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市場調查報告書
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1679683

自動駕駛 AI 晶片市場報告:2031 年趨勢、預測與競爭分析

Auto Driving AI Chip Market Report: Trends, Forecast and Competitive Analysis to 2031

出版日期: | 出版商: Lucintel | 英文 150 Pages | 商品交期: 3個工作天內

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簡介目錄

全球自動駕駛AI晶片市場前景廣闊,乘用車、商用車市場都存在機會。預計全球自動駕駛 AI 晶片市場在 2025 年至 2031 年期間的複合年成長率將達到 22.5%。該市場的主要驅動力是對自動駕駛汽車不斷成長的需求、鼓勵其開發和部署的優惠政策以及 AI 演算法的進步。

  • Lucintel 預計,在預測期內,GPU 將成為顯示卡類型中成長最快的。
  • 從應用角度來看,乘用車仍然是最大的細分市場。
  • 根據地區來看,預計亞太地區將在預測期內實現最高成長。

自動駕駛AI晶片市場的策略性成長機會

在技​​術進步和不斷變化的市場需求的推動下,自動駕駛人工智慧晶片市場在不同應用領域呈現出各種成長機會。關鍵機會反映了該行業的創新和擴張潛力。

  • 增強型汽車安全系統:用於先進安全系統的人工智慧晶片的開發將提供巨大的成長機會。這些晶片支援防撞、車道維持輔助和自動緊急煞車等功能,提高了車輛的整體安全性和駕駛體驗。
  • 自動駕駛汽車導航:AI晶片對於自動駕駛汽車導航至關重要,可實現自動駕駛汽車的即時處理和決策。對更精確、更可靠的導航系統的需求正在推動該應用的成長,為感測器整合和資料處理的創新提供了機會。
  • 電動車整合:將AI晶片整合到電動車中將改善電池管理、能源效率和整體車輛性能,創造成長潛力。致力於使電動車更智慧、更有效率,這與永續交通解決方案的大趨勢一致。
  • 車隊管理解決方案:AI晶片擴大用於車隊管理解決方案,以最佳化車輛營運、維護和路線規劃。隨著企業尋求透過先進的人工智慧技術來提高效率並降低營運成本,該應用程式帶來了成長機會。
  • 車載資訊娛樂系統:AI晶片整合到車載資訊娛樂系統中,將透過語音辨識、個人化建議、無縫連接等功能提升使用者體驗。隨著消費者對高級資訊娛樂功能的需求不斷增加,該應用帶來了成長機會。

這些策略性成長機會正在推動自動駕駛AI晶片市場的創新和擴張。透過解決廣泛的應用,公司可以充分利用新趨勢並滿足汽車行業不斷變化的需求。

自動駕駛AI晶片市場的驅動力與挑戰

自動駕駛 AI 晶片市場受到各種促進因素​​和挑戰的影響,包括技術進步、經濟因素和監管發展。這些因素將在塑造市場動態和未來成長方面發揮關鍵作用。

推動自動駕駛AI晶片市場發展的因素有:

  • 技術進步:人工智慧和半導體技術的快速進步正在推動自動駕駛人工智慧晶片市場的發展。晶片設計、處理能力和整合能力的創新將增強自動駕駛系統的性能和功能,從而促進市場成長。
  • 自動駕駛汽車的需求不斷增加:消費者對自動駕駛汽車的需求不斷增加是市場的主要驅動力。隨著越來越多的汽車製造商投資自動駕駛技術,對能夠處理複雜駕駛場景的先進人工智慧晶片的需求正在推動市場擴張。
  • 自動駕駛的監管支援:各地區的支持性法規環境將促進自動駕駛技術的發展和應用。促進自動駕駛汽車測試和部署的法規將有助於AI晶片市場的成長。
  • 研發投入:科技公司和汽車製造商對研發的大量投入將加速人工智慧晶片技術的進步。這些投資將帶來更多創新和有效的解決方案,推動市場成長。
  • 全球競爭與合作:全球科技公司和汽車製造商之間日益激烈的競爭與合作將推動人工智慧晶片技術的創新。夥伴關係和合資企業將推動進步並加速先進自動駕駛系統的發展。

自動駕駛AI晶片市場面臨的挑戰有:

  • 開發成本高:市場面臨的挑戰之一是先進AI晶片的開發成本高。需要在研究、開發和製造方面進行大量投資,這可能會成為一些公司的進入壁壘,並影響市場的整體成長。
  • 監管和安全挑戰:滿足複雜的監管要求並確保自動駕駛系統的安全合規性將對市場構成挑戰。在推進技術的同時滿足這些標準可能是一個充滿挑戰且耗費大量資源的過程。
  • 供應鏈中斷:供應鏈問題,包括關鍵材料和零件的短缺,可能會影響人工智慧晶片的生產和供應。這種中斷可能會影響市場動態並減緩新技術的開發和部署。

這些促進因素和挑戰的相互作用將塑造自動駕駛人工智慧晶片市場,影響其成長軌跡和市場動態。解決這些因素對於公司抓住機會、克服不斷發展的自動駕駛技術中的障礙至關重要。

目錄

第1章執行摘要

第2章 全球自動駕駛AI晶片市場:市場動態

  • 簡介、背景和分類
  • 供應鏈
  • 產業驅動力與挑戰

第3章 2019年至2031年市場趨勢及預測分析

  • 宏觀經濟趨勢(2019-2024)及預測(2025-2031)
  • 全球自動駕駛AI晶片市場趨勢(2019-2024)及預測(2025-2031)
  • 全球自動駕駛AI晶片市場(按類型)
    • GPU
    • DSP
    • NPU
    • 其他
  • 全球自動駕駛AI晶片市場(按應用)
    • 搭乘用車
    • 商用車

第4章2019年至2031年區域市場趨勢與預測分析

  • 全球自動駕駛AI晶片市場區域分佈
  • 北美自動駕駛AI晶片市場
  • 歐洲自動駕駛AI晶片市場
  • 亞太地區自動駕駛AI晶片市場
  • 其他地區自動駕駛AI晶片市場

第5章 競爭分析

  • 產品系列分析
  • 營運整合
  • 波特五力分析

第6章 成長機會與策略分析

  • 成長機會分析
    • 全球自動駕駛AI晶片市場成長機會(按類型)
    • 全球自動駕駛 AI 晶片市場成長機會(按應用)
    • 全球自動駕駛 AI 晶片市場成長機會(按地區)
  • 全球自動駕駛AI晶片市場新趨勢
  • 戰略分析
    • 新產品開發
    • 全球自動駕駛AI晶片市場產能擴張
    • 全球自動駕駛AI晶片市場併購與合資狀況
    • 認證和許可

第7章主要企業簡介

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

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