한글목차

세계 자율주행 AI 칩 시장의 미래는 승용차 시장과 상용차 시장에 기회가 있어 유망합니다. 세계 자율주행 AI 칩 시장은 2025년부터 2031년까지 CAGR 22.5%로 성장할 것으로 예상됩니다. 이 시장의 주요 촉진요인은 자율주행 차량에 대한 수요 증가, 개발 및 배포를 장려하는 유리한 정책, AI 알고리즘의 발전입니다.

• Lucintel은 유형별로는 GPU가 예측 기간 동안 가장 높은 성장세를 보일 것으로 예상하고 있습니다.
• 용도별로는 승용차가 여전히 가장 큰 부문입니다.
• 지역별로는 아시아태평양이 예측 기간 동안 가장 높은 성장을 보일 것으로 예상됩니다.

자율주행 AI 칩 시장의 전략적 성장 기회

자율주행 AI 칩 시장은 기술 발전과 진화하는 시장 요구에 따라 다양한 응용 분야에서 다양한 성장 기회를 제공하고 있습니다. 주요 기회는 이 분야의 기술 혁신과 확장 가능성을 반영합니다.

• 자동차 안전 시스템 강화 : 첨단 안전 시스템을 위한 AI 칩의 개발은 큰 성장 기회를 제공합니다. 이러한 칩은 충돌 방지, 차선 유지 지원, 자동 긴급 제동 등의 기능을 구현하여 차량 전체의 안전과 운전 경험을 향상시킬 수 있습니다.
• 자율주행 내비게이션 : AI 칩은 자율주행차의 내비게이션에 필수적인 요소로, 자율주행차의 실시간 처리 및 의사결정을 가능하게 합니다. 보다 정확하고 신뢰할 수 있는 내비게이션 시스템에 대한 수요가 이 애플리케이션의 성장을 촉진하고 있으며, 센서 통합 및 데이터 처리에서 혁신의 기회를 제공하고 있습니다.
• 전기자동차 통합 : 전기자동차에 AI 칩을 통합하여 배터리 관리, 에너지 효율, 전체 차량 성능을 개선하고 성장 잠재력을 제공하는 등 전기자동차에 AI 칩을 통합하는 것은 지속가능한 운송 솔루션을 향한 광범위한 추세와 일치합니다.
• 차량 관리 솔루션 : AI 칩은 차량 운행, 유지보수, 경로 계획을 최적화하기 위한 차량 관리 솔루션에 점점 더 많이 사용되고 있습니다. 이 애플리케이션은 기업이 첨단 AI 기술을 통해 효율성을 높이고 운영 비용을 절감하고자 하는 가운데 성장 기회를 제공합니다.
• 차량용 인포테인먼트 시스템 : 차량용 인포테인먼트 시스템에 AI 칩을 통합하면 음성 인식, 개인화된 추천, 원활한 연결성 등의 기능을 통해 사용자 경험을 향상시킬 수 있습니다. 이 애플리케이션은 고급 인포테인먼트 기능에 대한 소비자의 수요가 지속적으로 증가함에 따라 성장 기회를 제공합니다.

이러한 전략적 성장 기회는 자율주행 AI 칩 시장의 혁신과 확장을 촉진하고 있습니다. 다양한 애플리케이션에 대응함으로써 각 업체들은 새로운 트렌드를 활용하고 자동차 업계의 진화하는 요구에 대응할 수 있는 체제를 갖추고 있습니다.

자율주행 AI 칩 시장 활성화 요인 및 과제

자율주행 AI 칩 시장은 기술 발전, 경제 요인, 규제 발전 등 다양한 촉진요인과 도전 과제에 영향을 받고 있습니다. 이러한 요소들은 시장 역학 및 미래 성장을 형성하는 데 중요한 역할을 할 것입니다.

