自动驾驶 AI 晶片市场报告：2031 年趋势、预测与竞争分析

全球自动驾驶AI晶片市场前景广阔，乘用车、商用车市场都存在机会。预计全球自动驾驶 AI 晶片市场在 2025 年至 2031 年期间的复合年增长率将达到 22.5%。该市场的主要驱动力是对自动驾驶汽车不断增长的需求、鼓励其开发和部署的优惠政策以及 AI 演算法的进步。

• Lucintel 预计，在预测期内，GPU 将成为显示卡类型中成长最快的。
• 从应用角度来看，乘用车仍然是最大的细分市场。
• 根据地区来看，预计亚太地区将在预测期内实现最高成长。

自动驾驶AI晶片市场的策略性成长机会

在技​​术进步和不断变化的市场需求的推动下，自动驾驶人工智慧晶片市场在不同应用领域呈现出各种成长机会。关键机会反映了该行业的创新和扩张潜力。

• 增强型汽车安全系统：用于先进安全系统的人工智慧晶片的开发将提供巨大的成长机会。这些晶片支援防撞、车道维持辅助和自动紧急煞车等功能，提高了车辆的整体安全性和驾驶体验。
• 自动驾驶汽车导航：AI晶片对于自动驾驶汽车导航至关重要，可实现自动驾驶汽车的即时处理和决策。对更精确、更可靠的导航系统的需求正在推动该应用的成长，为感测器整合和资料处理的创新提供了机会。
• 电动车整合：将AI晶片整合到电动车中将改善电池管理、能源效率和整体车辆性能，创造成长潜力。致力于使电动车更智慧、更有效率，这与永续交通解决方案的大趋势一致。
• 车队管理解决方案：AI晶片越来越多地用于车队管理解决方案，以优化车辆营运、维护和路线规划。随着企业寻求透过先进的人工智慧技术来提高效率并降低营运成本，该应用程式带来了成长机会。
• 车载资讯娱乐系统：AI晶片整合到车载资讯娱乐系统中，将透过语音辨识、个人化建议、无缝连接等功能提升使用者体验。随着消费者对高级资讯娱乐功能的需求不断增加，该应用带来了成长机会。

这些策略性成长机会正在推动自动驾驶AI晶片市场的创新和扩张。透过解决广泛的应用，公司可以充分利用新趋势并满足汽车行业不断变化的需求。

自动驾驶AI晶片市场的驱动力与挑战

自动驾驶 AI 晶片市场受到各种驱动因素​​和挑战的影响，包括技术进步、经济因素和监管发展。这些因素将在塑造市场动态和未来成长方面发挥关键作用。

推动自动驾驶AI晶片市场发展的因素有：

• 技术进步：人工智慧和半导体技术的快速进步正在推动自动驾驶人工智慧晶片市场的发展。晶片设计、处理能力和整合能力的创新将增强自动驾驶系统的性能和功能，从而促进市场成长。
• 自动驾驶汽车的需求不断增加：消费者对自动驾驶汽车的需求不断增加是市场的主要驱动力。随着越来越多的汽车製造商投资自动驾驶技术，对能够处理复杂驾驶场景的先进人工智慧晶片的需求正在推动市场扩张。
• 自动驾驶的监管支援：各地区的支持性法规环境将促进自动驾驶技术的发展和应用。促进自动驾驶汽车测试和部署的法规将有助于AI晶片市场的成长。
• 研发投入：科技公司和汽车製造商对研发的大量投入将加速人工智慧晶片技术的进步。这些投资将带来更多创新和有效的解决方案，推动市场成长。
• 全球竞争与合作：全球科技公司和汽车製造商之间日益激烈的竞争与合作将推动人工智慧晶片技术的创新。伙伴关係和合资企业将推动进步并加速先进自动驾驶系统的发展。

自动驾驶AI晶片市场面临的挑战有：

• 开发成本高：市场面临的挑战之一是先进AI晶片的开发成本高。需要在研究、开发和製造方面进行大量投资，这可能会成为一些公司的进入壁垒，并影响市场的整体成长。
• 监管和安全挑战：满足复杂的监管要求并确保自动驾驶系统的安全合规性将对市场构成挑战。在推进技术的同时满足这些标准可能是一个充满挑战且耗费大量资源的过程。
• 供应链中断：供应链问题，包括关键材料和零件的短缺，可能会影响人工智慧晶片的生产和供应。这种中断可能会影响市场动态并减缓新技术的开发和部署。

