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市场调查报告书
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自动驾驶晶片市场机会、成长动力、产业趋势分析及 2025 - 2034 年预测

Autonomous Driving Chips Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034
出版日期: | 出版商: Global Market Insights Inc. | 英文 230 Pages | 商品交期: 2-3个工作天内

价格
简介目录

2024 年全球自动驾驶晶片市场价值为 242.2 亿美元，预计到 2034 年将以 23% 的复合年增长率增长至 1910.7 亿美元。

自动驾驶晶片市场 - IMG1

自动驾驶晶片是专用处理器，用于实现智慧车辆功能，执行即时路径规划、环境感知、感测器资料融合和自主决策等关键功能。随着汽车製造商稳步迈向更高级别的自动化，从基础驾驶辅助到完全自动驾驶，对能够提供超低延迟和高可靠性的晶片的需求也日益增长。高级驾驶辅助系统 (ADAS) 的广泛采用，以及汽车行业向电动车的转型，正在扩大对具备可扩展性、高能源效率和高精度运算能力的高性能晶片的需求。加强道路安全的监管压力也促使汽车原始设备製造商 (OEM) 整合更智慧的电子架构。汽车製造商正在从传统的基于处理器的平台转向能够提供更佳电源管理和性能优化的晶片组。这种转变有助于提高设计灵活性，并允许在各种车型中以经济高效的方式部署自动驾驶技术，从而推动全球市场的整体发展势头。

市场范围
起始年份 2024
预测年份 2025-2034
起始值 242.2亿美元
预测值 1910.7亿美元
复合年增长率 23%

2024年，专用积体电路 (ASIC) 市场占据36%的市场份额，预计到2034年将以25%的复合年增长率成长。这些晶片经过高度优化，可处理特定任务，例如感测器融合、机器视觉和神经网路加速。其专用架构可提高运算效率、降低延迟并增强热稳定性，这些优势在紧凑尺寸、功耗优化和安全性至关重要的汽车环境中尤为突出。 ASIC 的设计充分考虑了特定的工作负载，这使其在精度和可靠性至关重要的自动驾驶领域尤其重要。

2024年，1级（驾驶辅助）细分市场占据45%的市场份额，预计2025年至2034年的复合年增长率将达到18.8%。儘管市场正朝着更高自动化水平发展，但1级凭藉其经济实惠、易于整合以及对成熟技术的依赖，仍占据主导地位。由于消费者对部分自动化的兴趣以及监管机构对安全性提升的日益重视，2级功能正日益受到青睐。然而，1级解决方案凭藉其成本效益和较低的复杂性，在大众市场汽车中仍然备受青睐。

北美自动驾驶晶片市场占35%的市场份额，2024年市场规模达85.4亿美元。该地区，尤其是美国，凭藉其先进的研发能力、有利的政策导向、成熟的半导体製造基础设施以及广泛的实际测试项目，成为自动驾驶晶片市场的主导力量。这种环境为自动驾驶晶片技术的创新和商业化创造了强劲动力，推动了其在乘用车、电动车和连网行动平台的快速应用。

全球自动驾驶晶片市场的主要参与者包括义法半导体、德州仪器、英特尔（Mobileye）、高通、英飞凌科技、NVIDIA、瑞萨电子、ADI公司和恩智浦半导体。为了巩固其在自动驾驶晶片市场的竞争优势，各公司正投资专为边缘AI处理、低延迟控制和即时感测器解读而建构的下一代晶片架构。与汽车OEM厂商、一级供应商和AI软体供应商的策略联盟，使硬体和自动驾驶堆迭能够更紧密地整合。研发支出用于提高晶片的可扩展性、降低能耗，并在更小的晶片尺寸内实现更高等级的自动化。

目录

第一章：方法论

  • 市场范围和定义
  • 研究设计
    • 研究方法
    • 资料收集方法
  • 资料探勘来源
    • 全球的
    • 地区/国家
  • 基础估算与计算
    • 基准年计算
    • 市场评估的主要趋势
  • 初步研究和验证
    • 主要来源
  • 预报
  • 研究假设和局限性

