自動運転AIチップ市場レポート：2031年までの動向、予測、競合分析

世界の自動運転AIチップ市場の将来は、乗用車市場と商用車市場に機会があり、有望視されています。世界の自動運転AIチップ市場は、2025年から2031年にかけてCAGR 22.5％で成長すると予想されます。この市場の主な促進要因は、自律走行車に対する需要の高まり、開発と展開を奨励する有利な政策、AIアルゴリズムの進歩です。

• Lucintelでは、タイプ別ではGPUが予測期間中に最も高い成長を遂げると予測しています。
• 用途別では、乗用車が引き続き最大セグメントです。
• 地域別では、アジア太平洋が予測期間中に最も高い成長が見込まれます。

自動運転AIチップ市場の戦略的成長機会

自動運転AIチップ市場は、技術的進歩と進化する市場ニーズによって、さまざまな用途でさまざまな成長機会を提示しています。主な機会は、この分野における技術革新と拡大の可能性を反映しています。

• 自動車安全システムの強化：高度な安全システムのためのAIチップの開発は、大きな成長機会をもたらします。これらのチップは、衝突回避、車線維持支援、自動緊急ブレーキなどの機能を実現し、車両全体の安全性と運転体験を向上させます。
• 自律走行ナビゲーション：AIチップは自律走行車のナビゲーションに不可欠であり、自動運転車のリアルタイム処理と意思決定を可能にします。より正確で信頼性の高いナビゲーション・システムへの需要がこのアプリケーションの成長を後押ししており、センサーの統合とデータ処理に革新の機会がもたらされています。
• 電気自動車の統合：電気自動車にAIチップを統合することで、バッテリー管理、エネルギー効率、車両全体の性能を向上させ、成長の可能性をもたらします。EVをよりスマートで効率的なものにするという焦点は、持続可能な輸送ソリューションに向けた幅広い動向と一致しています。
• フリート管理ソリューション：AIチップは、車両運行、メンテナンス、ルート計画を最適化するための車両管理ソリューションでますます使用されるようになっています。このアプリケーションは、企業が高度なAI技術を通じて効率性の向上と運用コストの削減を目指す中で、成長機会をもたらします。
• 車載インフォテインメント・システム：車載インフォテインメント・システムへのAIチップの統合は、音声認識、パーソナライズされたレコメンデーション、シームレスな接続性などの機能によってユーザー体験を向上させます。このアプリケーションは、高度なインフォテインメント機能に対する消費者の需要が高まり続けていることから、成長機会をもたらします。

こうした戦略的成長機会が、自動運転AIチップ市場の革新と拡大を促進しています。さまざまなアプリケーションに対応することで、各社は新たな動向を活用し、自動車業界の進化するニーズに対応できる体制を整えています。

自動運転AIチップ市場の促進要因・課題

自動運転AIチップ市場は、技術の進歩、経済要因、規制の進展など、さまざまな促進要因・課題の影響を受けています。これらの要素は、市場力学と将来の成長を形成する上で重要な役割を果たします。

自動運転AIチップ市場を牽引する要因は以下の通りです：

• 技術の進歩：AIと半導体技術の急速な進歩が自動運転AIチップ市場を牽引しています。チップ設計、処理能力、統合能力の革新は、自律走行システムの性能と機能を強化し、市場成長の拡大につながります。
• 自律走行車に対する需要の増加：自律走行車に対する消費者の需要の高まりは、市場の主要な促進要因です。自律走行技術に投資する自動車メーカーが増える中、複雑な運転シナリオに対応できる高度なAIチップのニーズが市場拡大を後押ししています。
• 自律走行に対する規制支援：さまざまな地域における支援的な規制環境は、自律走行技術の開発と採用を促進します。自動運転車の試験と配備を促進する規制は、AIチップ市場の成長に寄与します。
• 研究開発への投資：ハイテク企業や自動車メーカーによる研究開発への多額の投資は、AIチップ技術の進歩を加速させます。こうした投資は、より革新的で効果的なソリューションにつながり、市場の成長を促進します。
• 世界な競合と協業：世界なハイテク企業や自動車メーカー間の競争と協力の激化が、AIチップ技術の革新を促進します。パートナーシップや合弁事業が進歩を促進し、高度な自律走行システムの開発を加速させます。

自動運転AIチップ市場の課題は以下の通りです：

• 高い開発コスト：市場が直面する課題の1つは、高度なAIチップの開発コストが高いことです。研究開発、製造に多額の投資が必要となるため、一部の企業にとっては参入障壁となり、市場全体の成長に影響を及ぼす可能性があります。
• 規制と安全性の課題：複雑な規制要件を乗り越え、自律走行システムの安全コンプライアンスを確保することは、市場にとって課題となります。技術を進歩させながらこれらの基準を満たすことは、困難で資源集約的なプロセスとなる可能性があります。
• サプライチェーンの混乱：主要材料や部品の不足を含むサプライチェーンの問題は、AIチップの生産と入手に影響を与える可能性があります。こうした混乱は市場力学に影響を与え、新技術の開発と展開を遅らせる可能性があります。

これらの促進要因・課題の相互作用が自動運転AIチップ市場を形成し、成長軌道と市場ダイナミクスに影響を与えます。これらの要因に対処することは、企業が自律走行技術の進化する状況において、機会を生かし、障害を克服するために極めて重要です。

目次

第1章 エグゼクティブサマリー

第2章 世界の自動運転AIチップ市場：市場力学

• イントロダクション、背景、分類
• サプライチェーン
• 業界の促進要因と課題

第3章 2019年から2031年までの市場動向と予測分析

• マクロ経済動向（2019～2024年）と予測（2025～2031年）
• 世界の自動運転AIチップ市場の動向（2019～2024年）と予測（2025～2031年）
• 世界の自動運転AIチップ市場（タイプ別）
  • GPU
  • DSP
  • NPU
  • その他
• 世界の自動運転AIチップ市場（用途別）
  • 乗用車
  • 商用車

第4章 2019年から2031年までの地域別市場動向と予測分析

• 地域別の世界自動運転AIチップ市場
• 北米の自動運転AIチップ市場
• 欧州の自動運転AIチップ市場
• アジア太平洋の自動運転AIチップ市場
• その他地域の自動運転AIチップ市場

第5章 競合分析

• 製品ポートフォリオ分析
• 運用統合
• ポーターのファイブフォース分析

第6章 成長機会と戦略分析

• 成長機会分析
  • 世界の自動運転AIチップ市場の成長機会、タイプ別
  • 世界の自動運転AIチップ市場の成長機会、用途別
  • 世界の自動運転AIチップ市場の成長機会、地域別
• 世界の自動運転AIチップ市場の新たな動向
• 戦略分析
  • 新製品開発
  • 世界の自動運転AIチップ市場の生産能力拡大
  • 世界の自動運転AIチップ市場における合併、買収、合弁事業
  • 認証とライセンシング

第7章 主要企業の企業プロファイル

• 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