Guolian Minsheng Securities released a research report stating that the industrialization of RoboX is accelerating, driven by strong policy tailwinds, with national-level support measures establishing a foundational institutional framework for large-scale deployment. On the demand side, the urgent need for cost reduction and efficiency enhancement is a key driver, significantly lowering operational expenditures. On the supply side, technological breakthroughs are notable, with the costs of core hardware components continuing to decline, thereby propelling widespread implementation. RoboX is transitioning from technical validation to achieving commercial viability, with penetration rates expected to surge rapidly during 2026-2027, unlocking a market potential valued in the hundreds of billions. The firm believes that autonomous driving solution providers and operators will directly benefit from the commercial scaling of RoboX, with an inflection point in profitability models now emerging. Guolian Minsheng Securities' key views are as follows:

RoboX is approaching an industrial singularity, accelerating its shift from technical proof-of-concept to large-scale deployment. On the policy front, since 2020, the State Council and various ministries have intensively issued supportive policies, leading to increasingly robust institutional safeguards. On the supply side, the penetration rate of L2 and higher intelligent functions in passenger vehicles is rising swiftly, driving the mass production and significant cost reduction of core components like LiDAR and computing chips. On the demand side, multiple factors—including the push for cost efficiency, enhanced safety, and labor shortages—are collectively fueling strong demand for intelligent driving. With its unique value across various transport scenarios, RoboX is becoming the core force leading this wave of industrial transformation, and the commercial singularity may have already arrived.

Robotaxi: Inflection Point for Scale Has Emerged; Fully Driverless Commercialization is Gradually Being Implemented. On the demand side, the core advantage of Robotaxi lies in substantial cost reduction; data from WeRide indicates that by 2027, Robotaxi operating costs are projected to be $0.2 per kilometer, a 50% reduction compared to traditional ride-sharing platforms, primarily driven by the remote safety operator model and economies of scale optimizing labor costs. Concurrently, Robotaxi can significantly lower accident rates by minimizing human error, greatly enhancing safety, with the global market expected to reach a scale of hundreds of billions by 2030. On the supply side, declining hardware costs and improved operational efficiency are key factors. Pre-installed mass-produced Robotaxis are becoming a core driver for accelerating industry commercialization, facilitating the shift from demonstration projects to scaled deployment through substantial hardware cost reductions and standardized production. Tesla's entry into Robotaxi with a pure vision solution acts as a new, powerful catalyst for the sector. On the policy front, fully driverless commercialization is being rolled out in key Chinese cities, moving from technical validation towards closed-loop business models.

Robovan: Strong Demand for Unmanned Delivery; Cost Reduction in Core Components Drives Price Advantages. On the demand side, the last-mile delivery segment faces severe labor shortages and high cost pressures, creating an urgent need for automation. Robovan, with its all-weather, high-frequency, low-cost operational capabilities, has become a critical solution, already widely deployed across four high-frequency, essential scenarios: e-commerce logistics, supermarket retail, fresh food delivery, and industrial parks. On the supply side, economies of scale are driving down the cost of core components, giving unmanned delivery vehicles a significant price advantage. The rapid increase in the standard inclusion rate of NOA functions in passenger vehicles, with L2 and above penetration expected to exceed 90% by 2030, is promoting the mass production of core components like LiDAR and computing chips, driving the price of unmanned delivery vehicles down from the 500,000-600,000 yuan range to around 20,000 yuan. Startups are forming integrated "hardware + software + service" business models. On the policy front, the opening of road rights and the implementation of pilot programs continue to accelerate. In January 2024, a joint "Pilot Notice" from five departments including the MIIT set a mandatory target of "deploying no fewer than 200 low-speed unmanned vehicles," pushing the industry from demonstration phases towards scaled application.

Robotruck: Transitioning from Enclosed Sites to Long-Haul Logistics; Cross-Province Platooning Tests are Underway. On the demand side, Robotruck applications primarily include enclosed scenarios like ports and mines, and long-haul logistics, with the market size for pre-installed systems and transport services poised to reach hundreds of billions. On the supply side, enclosed scenarios are leading the way in achieving L4 deployment, validating all-weather, high-intensity operational capabilities. Although the environment for long-haul logistics is complex, stable freight demand and high operational value make it a core direction for commercialization, currently moving from demonstration and validation to small-scale operations focused on proving profitable business models. By employing a "virtual driver" system, Robotruck can substantially reduce the operating costs of pure-electric tractor units. On the policy front, national support is clear, but due to the high accident risks associated with heavy trucks, local authorities maintain a cautious approach to opening roads; however, the "vehicle-road-cloud integration" pilot program is expected to accelerate cross-provincial coordination.

Risk warnings: Slower-than-expected increase in intelligent function penetration rates; slower-than-expected customer expansion; intensifying market competition; failure to establish profitable business models; slower-than-expected implementation of autonomous driving policies.