第 2 章：执行摘要

第三章：行业洞察

  • 产业生态系统分析
    • 供应商格局
    • 利润率分析
    • 成本结构
    • 每个阶段的增值
    • 影响价值链的因素
    • 中断
  • 产业衝击力
    • 成长动力
      • SAE 2+级和3级车辆的采用率不断上升
      • 人工智慧和边缘运算技术的快速发展
      • 汽车原始设备製造商和一级供应商增加投资
      • 政府支持和自动驾驶友善法规
      • 日益增长的安全问题和减少事故的倡议
      • 电动和软体定义汽车架构的扩展
    • 产业陷阱与挑战
      • 先进晶片的开发和製造成本高
      • 功能安全认证的复杂性（ASIL-D、ISO 26262）
    • 市场机会
      • 4/5级自动驾驶商用车队的出现
      • 亚太和中东地区的需求不断增长
      • 小晶片和模组化架构的兴起
      • 与5G和V2X通讯技术的集成
  • 成长潜力分析
  • 专利分析
  • 波特的分析
  • PESTEL分析
  • 成本分解分析
  • 技术和创新格局
    • 当前的技术趋势
      • 电脑视觉演算法的演变
      • 感测器融合技术趋势
      • 边缘运算的进步
      • 即时处理创新
    • 新兴技术
  • 监管格局
    • 全球监理框架概览
    • NHTSA 自动驾驶汽车指南
    • 欧洲型式认证要求
    • 中国国家标准（GB/T）
    • 新兴监管趋势
  • 价格趋势
    • 按地区
    • 按晶片
  • 生产统计
    • 生产中心
    • 消费中心
    • 汇出和汇入
  • 永续性和 ESG 影响分析
    • 绿色製造实践
    • 能源效率优化
    • 减少晶圆厂运作中的浪费
    • 可持续材料的使用
  • 投资与融资趋势分析
  • 品质和可靠性标准
    • ISO 26262 功能安全 (ASIL-D)
    • AEC-Q100 汽车认证
    • 网路安全标准（ISO 21434）
    • 人工智慧安全和验证要求
  • 数位转型的影响
    • 人工智慧驱动的设计自动化
    • 数位孪生实施
    • 基于云端的开发
    • 晶片开发中的 DevOps
  • 供应链弹性评估
    • 关键材料依赖性
    • 地理集中风险
    • 单点故障分析
    • 供应链多样化
    • 替代采购策略
    • 供应链透明度

第四章：竞争格局

  • 介绍
  • 公司市占率分析
    • 北美洲
    • 欧洲
    • 亚太地区
    • 拉丁美洲
    • 中东和非洲
  • 主要市场参与者的竞争分析
  • 竞争定位矩阵
  • 战略展望矩阵
  • 关键进展
    • 併购
    • 伙伴关係与合作
    • 新产品发布
    • 扩张计划和资金

第五章：市场估计与预测：按晶片，2021 - 2034

  • 主要趋势
  • 微控制器（MCU）
  • 图形处理器
  • FPGA
  • 专用积体电路 (ASIC)
  • 其他的

第六章：市场估计与预测：依自主水平，2021 - 2034 年

  • 主要趋势
  • 1级（驾驶辅助）
  • 2级（部分自动化）
  • 3级（有条件自动化）
  • 4级（高度自动化）
  • 5级（全自动）

第七章：市场估计与预测：依功能，2021 - 2034

  • 主要趋势
  • 感知晶片
  • 决策晶片
  • 控制晶片

第八章：市场估计与预测：依车型，2021 - 2034

  • 主要趋势
  • 乘客
  • 商业的

第九章：市场估计与预测：按地区，2021 - 2034

  • 主要趋势
  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 德国
    • 英国
    • 法国
    • 义大利
    • 西班牙
    • 北欧人
    • 俄罗斯
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 澳洲
    • 印尼
    • 菲律宾
    • 泰国
    • 韩国
    • 新加坡
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • 中东和非洲
    • 沙乌地阿拉伯
    • 南非
    • 阿联酋

