PUBLISHER: QYResearch | PRODUCT CODE: 1866699
PUBLISHER: QYResearch | PRODUCT CODE: 1866699
The global market for Mining Unmanned Driving was estimated to be worth US$ 1182 million in 2024 and is forecast to a readjusted size of US$ 2595 million by 2031 with a CAGR of 13.0% during the forecast period 2025-2031.
As a vital foundational industry crucial to China's economic lifeline and energy security, the mining industry must embrace intelligent development, driving it towards safety, efficiency, green development, and economic efficiency. Unmanned mining vehicle technology plays a crucial role in intelligent mining strategies. Smart mines integrate the Internet of Things (IoT), cloud computing, big data, artificial intelligence (AI), automated control, the Industrial Internet, and robotic equipment with modern mining development technologies to create a complete intelligent system with comprehensive mine perception, real-time connectivity, analytical decision-making, autonomous learning, dynamic prediction, and collaborative control, enabling intelligent operation throughout the entire process. Mines are a core deployment scenario for autonomous driving, and autonomous mining, as a subsystem of smart mines, plays a crucial role. This report focuses on autonomous mining systems and solutions.
The main drivers of the autonomous mining market include the following:
1. Safety Demand and Rising Labor Costs
Frequent Safety Accidents: Mining environments are complex, posing safety hazards such as roof collapse and rock spalling. For example, a mine accident in Xingan County, Jiangxi Province in 2023 resulted in four deaths, highlighting the high risks of manual operations.
High Labor Costs: Labor costs account for a significant proportion of the mining industry, and recruitment is difficult. Autonomous driving can reduce the number of underground workers. For example, Huainan Mining has saved 3 million yuan in labor costs annually after implementing autonomous assisted transport robots.
Policy-Driven Safety Upgrades: The government has implemented policies such as the "Special Management Measures for Central Budget Investment in Coal Mine Safety Reform," mandating that mining companies improve safety standards and promoting the adoption of automation technology.
2. Efficiency Improvement and Operational Optimization
24-Hour Continuous Operation: Autonomous driving systems (such as EasyControl Intelligent Driving Unmanned Electric Vehicles) enable uninterrupted transportation around the clock, increasing daily effective operating hours to 11 hours, significantly higher than manual operations.
Improved Transportation Efficiency: Intelligent scheduling optimizes routes, reducing empty loads and trip times. For example, the loading and unloading times of unmanned trucks at the Heidaigou open-pit coal mine have been reduced by 50 and 60 seconds, respectively, increasing overall operational efficiency by 10%.
Improved Resource Utilization: Automation technology is enabling refined mining operations in mines. For example, optimizing blasting parameters has increased the ore fragmentation rate to 90%, reducing energy consumption in subsequent crushing.
3. Policy Support and Intelligent Transformation Trends
Central Government Subsidies: The National Development and Reform Commission provides investment subsidies of up to 25% for eligible coal mine safety renovation projects, capped at 30 million yuan, directly reducing the cost of intelligent transformation for enterprises.
Standard System Construction: The National Energy Administration has issued the "Guidelines for the Construction of an Intelligent Coal Mine Standard System," clearly stating that a complete standard system will be established by 2025 to provide guidelines for the implementation of the technology.
Encouraging Private Enterprise Participation: Shanxi Province has introduced policies to support private enterprises in participating in intelligent coal mine development, conducting research and development and application in areas such as information technology and intelligent equipment, and promoting diversified market competition.
Driven by safety pressures, efficiency demands, and favorable policies, the autonomous driving market in mines is accelerating its transition from pilot projects to large-scale applications. The market is expected to reach tens of billions of yuan in the next five years.
This report aims to provide a comprehensive presentation of the global market for Mining Unmanned Driving, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Mining Unmanned Driving by region & country, by Type, and by Application.
The Mining Unmanned Driving market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Mining Unmanned Driving.
Market Segmentation
By Company
Segment by Type
Segment by Application
By Region
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Mining Unmanned Driving company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Revenue of Mining Unmanned Driving in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Mining Unmanned Driving in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.