Listing Success | Frost & Sullivan Supports Yikong Intelligent Driving Technology Co., Ltd. in Successfully Listing in Hong Kong (7687.HK)

MagnaTEC Advanced Materials was successfully listed on the stock market on July 8, 2026. The company plans to issue 26,132,000 H shares, including 23,518,800 shares for international offerings and 2,613,200 shares for Hong Kong offerings. The issue price is HK$87.92 per share, raising a net amount of over HK$2 billion.

During the IPO process, Frost & Sullivan performed the following tasks: helping the issuer accurately and objectively understand its position in the target market, using objective market data to identify and highlight the issuer’s competitive advantages, assisting the issuer, investment banks, and other intermediaries in writing important sections of the prospectus such as overview, competitive advantages and strategy, industry overview, and business, helping the issuer communicate with the Stock Exchange and investors, and assisting the issuer in responding to various questions from the Stock Exchange regarding the industry.

Frost & Sullivan has always been a leader in helping companies go public in Hong Kong. According to LiveReport Big Data (data as of June 30, 2026), in the past 36 months and 12 months, and from January to June 2026, Frost & Sullivan provided listing industry consulting services for 212 Hong Kong IPOs (market share of 69%), 111 IPOs (market share of 71%), and 58 IPOs (market share of 69%), ranking first in number of services provided. It has rich industry experience and communication skills with regulatory authorities, exchanges, investment and financing institutions, and related organizations.

Autonomous driving technology refers to technology that enables vehicles to operate without human intervention through advanced sensors, control systems, and artificial intelligence, usually referring specifically to L4 and L5 levels of high and full automation respectively.L5 levelDriverless systems. According to SAE classification, driverless is divided from L0 level (no automation) to L5 level (full automation). L0 level represents manual driving, where the human driver fully controls the vehicle. L1 and L2 levels introduce driving assistance technologies, where the system can assist with acceleration, steering, or braking, but still requires human supervision. L3 level allows conditional automation, where the vehicle can take over driving under certain conditions, but the driver must be ready to intervene when prompted. L4 level represents high automation, where the vehicle can drive autonomously within specific operating domains without human intervention, but still limited to certain environments. L5 level is full automation, requiring no human supervision or control, allowing the vehicle to operate automatically in all environments. Although achieving driverless on public roads, especially L5 level (full automation), remains a long-term goal, L4 level driverless has already been implemented in controlled environments such as mines, ports, and factories, where the vehicle can operate without human intervention under specific conditions.

Consumer vehicle smart driving can be roughly divided into three types: urban roads, intercity roads, and closed environments. Due to dense traffic, frequent stops, and unpredictable interactions, urban road applications (such as last-mile delivery vehicles) face the highest technical challenges, so most are in the pilot or early commercialization stage. Intercity road applications mainly involve autonomous trucking on highways, benefiting from structured routes, but high safety standards are still required for large-scale deployment. Closed environments such as mines and ports operate in controlled and predictable scenarios with minimal external traffic interference, making them the field with the highest degree of commercialization and the earliest large-scale deployment.

Smart driving is more widely used in commercial vehicles than in passenger cars because commercial vehicles face less uncertainty in operating environments, with clearer regulatory and economic conditions. Corporate users value efficiency and cost savings, enabling quantifiable returns on investment. In closed or semi-structured sites such as mines, ports, and factories, driverless trucks, tractors, and handling equipment have demonstrated their value by improving safety, reducing reliance on labor, and achieving stable high-precision operation. With clear economic benefits, including lower labor and fuel costs, fewer accidents, and higher efficiency, smart driving is expected to expand into environmental health, long-distance freight, and last-mile delivery as technology becomes more mature and labor shortages persist.

01

Overview of the Driverless Mining Solution Industry in China

Driverless technology accelerates the transformation of mines towards intelligence and driverless operations. By integrating driverless mine trucks, IoT infrastructure, cloud control platforms, and real-time scheduling systems, modernized transportation is achieved in mines. As a national priority for China to promote digital and intelligent industrial upgrading, "smart mines" focus on improving production efficiency, safety, and environmental performance. The transportation sector plays a crucial role as a key link between mining and processing. Driverless technology ensures continuous, accurate, and efficient ore transport, reducing risks, accident rates, and production losses. Open-pit mines dominate China’s coal and metal production, characterized by relatively structured point-to-point transportation routes, making them the primary application area for driverless technology, providing real-time measurable benefits in safety, normal operation time, and cost reduction.

Due to high accident rates, rising labor costs, severe labor shortages, and environmental pressures faced by mining operators, driverless is an inevitable requirement. In 2024, the death rate per million tons of coal mines in China was 0.059, and traditional mine transportation required 2 to 4 drivers per vehicle, with annual labor costs ranging from HK$100,000 to HK$150,000. The driver loss rate in some open-pit mines exceeded 50%, especially in remote areas. Driverless mine trucks address these challenges by keeping drivers away from dangerous environments, enabling 24/7 operation, improving efficiency and fuel efficiency, and controlling the scale of labor. However, the deployment process requires high technical standards: mining environments often lack paved roads, with variable terrain and exposure to dust, snow, and low light, necessitating powerful sensors, anti-interference sensing, and reliable positioning. Therefore, only a few providers of full-stack solutions that integrate software and hardware can offer reliable and scalable driverless mining systems, creating a high barrier and creating significant advantages for integrated practitioners.