第十章：公司简介

  • 全球参与者
    • Analog Devices
    • Infineon Technologies
    • Intel (Mobileye)
    • NVIDIA
    • NXP Semiconductors
    • ON Semiconductor
    • Qualcomm
    • Renesas Electronics
    • STMicroelectronics
    • Texas Instruments
  • 区域参与者
    • Ambarella
    • Black Sesame Technologies
    • Cambricon Technologies
    • Esperanto Technologies
    • Hailo Technologies
    • Horizon Robotics
    • Kalray
    • Kneron
  • 新兴参与者/颠覆者
    • AImotive
    • Blaize
    • BrainChip
    • Eta Compute
    • Flex Logix
    • GreenWaves Technologies
    • Recogni
    • Syntiant
简介目录
Product Code: 14794

The Global Autonomous Driving Chips Market was valued at USD 24.22 billion in 2024 and is estimated to grow at a CAGR of 23% to reach USD 191.07 billion by 2034.

Autonomous Driving Chips Market - IMG1

Autonomous driving chips are purpose-built processors that enable intelligent vehicle functionality, executing critical functions such as real-time path planning, environmental perception, sensor data fusion, and autonomous decision-making. As automakers steadily move toward higher levels of automation, from basic driver assistance to full autonomy, the need for chips that can deliver ultra-low latency and high reliability has intensified. The widespread adoption of advanced driver-assistance systems (ADAS), along with the industry's pivot to electric vehicles, is amplifying the demand for high-performance chips that offer scalability, energy efficiency, and precision computing. Regulatory pressure to enhance road safety is also encouraging automotive OEMs to integrate smarter electronic architectures. Automakers are transitioning away from traditional processor-based platforms in favor of chipsets that provide better power management and performance optimization. This shift supports improved design flexibility and allows cost-effective deployment of autonomous technologies across vehicle categories, driving the overall momentum of the global market.

Market Scope
Start Year2024
Forecast Year2025-2034
Start Value$24.22 Billion
Forecast Value$191.07 Billion
CAGR23%

In 2024, the application-specific integrated circuits (ASIC) segment held a 36% share and is forecast to grow at a CAGR of 25% through 2034. These chips are highly optimized to handle defined tasks, such as sensor fusion, machine vision, and neural network acceleration. Their dedicated architecture results in greater computational efficiency, reduced latency, and thermal stability, key benefits in automotive environments where compact size, power optimization, and safety are critical. ASICs are designed with specific workloads in mind, making them especially valuable in autonomous driving, where precision and reliability are non-negotiable.

The Level 1 (driver assistance) segment held a 45% share in 2024 and is estimated to grow at a CAGR of 18.8% from 2025 to 2034. While the market is trending toward higher levels of automation, Level 1 remains dominant due to its affordability, ease of integration, and reliance on mature technologies. Level 2 capabilities are growing in prominence, supported by consumer interest in partial automation and growing regulatory focus on safety enhancement. However, Level 1 solutions continue to be favored in mass-market vehicles due to their cost-effectiveness and lower complexity.

North America Autonomous Driving Chips Market held a 35% share and generated USD 8.54 billion in 2024. The region, particularly the United States, is a dominant force due to a blend of advanced R&D capabilities, favorable policy direction, mature semiconductor manufacturing infrastructure, and widespread deployment of real-world testing programs. This environment has created strong momentum for innovation and commercialization of autonomous chip technologies, driving rapid adoption in passenger cars, electric vehicles, and connected mobility platforms.

Key players in the Global Autonomous Driving Chips Market include STMicroelectronics, Texas Instruments, Intel (Mobileye), Qualcomm, Infineon Technologies, NVIDIA, Renesas Electronics, Analog Devices, and NXP Semiconductors. To solidify their competitive edge in the autonomous driving chips market, companies are investing in next-generation chip architectures purpose-built for edge AI processing, low-latency control, and real-time sensor interpretation. Strategic alliances with automotive OEMs, Tier-1 suppliers, and AI software vendors enable tighter integration of hardware and autonomous driving stacks. R&D spending is directed toward improving chip scalability, reducing energy consumption, and enabling higher-level automation in a smaller silicon footprint.

