China Securities Co., Ltd.: Autonomous driving in mining areas is the optimal commercial path for closed-circuit scenarios, with the potential to open a second growth curve overseas.

China Securities Co., Ltd. published a research report stating that autonomous driving in mining areas differs from Robotaxi services. The closed scenarios, rigid labor demands, and clear cost-reduction and efficiency-increasing values make its commercialization path clearer. The industry is expected to enter an S-curve acceleration phase after breaking the 10% penetration rate. Nearly 100,000 mining trucks in China provide ongoing renovation opportunities, while the expansion of large coal mine fleets, replication of metal mining projects, and the penetration of small and medium-sized mines will support domestic market growth. In overseas markets like Australia, where labor costs are high, the service value per vehicle is significantly higher than in China, which is expected to open a second growth curve. The main points from China Securities Co., Ltd. are as follows: Threefold drivers of policy, labor, and efficiency will lead to the commercialization of Level 4 (L4) technology in mining areas. Compared to urban Robotaxi services, the regulation of autonomous driving in mining areas is clearer and the technical implementation path is more certain, primarily addressing issues such as difficulty in recruiting for high-risk positions and high ongoing operational costs, thus achieving higher commercial acceptance. The policy side continues to promote mine automation and the replacement of hazardous job roles with Siasun Robot & Automation; economically, autonomous driving can reduce labor costs per vehicle by approximately 180,000 yuan per year, providing clear cost-reduction potential; operationally, unmanned mining trucks can achieve all-weather continuous operation, improving vehicle utilization; and in terms of safety, reducing personnel access to high-risk transport areas lowers accident risks. Collaboration across the industrial chain and resonance with domestic and foreign demand will enable unmanned mining trucks to enter a stage of scaled development. The domestic fleet of mining trucks is nearly 100,000 units, with relatively low levels of unmanned penetration. Coal mines currently constitute the main application scenario, while metal mines and large sand and gravel mines are expected to contribute future growth. As the industry penetration rate surpasses 10%, the scale of unmanned mining trucks in the domestic market is expected to reach 20,000 units by 2030, corresponding to a technological service market of approximately 4 billion yuan and an overall market space exceeding 5 billion yuan. In overseas markets, large mining areas in Australia, with their high labor costs and mature automation foundations, can achieve an annual service value of 2 million yuan per vehicle, while resource-based markets in Central Asia, Indonesia, and South America provide opportunities for domestic solution providers to scale their exports. The accelerated replication of controllable light assets, driven by technology and overseas markets. The company expects to achieve revenues of 1.435 billion yuan in 2025, with 2,580 active unmanned mining trucks, and the revenue share of customer-provided fleet models rising to 56.8%, as the business model continues to shift from heavy to light. Leveraging Zhuosh + Muye + Yushi, the company is building a full-stack technology system covering over 70 vehicle models, while operation across more than 30 mining areas creates a data feedback loop that enhances the ability to replicate across various models and mining types. The expansion of large domestic mines and the penetration of small and medium-sized mines provide continuous growth. The Australian project is entering true production, with the annual service value per vehicle expected to reach 1-2 million yuan, and overseas high-value markets expected to form a second growth curve. Risk Analysis: The penetration rate of autonomous driving in mining areas may increase less than expected; the promotion of the light asset business model may fall short of expectations; the concentration of large domestic mining customers is relatively high; technological iteration and adaptation to complex scenarios may not meet expectations; intensified industry competition may pressure profitability; expansion in overseas markets may underperform; the level of high-value service fees overseas may be lower than anticipated; continued increases in R&D and overseas investments may lead to profitability improvements lagging behind expectations; and there are risks related to changes in mining safety regulations and autonomous driving policies.