-truck technology. Meanwhile, Torc Robotics, Daimler's autonomous heavy-truck division, is collaborating with Amazon's cloud computing arm to manage the massive amounts of autonomous truck data generated at its facilities in New Mexico and Virginia, USA.

Translated from Sina Auto

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