Table of Contents

Chapter 1 Methodology

  • 1.1 Market scope and definition
  • 1.2 Research design
    • 1.2.1 Research approach
    • 1.2.2 Data collection methods
  • 1.3 Data mining sources
    • 1.3.1 Global
    • 1.3.2 Regional/Country
  • 1.4 Base estimates and calculations
    • 1.4.1 Base year calculation
    • 1.4.2 Key trends for market estimation
  • 1.5 Primary research and validation
    • 1.5.1 Primary sources
  • 1.6 Forecast
  • 1.7 Research assumptions and limitations

Chapter 2 Executive Summary

  • 2.1 Industry 360° synopsis, 2021 - 2034
  • 2.2 Key market trends
    • 2.2.1 Regional
    • 2.2.2 Chip
    • 2.2.3 Autonomy level
    • 2.2.4 Function
    • 2.2.5 Vehicle
  • 2.3 TAM analysis, 2025-2034
  • 2.4 CXO perspectives: Strategic imperatives
    • 2.4.1 Executive decision points
    • 2.4.2 Critical success factors
  • 2.5 Future-outlook and strategic recommendations

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
    • 3.1.1 Supplier landscape
    • 3.1.2 Profit margin analysis
    • 3.1.3 Cost structure
    • 3.1.4 Value addition at each stage
    • 3.1.5 Factors affecting the value chain
    • 3.1.6 Disruptions
  • 3.2 Industry impact forces
    • 3.2.1 Growth drivers
      • 3.2.1.1 Rising adoption of sae level 2+ and level 3 vehicles
      • 3.2.1.2 Rapid advancements in AI and edge computing technologies
      • 3.2.1.3 Increased investments by automotive oems and tier-1 suppliers
      • 3.2.1.4 Government support and AV-friendly regulations
      • 3.2.1.5 Growing safety concerns and accident reduction initiatives
      • 3.2.1.6 Expansion of electric and software-defined vehicle architectures
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 High development and manufacturing costs of advanced chips
      • 3.2.2.2 Complexity of functional safety certification (ASIL-D, ISO 26262)
    • 3.2.3 Market opportunities
      • 3.2.3.1 Emergence of level 4/5 autonomous commercial fleets
      • 3.2.3.2 Growing demand in Asia Pacific and Middle East regions
      • 3.2.3.3 Rise of chiplet and modular architectures
      • 3.2.3.4 Integration with 5G and V2X communication technologies
  • 3.3 Growth potential analysis
  • 3.4 Patent analysis
  • 3.5 Porter’s analysis
  • 3.6 PESTEL analysis
  • 3.7 Cost breakdown analysis
  • 3.8 Technology and innovation landscape
    • 3.8.1 Current technological trends
      • 3.8.1.1 Computer vision algorithm evolution
      • 3.8.1.2 Sensor fusion technology trends
      • 3.8.1.3 Edge computing advancement
      • 3.8.1.4 Real-time processing innovations
    • 3.8.2 Emerging technologies
  • 3.9 Regulatory landscape
    • 3.9.1 Global regulatory framework overview
    • 3.9.2 NHTSA autonomous vehicle guidelines
    • 3.9.3 European type approval requirements
    • 3.9.4 China's national standards (GB/T)
    • 3.9.5 Emerging regulatory trends
  • 3.10 Price trends
    • 3.10.1 By region
    • 3.10.2 By chip
  • 3.11 Production statistics
    • 3.11.1 Production hubs
    • 3.11.2 Consumption hubs
    • 3.11.3 Export and import
  • 3.12 Sustainability & ESG impact analysis
    • 3.12.1 Green manufacturing practices
    • 3.12.2 Energy efficiency optimization
    • 3.12.3 Waste reduction in fab operations
    • 3.12.4 Sustainable material usage
  • 3.13 Investment & funding trends analysis
  • 3.14 Quality and reliability standards
    • 3.14.1 ISO 26262 functional safety (ASIL-D)
    • 3.14.2 AEC-Q100 automotive qualification
    • 3.14.3 Cybersecurity standards (ISO 21434)
    • 3.14.4 AI safety and validation requirements
  • 3.15 Digital transformation impact
    • 3.15.1 AI-driven design automation
    • 3.15.2 Digital twin implementation
    • 3.15.3 Cloud-based development
    • 3.15.4 DevOps in chip development
  • 3.16 Supply chain resilience assessment
    • 3.16.1 Critical material dependencies
    • 3.16.2 Geographic concentration risks
    • 3.16.3 Single point of failure analysis
    • 3.16.4 Supply chain diversification
    • 3.16.5 Alternative sourcing strategies
    • 3.16.6 Supply chain transparency