这些驱动因素和挑战的相互作用将塑造自动驾驶人工智慧晶片市场，影响其成长轨迹和市场动态。解决这些因素对于公司抓住机会、克服不断发展的自动驾驶技术中的障碍至关重要。

目录

第一章执行摘要

第二章 全球自动驾驶AI晶片市场：市场动态

• 简介、背景和分类
• 供应链
• 产业驱动力与挑战

第三章 2019年至2031年市场趋势及预测分析

• 宏观经济趋势（2019-2024）及预测（2025-2031）
• 全球自动驾驶AI晶片市场趋势（2019-2024）及预测（2025-2031）
• 全球自动驾驶AI晶片市场（按类型）
  • GPU
  • DSP
  • NPU
  • 其他的
• 全球自动驾驶AI晶片市场（按应用）
  • 搭乘用车
  • 商用车

第四章2019年至2031年区域市场趋势与预测分析

• 全球自动驾驶AI晶片市场区域分布
• 北美自动驾驶AI晶片市场
• 欧洲自动驾驶AI晶片市场
• 亚太地区自动驾驶AI晶片市场
• 其他地区自动驾驶AI晶片市场

第五章 竞争分析

• 产品系列分析
• 营运整合
• 波特五力分析

第六章 成长机会与策略分析

• 成长机会分析
  • 全球自动驾驶AI晶片市场成长机会（按类型）
  • 全球自动驾驶 AI 晶片市场成长机会（按应用）
  • 全球自动驾驶 AI 晶片市场成长机会（按地区）
• 全球自动驾驶AI晶片市场新趋势
• 战略分析
  • 新产品开发
  • 全球自动驾驶AI晶片市场产能扩张
  • 全球自动驾驶AI晶片市场併购与合资状况
  • 认证和许可

第七章主要企业简介

• Intel
• Advanced Micro Devices
• Qualcomm
• Black Sesame Technologies
• Huawei
• Hailo
• Nvidia

The future of the global auto driving AI chip market looks promising with opportunities in the passenger vehicle and commercial vehicle markets. The global auto driving AI chip market is expected to grow with a CAGR of 22.5% from 2025 to 2031. The major drivers for this market are the rising demand for autonomous vehicles, favorable policies encouraging development and deployment, and advancements in AI algorithms.

• Lucintel forecasts that, within the type category, GPU is expected to witness the highest growth over the forecast period.
• Within the application category, passenger vehicles will remain the largest segment.
• In terms of regions, APAC is expected to witness the highest growth over the forecast period.

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Emerging Trends in the Auto Driving AI Chip Market

Emerging trends in the auto driving AI chip market are shaping the future of vehicle automation with advancements in technology and evolving consumer demands. These trends reflect the shift toward more sophisticated, efficient, and integrated solutions for autonomous driving.

• Advanced Neural Network Architectures: Companies are developing chips with advanced neural network architectures to improve real-time processing and decision-making. These architectures enable better handling of complex driving environments and scenarios, enhancing safety and efficiency. As neural networks become more sophisticated, AI chips can process more data at higher speeds, driving advancements in autonomous driving capabilities.
• Integration with 5G Technology: The integration of AI chips with 5G technology is becoming a key trend, facilitating faster data transmission and improved vehicle-to-everything (V2X) communication. This allows more reliable and responsive autonomous driving systems, as real-time data exchange between vehicles and infrastructure enhances situational awareness and decision-making.
• Focus on Energy Efficiency: Energy efficiency is gaining importance as companies strive to reduce the power consumption of AI chips. Developing chips that balance performance with lower energy consumption helps extend the range of electric vehicles and reduces overall operational costs. This trend reflects a broader push toward sustainability in automotive technology.
• Enhanced Edge Computing Capabilities: AI chips are increasingly designed with enhanced edge computing capabilities, allowing more processing to be done within the vehicle itself rather than relying on cloud-based systems. This reduces latency and improves the responsiveness of autonomous driving systems, making real-time decision-making more efficient.
• Collaborative Development Ecosystems: There is a growing trend toward collaborative development ecosystems, where automotive manufacturers and tech companies work together to advance AI chip technology. These collaborations leverage diverse expertise and resources to accelerate innovation and bring more integrated solutions to the market.