자율주행 AI 칩 시장을 견인하는 요인은 다음과 같습니다:

• 기술 발전 : AI와 반도체 기술의 급속한 발전이 자율주행 AI 칩 시장을 주도하고 있습니다. 칩 설계, 처리 능력, 통합 능력의 혁신은 자율주행 시스템의 성능과 기능을 강화하여 시장 성장의 확대로 이어질 것입니다.
• 자율주행 자동차에 대한 수요 증가 : 자율주행 자동차에 대한 소비자 수요 증가는 시장의 주요 촉진요인입니다. 자율주행 기술에 투자하는 자동차 제조업체가 증가함에 따라 복잡한 운전 시나리오에 대응할 수 있는 고급 AI 칩에 대한 요구가 시장 확대를 촉진하고 있습니다.
• 자율주행에 대한 규제 지원 : 다양한 지역의 지원적인 규제 환경은 자율주행 기술의 개발 및 채택을 촉진합니다. 자율주행차 시험 및 배치를 촉진하는 규제는 AI 칩 시장의 성장에 기여합니다.
• 연구개발 투자 : 하이테크 기업 및 자동차 제조업체의 연구개발에 대한 막대한 투자는 AI 칩 기술의 발전을 가속화할 것입니다. 이러한 투자는 보다 혁신적이고 효과적인 솔루션으로 이어져 시장 성장을 촉진할 것입니다.
• 세계 경쟁과 협력 : 세계 하이테크 기업과 자동차 제조업체 간의 경쟁과 협력의 강화는 AI 칩 기술의 혁신을 촉진할 것입니다. 파트너십과 합작투자는 진보를 촉진하고 첨단 자율주행 시스템 개발을 가속화할 것입니다.

자율주행 AI 칩 시장의 과제는 다음과 같습니다:

• 높은 개발 비용 : 시장이 직면한 과제 중 하나는 고급 AI 칩의 개발 비용이 높다는 것입니다. 연구개발, 제조에 많은 투자가 필요하기 때문에 일부 기업에게는 진입장벽이 되어 전체 시장 성장에 영향을 미칠 수 있습니다.
• 규제 및 안전 문제 : 복잡한 규제 요건을 극복하고 자율주행 시스템의 안전 규정 준수를 보장하는 것은 시장에 도전이 될 것입니다. 기술을 발전시키면서 이러한 기준을 충족하는 것은 어렵고 자원 집약적인 프로세스가 될 수 있습니다.
• 공급망 혼란 : 주요 자재 및 부품 부족을 포함한 공급망 문제는 AI 칩의 생산 및 수급에 영향을 미칠 수 있습니다. 이러한 혼란은 시장 역학에 영향을 미치고 신기술의 개발 및 배포를 지연시킬 수 있습니다.

이러한 촉진요인과 도전과제의 상호 작용이 자율주행 AI 칩 시장을 형성하고 성장 궤도와 시장 역학에 영향을 미칩니다. 이러한 요인들을 해결하는 것은 기업이 자율주행 기술의 진화하는 상황에서 기회를 활용하고 장애물을 극복하는 데 있어 매우 중요합니다.

목차

제1장 주요 요약

제2장 세계의 자율주행 AI 칩 시장 : 시장 역학

• 소개, 배경, 분류
• 공급망
• 업계 성장 촉진요인과 과제

제3장 2019년부터 2031년까지 시장 동향과 예측 분석

• 거시경제 동향(2019-2024년)과 예측(2025-2031년)
• 세계의 자율주행 AI 칩 시장 동향(2019-2024년)과 예측(2025-2031년)
• 세계의 자율주행 AI 칩 시장(유형별)
  • GPU
  • DSP
  • NPU
  • 기타
• 세계의 자율주행 AI 칩 시장(용도별)
  • 승용차
  • 상용차

제4장 2019년부터 2031년까지 지역별 시장 동향과 예측 분석

• 지역별 세계 자율주행 AI 칩 시장
• 북미의 자율주행 AI 칩 시장
• 유럽의 자율주행 AI 칩 시장
• 아시아태평양의 자율주행 AI 칩 시장
• 기타 지역의 자율주행 AI 칩 시장

제5장 경쟁 분석

• 제품 포트폴리오 분석
• 운영 통합
• Porter's Five Forces 분석

제6장 성장 기회와 전략 분석

• 성장 기회 분석
  • 세계의 자율주행 AI 칩 시장 성장 기회, 유형별
  • 세계의 자율주행 AI 칩 시장 성장 기회, 용도별
  • 세계의 자율주행 AI 칩 시장 성장 기회, 지역별
• 세계의 자율주행 AI 칩 시장 최신 동향
• 전략 분석
  • 신제품 개발
  • 세계의 자율주행 AI 칩 시장 생산능력 확대
  • 세계의 자율주행 AI 칩 시장 합병, 인수, 합작투자
  • 인증과 라이선싱

제7장 주요 기업 개요

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

영문목차

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