Chapter 4 Competitive Landscape, 2024

  • 4.1 Introduction
  • 4.2 Company market share analysis
    • 4.2.1 North America
    • 4.2.2 Europe
    • 4.2.3 Asia Pacific
    • 4.2.4 Latin America
    • 4.2.5 Middle East & Africa
  • 4.3 Competitive analysis of major market players
  • 4.4 Competitive positioning matrix
  • 4.5 Strategic outlook matrix
  • 4.6 Key developments
    • 4.6.1 Mergers & acquisitions
    • 4.6.2 Partnerships & collaborations
    • 4.6.3 New product launches
    • 4.6.4 Expansion plans and funding

Chapter 5 Market Estimates & Forecast, By Chip, 2021 - 2034 (USD Bn, Million Units)

  • 5.1 Key trends
  • 5.2 Microcontrollers (MCUs)
  • 5.3 GPU
  • 5.4 FPGA
  • 5.5 ASIC
  • 5.6 Others

Chapter 6 Market Estimates & Forecast, By Autonomy Level, 2021 - 2034 (USD Bn, Million Units)

  • 6.1 Key trends
  • 6.2 Level 1 (driver assistance)
  • 6.3 Level 2 (partial automation)
  • 6.4 Level 3 (conditional automation)
  • 6.5 Level 4 (high automation)
  • 6.6 Level 5 (full automation)

Chapter 7 Market Estimates & Forecast, By Function, 2021 - 2034 (USD Bn, Million Units)

  • 7.1 Key trends
  • 7.2 Perception chips
  • 7.3 Decision-making chips
  • 7.4 Control chips

Chapter 8 Market Estimates & Forecast, By Vehicle, 2021 - 2034 (USD Bn, Million Units)

  • 8.1 Key trends
  • 8.2 Passenger
  • 8.3 Commercial

Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2034 (USD Bn, Million Units)

  • 9.1 Key trends
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 France
    • 9.3.4 Italy
    • 9.3.5 Spain
    • 9.3.6 Nordics
    • 9.3.7 Russia
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 India
    • 9.4.3 Japan
    • 9.4.4 Australia
    • 9.4.5 Indonesia
    • 9.4.6 Philippines
    • 9.4.7 Thailand
    • 9.4.8 South Korea
    • 9.4.9 Singapore
  • 9.5 Latin America
    • 9.5.1 Brazil
    • 9.5.2 Mexico
    • 9.5.3 Argentina
  • 9.6 Middle East and Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 South Africa
    • 9.6.3 UAE

Chapter 10 Company Profiles

  • 10.1 Global Players
    • 10.1.1 Analog Devices
    • 10.1.2 Infineon Technologies
    • 10.1.3 Intel (Mobileye)
    • 10.1.4 NVIDIA
    • 10.1.5 NXP Semiconductors
    • 10.1.6 ON Semiconductor
    • 10.1.7 Qualcomm
    • 10.1.8 Renesas Electronics
    • 10.1.9 STMicroelectronics
    • 10.1.10 Texas Instruments
  • 10.2 Regional Players
    • 10.2.1 Ambarella
    • 10.2.2 Black Sesame Technologies
    • 10.2.3 Cambricon Technologies
    • 10.2.4 Esperanto Technologies
    • 10.2.5 Hailo Technologies
    • 10.2.6 Horizon Robotics
    • 10.2.7 Kalray
    • 10.2.8 Kneron
  • 10.3 Emerging Players / Disruptors
    • 10.3.1 AImotive
    • 10.3.2 Blaize
    • 10.3.3 BrainChip
    • 10.3.4 Eta Compute
    • 10.3.5 Flex Logix
    • 10.3.6 GreenWaves Technologies
    • 10.3.7 Recogni
    • 10.3.8 Syntiant