These trends are reshaping the auto driving AI chip market by driving technological innovation, enhancing system capabilities, and improving overall efficiency. As companies continue to develop and integrate advanced AI chips, the market is evolving toward more sophisticated, responsive, and energy-efficient solutions for autonomous vehicles.

Recent Developments in the Auto Driving AI Chip Market

Recent developments in the auto driving AI chip market reflect significant advancements in technology, strategic investments, and competitive dynamics. Key developments highlight the progress made in AI chip capabilities and their impact on autonomous driving systems.

• NVIDIA Orin Platform: NVIDIA's Orin platform represents a major leap in AI chip technology with its high-performance processing capabilities. The platform supports more complex neural networks and real-time decision-making, making it a cornerstone for advanced autonomous driving systems and pushing the boundaries of what AI chips can achieve.
• Baidu Apollo Project: Baidu's Apollo project continues to make strides in AI chip development, focusing on enhancing the capabilities of autonomous vehicles. The integration of Apollo chips into various vehicle models demonstrates significant progress in improving safety, navigation, and overall driving performance.
• Intel Mobileye Technology: Intel's Mobileye division is advancing its AI chip technology with a focus on enhancing perception and decision-making capabilities in autonomous vehicles. Mobileye chips are being integrated into numerous vehicle models, showcasing their impact on improving autonomous driving systems and safety features.
• Huawei Kirin Chips: Huawei's Kirin chips are making waves in the auto driving AI chip market with their advanced processing power and efficiency. The chips are designed to handle complex driving scenarios and support autonomous driving features, contributing to the advancement of vehicle automation technologies.
• Bosch AI Chip Developments: Bosch is advancing its AI chip technology with a focus on enhancing vehicle safety and automation. The company's developments include improvements in real-time processing and integration with existing automotive systems, reflecting Germany's commitment to leading in automotive technology.

These developments are driving significant progress in the auto driving AI chip market, pushing the boundaries of technology and enhancing the capabilities of autonomous driving systems. As these innovations continue to evolve, they are setting new standards for performance, safety, and integration in the automotive industry.

Strategic Growth Opportunities for Auto Driving AI Chip Market

The auto driving AI chip market presents various growth opportunities across different applications, driven by technological advancements and evolving market needs. Key opportunities reflect the potential for innovation and expansion in the sector.

• Enhanced Vehicle Safety Systems: The development of AI chips for advanced safety systems presents significant growth opportunities. These chips enable features such as collision avoidance, lane-keeping assistance, and automatic emergency braking, enhancing overall vehicle safety and the driving experience.
• Autonomous Vehicle Navigation: AI chips are crucial for autonomous vehicle navigation, enabling real-time processing and decision-making for self-driving cars. The demand for more precise and reliable navigation systems is driving growth in this application, with opportunities for innovation in sensor integration and data processing.
• Electric Vehicle Integration: Integrating AI chips into electric vehicles offers growth potential by improving battery management, energy efficiency, and overall vehicle performance. The focus on making EVs smarter and more efficient aligns with the broader trend toward sustainable transportation solutions.
• Fleet Management Solutions: AI chips are increasingly being used in fleet management solutions to optimize vehicle operations, maintenance, and route planning. This application offers growth opportunities as companies seek to improve efficiency and reduce operational costs through advanced AI technology.
• In-Car Infotainment Systems: The integration of AI chips into in-car infotainment systems enhances user experience with features such as voice recognition, personalized recommendations, and seamless connectivity. This application presents opportunities for growth as consumer demand for advanced infotainment features continues to rise.

These strategic growth opportunities are driving innovation and expansion in the auto driving AI chip market. By addressing various applications, companies are positioning themselves to capitalize on emerging trends and meet the evolving needs of the automotive industry.

Auto Driving AI Chip Market Driver and Challenges

The auto driving AI chip market is influenced by various drivers and challenges, including technological advancements, economic factors, and regulatory developments. These elements play a crucial role in shaping market dynamics and future growth.

