Guolian Minsheng Securities: Benefits of RoboX in commercial applications of automated driving are accelerating through scale.
The bank believes that autonomous driving solution providers and operators will benefit directly from the commercial scale of RoboX, and the inflection point of the profit model has emerged.
Guolian Minsheng Securities released a research report stating that the industrialization of RoboX is accelerating, driven by strong policies. Support measures at the national level are laying the institutional foundation for large-scale implementation; demand is being driven by the urgent need to reduce costs and increase efficiency, significantly reducing operating costs. On the supply side, there have been significant technological breakthroughs, with core hardware costs continuously decreasing, driving large-scale implementation. RoboX is transitioning from technical validation to commercialization and is expected to see a rapid increase in penetration rates in 2026-2027, unleashing a market potential of hundreds of billions. The firm believes that autonomous driving solution providers and operators will directly benefit from the large-scale commercial use of RoboX, with a turning point in the profit model already visible.
Key points from Guolian Minsheng Securities:
RoboX is reaching a tipping point in industrialization, accelerating from technical validation to large-scale deployment.
On the policy side, starting from 2020, the State Council and ministries have issued a series of supportive policies, with institutional safeguards becoming increasingly perfect; on the supply side, the penetration rate of intelligent functions in passenger cars at L2 and above is rapidly increasing, driving the large-scale production of core components such as LiDAR and computing chips, with significant cost reductions; on the demand side, factors such as cost reduction, efficiency enhancement, safety improvement, and labor shortage are jointly driving a strong demand for intelligent driving. With its unique value in different transportation scenarios, RoboX has become the core force leading this round of industry revolution, with the commercialization tipping point possibly reached.
Robotaxi: The tipping point for large-scale commercialization is already here, with fully automated commercialization gradually taking off.
On the demand side, the core advantage of Robotaxi lies in significantly reducing costs. Data from WIMI shows that the operating cost of Robotaxi is expected to be $0.2/km in 2027, 50% lower than traditional ride-sharing platforms, mainly due to cost optimization driven by remote safety monitoring and economies of scale. At the same time, Robotaxi can significantly reduce accident rates by reducing human errors, greatly improving safety. The global market is expected to reach hundreds of billions by 2030. On the supply side, the key factors are the reduction in hardware costs and the improvement in operational efficiency. Pre-installed Robotaxis are becoming the core DRIVER accelerating commercialization in the industry, by significantly reducing hardware costs and standardizing production, driving Robotaxi from demonstration operation to large-scale deployment. Tesla's entry into the market with a pure vision solution has become a new strong catalyst for the sector. On the policy side, fully automated commercialization is gradually taking off in core cities in China, transitioning from technical validation to commercialization.
Robovan: Strong demand for unmanned delivery, with cost reduction of core components driving price advantages.
On the demand side, the last-mile delivery sector faces labor shortages and high costs, with an urgent need for automation. Robovan, with its ability to operate 24/7, high frequency, and low cost, has become a key solution, covering a wide range of high-frequency and essential scenarios such as e-commerce delivery, supermarket retail, fresh food delivery, and factory parks. On the supply side, economies of scale drive down the cost of core components, making unmanned vehicle price advantages significant. The standard rate of NOA function in passenger cars is rapidly increasing, with a penetration rate of over 90% for L2 and above expected by 2030, driving the large-scale production of core components such as LiDAR and computing chips, leading to a decrease in the price of unmanned delivery vehicles from 500,000-600,000 yuan to the range of 20,000 yuan, enabling startups to form an integrated business model of "hardware + software + service". On the policy side, the opening of road rights and the acceleration of pilot trials continue. In January 2024, the Ministry of Industry and Information Technology and four other departments issued the first "Pilot Notice" with a hard indicator of "deploying no less than 200 low-speed unmanned vehicles", driving the industry from demonstration to large-scale application.
Robotruck: Moving from closed scenarios to long-haul logistics with cross-province and city convoy tests.
On the demand side, the application scenarios for Robotruck mainly include closed scenarios such as ports/mining areas and long-haul logistics. The front-loading and power service market scales are expected to reach hundreds of billions. On the supply side, closed scenarios have achieved L4 implementation first, demonstrating the ability to operate intensively 24/7. Although long-haul logistics have complex environments, freight demand is stable, and operational value is high, making it the core direction for commercialization. It is transitioning from demonstration validation to small-scale operation, focusing on running a profitable model. Robotruck, by using a "virtual driver," can significantly reduce the cost of using pure electric tractor-trailers. On the policy side, national support is clear, but due to high risks of accidents involving heavy trucks, local authorities are cautious in their approach, with initiatives such as the "integration of vehicles and roads" expected to accelerate cross-provincial and city collaboration.
Risk warning: The penetration rate of intelligence may not increase as expected, customer expansion may not meet expectations, market competition may intensify, profit models may not materialize, and the implementation of intelligent driving policies may fall short of expectations.
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