02

Market Size of the Driverless Mining Solution Industry in China

Driven by strong regulatory trends, technological progress, and the need for safer and more efficient operations by mining operators, the driverless mining solution market in China has seen explosive growth. The market size of driverless mining solutions in China increased from a small scale in 2021 to approximately HK$3.8 billion in 2025, with a compound annual growth rate of about 171.4%. Although early stages were mainly focused on pilot programs and initial deployments, the industry is now entering a phase of large-scale deployment. As driverless is implemented in different mine types and regions, the market is expected to continue growing strongly. In 2024, the State Mine Safety Administration and the National Development and Reform Commission jointly issued the "Guiding Opinions on Further Promoting Intelligent Mine Construction and Facilitating Safe Mine Development," setting clear goals: by 2026, all coal mine working faces should adopt an intelligent system, with at least 80% of intelligent working faces operating normally, and the replacement rate of intelligent equipment or robots in hazardous and heavy-duty positions in coal and non-coal mines should be no less than 30% and 20% respectively. Additionally, in 2024, the Ministry of Natural Resources and six other ministries jointly issued the "Notice on Further Strengthening Green Mine Construction," encouraging the application of advanced green and low-carbon technologies to accelerate the transition to sustainable mining. These policies also call for faster integration of 5G, big data, the internet, and artificial intelligence to promote intelligent and green development of mining enterprises and improve resource utilization and production management efficiency. These favorable policies will further promote growth in the driverless mining solution industry in China.

01

Policy guidance accelerates large-scale application

In recent years, China has introduced multiple measures at central and local levels to promote smart mining, driverless technology, and low-carbon development, accelerating the deployment of driverless solutions in the mining industry and creating broad market opportunities for driverless mining solution providers.

At the national level, policy documents such as the "Guidelines for Coal Mine Intelligence Construction," "Notice on Supporting the Construction of a New Generation of Artificial Intelligence Demonstration Applications," and "Notice on Further Accelerating Coal Mine Intelligence Construction to Promote High-Quality Coal Development" require the application of driverless technology in mine transportation, encourage the promotion of driverless mine trucks, and improve safety and operational efficiency. The State Mine Safety Administration and the National Development and Reform Commission jointly issued the "Guiding Opinions on Further Promoting Intelligent Mine Construction and Facilitating Safe Mine Development" in April 2024, setting clear goals: by 2026, more than 30% of all coal mine working faces should adopt an intelligent system, with at least 80% operating normally, and the replacement rate of intelligent equipment or robots in coal and non-coal dangerous and heavy-duty positions should be no less than 30% and 20% respectively. In addition, in 2024, the Ministry of Natural Resources and six other ministries jointly issued the "Notice on Further Strengthening Green Mine Construction," encouraging the application of advanced green and low-carbon technologies to accelerate the transition to sustainable mining. These policies also call for faster integration of 5G, big data, the internet, and artificial intelligence to promote intelligent and green development of mining enterprises and improve resource utilization and production management efficiency. These favorable policies will further promote growth in the driverless mining solution industry in China.

At the same time, local governments also support mining enterprises by providing financial subsidies, industrial support, and demonstration projects. For example, major coal mine provinces such as Xinjiang and Inner Mongolia have taken the lead in deploying driverless mine truck demonstration areas, promoting large-scale application in the industry. The "Three-Year Action Plan for Coal Mine Intelligence Construction in Xinjiang Uyghur Autonomous Region (2023-2025)" requires the construction of different intelligent operation modes based on mining processes, including the use of driverless mine trucks to improve overall mine operation efficiency. The General Office of the Inner Mongolia Autonomous Region Government issued the "Notice on Further Strengthening Safety Management of Open-Pit Coal Mines in the Region," encouraging the application of advanced technologies such as driverless and slope radar monitoring in existing large-stock, well-managed, and well-equipped open-pit coal mines, and further improving safety levels through intelligent and digital transformation.

02

AI drives significant improvements in automation and productivity

AI enhances the perception, route planning, and decision-making capabilities of driverless mine trucks through deep learning and real-time data processing, fundamentally changing the operation mode of driverless mine trucks in complex and dynamic environments, reducing accident rates, minimizing human intervention, and enabling more intelligent deployment and maintenance. More importantly, AI-driven rapid learning and system iteration have become key breakthroughs. For example, MagnaTEC used a proprietary training engine developed from 100+ real mine high-frequency operation scenarios to reduce the deployment time for new mines from three months to three days.

03

Technical breakthroughs address long-standing industry challenges

04

Growth in mining output creates demand for driverless systems

05

Expansion from open-pit mines to diverse scenarios

06

Export of Chinese driverless mining technology overseas