The factors responsible for driving the auto driving AI chip market include:

• Technological Advancements: Rapid advancements in AI and semiconductor technologies are driving the auto driving AI chip market. Innovations in chip design, processing power, and integration capabilities enhance the performance and functionality of autonomous driving systems, leading to increased market growth.
• Increasing Demand for Autonomous Vehicles: Growing consumer demand for autonomous vehicles is a major driver for the market. As more automakers invest in autonomous driving technology, the need for advanced AI chips that can handle complex driving scenarios drives market expansion.
• Regulatory Support for Autonomous Driving: Supportive regulatory environments in various regions facilitate the development and adoption of autonomous driving technologies. Regulations that promote the testing and deployment of self-driving vehicles contribute to the growth of the AI chip market.
• Investment in Research and Development: Significant investments in research and development by tech companies and automotive manufacturers accelerate advancements in AI chip technology. These investments lead to more innovative and effective solutions, driving market growth.
• Global Competition and Collaboration: Increased competition and collaboration among global tech companies and automotive manufacturers drive innovation in AI chip technology. Partnerships and joint ventures foster advancements and accelerate the development of advanced autonomous driving systems.

Challenges in the auto driving AI chip market are:

• High Development Costs: One of the challenges facing the market is the high cost of developing advanced AI chips. The significant investment required for research, development, and manufacturing can be a barrier to entry for some companies and impact overall market growth.
• Regulatory and Safety Challenges: Navigating complex regulatory requirements and ensuring safety compliance for autonomous driving systems pose challenges for the market. Meeting these standards while advancing technology can be a difficult and resource-intensive process.
• Supply Chain Disruptions: Supply chain issues, including shortages of key materials and components, can impact the production and availability of AI chips. These disruptions can affect market dynamics and delay the development and deployment of new technologies.

The interplay between these drivers and challenges shapes the auto driving AI chip market, influencing growth trajectories and market dynamics. Addressing these factors is crucial for companies to capitalize on opportunities and overcome obstacles in the evolving landscape of autonomous driving technology.

List of Auto Driving AI Chip Companies

Companies in the market compete based on product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies auto driving AI chip companies cater to increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the auto driving AI chip companies profiled in this report include-

• Intel
• Advanced Micro Devices
• Qualcomm
• Black Sesame Technologies
• Huawei
• Hailo
• Nvidia

Auto Driving AI Chip by Segment

The study includes a forecast for the global auto driving AI chip market by type, application, and region.

Auto Driving AI Chip Market by Type [Analysis by Value from 2019 to 2031]:

• GPU
• DSP
• NPU
• Others

Auto Driving AI Chip Market by Application [Analysis by Value from 2019 to 2031]:

• Passenger Vehicle
• Commercial Vehicle

Auto Driving AI Chip Market by Region [Analysis by Value from 2019 to 2031]:

• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the Auto Driving AI Chip Market

Recent developments in the auto driving AI chip market reflect rapid advancements driven by technological innovation, regulatory changes, and market demand for enhanced vehicle automation. Key players are pushing boundaries in AI chip capabilities, focusing on improving performance, efficiency, and safety in autonomous driving systems. Regional developments in the United States, China, Germany, India, and Japan highlight varying priorities and strategies in this competitive landscape.

• United States: The U.S. continues to lead in AI chip innovation, with major tech firms like NVIDIA and Intel advancing their autonomous driving solutions. NVIDIA's Orin platform and Intel's Mobileye have made strides in processing power and integration, pushing the envelope for higher levels of automation and improved safety features. Significant investments in AI chip research and development bolster the U.S. market's competitive edge.
• China: China has emerged as a formidable player in the auto driving AI chip market, with companies like Baidu and Huawei making significant strides. Baidu's Apollo project and Huawei's Kirin chip series drive advancements in AI capabilities and integration with autonomous driving technologies. The Chinese government's support for AI research and development accelerates the growth of domestic tech companies in this sector.
• Germany: Germany, a leader in automotive engineering, focuses on integrating AI chips into high-performance vehicles. Companies like Bosch and Continental advance their AI chip technologies to enhance vehicle safety and autonomous capabilities. The emphasis is on developing chips that can handle complex driving environments, aligning with Germany's strong automotive industry and commitment to innovation.
• India: India is emerging as a key player in the auto driving AI chip market, driven by a growing tech ecosystem and increasing investment in research and development. Companies like Tata Elxsi and global players expanding into India contribute to advancements in AI chip technology. The focus is on making cost-effective, efficient solutions suitable for diverse driving conditions.
• Japan: Japan is known for its advanced automotive technology, and recent developments include significant investments in AI chip technology by companies like Toyota and Sony. These advancements focus on improving real-time processing and decision-making capabilities for autonomous vehicles. Japan's emphasis on integration with existing automotive systems and collaboration with international tech firms drives innovation in the market.

Features of the Global Auto Driving AI Chip Market

Market Size Estimates: Auto driving AI chip market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: Auto driving AI chip market size by type, application, and region in terms of value ($B).

Regional Analysis: Auto driving AI chip market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the auto driving AI chip market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the auto driving AI chip market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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This report answers following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the auto driving AI chip market by type (GPU, DSP, NPU, and others), application (passenger vehicle and commercial vehicle), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
• Q.2. Which segments will grow at a faster pace and why?
• Q.3. Which region will grow at a faster pace and why?
• Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
• Q.5. What are the business risks and competitive threats in this market?
• Q.6. What are the emerging trends in this market and the reasons behind them?
• Q.7. What are some of the changing demands of customers in the market?
• Q.8. What are the new developments in the market? Which companies are leading these developments?
• Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
• Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
• Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global Auto Driving AI Chip Market : Market Dynamics

• 2.1: Introduction, Background, and Classifications
• 2.2: Supply Chain
• 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

• 3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
• 3.2. Global Auto Driving AI Chip Market Trends (2019-2024) and Forecast (2025-2031)
• 3.3: Global Auto Driving AI Chip Market by Type
  • 3.3.1: GPU
  • 3.3.2: DSP
  • 3.3.3: NPU
  • 3.3.4: Others
• 3.4: Global Auto Driving AI Chip Market by Application
  • 3.4.1: Passenger Vehicle
  • 3.4.2: Commercial Vehicle

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

• 4.1: Global Auto Driving AI Chip Market by Region
• 4.2: North American Auto Driving AI Chip Market
  • 4.2.1: North American Market by Type: GPU, DSP, NPU, and Others
  • 4.2.2: North American Market by Application: Passenger Vehicle and Commercial Vehicle
• 4.3: European Auto Driving AI Chip Market
  • 4.3.1: European Market by Type: GPU, DSP, NPU, and Others
  • 4.3.2: European Market by Application: Passenger Vehicle and Commercial Vehicle
• 4.4: APAC Auto Driving AI Chip Market
  • 4.4.1: APAC Market by Type: GPU, DSP, NPU, and Others
  • 4.4.2: APAC Market by Application: Passenger Vehicle and Commercial Vehicle
• 4.5: ROW Auto Driving AI Chip Market
  • 4.5.1: ROW Market by Type: GPU, DSP, NPU, and Others
  • 4.5.2: ROW Market by Application: Passenger Vehicle and Commercial Vehicle

5. Competitor Analysis

• 5.1: Product Portfolio Analysis
• 5.2: Operational Integration
• 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

• 6.1: Growth Opportunity Analysis
  • 6.1.1: Growth Opportunities for the Global Auto Driving AI Chip Market by Type
  • 6.1.2: Growth Opportunities for the Global Auto Driving AI Chip Market by Application
  • 6.1.3: Growth Opportunities for the Global Auto Driving AI Chip Market by Region
• 6.2: Emerging Trends in the Global Auto Driving AI Chip Market
• 6.3: Strategic Analysis
  • 6.3.1: New Product Development
  • 6.3.2: Capacity Expansion of the Global Auto Driving AI Chip Market
  • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global Auto Driving AI Chip Market
  • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

• 7.1: Intel
• 7.2: Advanced Micro Devices
• 7.3: Qualcomm
• 7.4: Black Sesame Technologies
• 7.5: Huawei
• 7.6: Hailo
• 7.7: Nvidia