ADAS용 GPU 시장 : 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the ADAS GPU market size is expected to grow from USD 4.39 billion in 2025 to USD 5.38 billion in 2026 and is forecast to reach USD 16.27 billion by 2031 at 24.77% CAGR over 2026-2031.

This report is Segmented by GPU Integration Type (Integrated GPU/SoC, and Discrete GPU/Accelerator), ADAS Application (Perception and Sensor Fusion, Path Planning, Driver Monitoring, Surround View, and Autonomous Driving Compute), Vehicle Type (Passenger Vehicles, and Commercial Vehicles), Level of Autonomy (Level 1, Level 2, Level 3, More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global ADAS GPU Market Trends and Insights

Rising ADAS Content Per Vehicle

The ADAS GPU market is seeing its strongest near-term push from the steady increase in compute-heavy safety and convenience features per vehicle. Mid-range models now carry broader combinations of radar, surround-view cameras, driver monitoring, occupant monitoring, and highway or city assistance functions, which raises processing needs well beyond older control architectures. That change is no longer limited to premium vehicles, because mainstream launches now use feature bundles that require more parallel compute and faster data handling. As those features move into higher-volume production, suppliers are making GPU and SoC decisions earlier in the vehicle development cycle so they can lock software, memory, and validation plans together. This also raises the value of platforms that can support multiple workloads on the same silicon, since automakers want to avoid adding separate processors for each new function. The ADAS GPU market, therefore, benefits not only from more vehicles using assistance functions but also from each equipped vehicle carrying a higher compute load than the previous model cycle.

Shift Toward Software-Defined Vehicles

The shift toward software-defined vehicles is changing how automakers design electronic systems, and that directly supports the ADAS GPU market. Instead of spreading functions across dozens of dedicated control units, newer architectures move more sensing, decision-making, and user-interface tasks into fewer high-performance compute nodes. That model favors GPU-enabled SoCs because they are better suited to inference-heavy workloads that need fast parallel processing and shared memory access. Qualcomm and BMW introduced Snapdragon Ride Pilot in the all-new BMW iX3 as a jointly developed automated driving system, demonstrating how closely chip vendors now work with automakers on the software stack and hardware platform. The commercial effect is equally important because the software-defined model gives semiconductor platform suppliers a greater role in long-cycle vehicle programs and reduces the gap between the chip and vehicle roadmaps. For the ADAS GPU market, this means demand is increasingly tied to platform standardization across model families, not only to feature adoption in one vehicle line.

High Automotive Qualification And Functional Safety Burden

Functional safety remains one of the biggest constraints on the ADAS GPU market because automotive qualification requires more than strong compute performance. Suppliers need hardware safety mechanisms, redundancy, diagnostics, process controls, and documentation that meet the highest automotive safety standards over long development cycles. That adds time, cost, and engineering effort before a platform can enter production in safety-critical vehicle programs. NVIDIA said its DriveOS platform reached ASIL-D conformance, assessed by TUV SUD, and also achieved ISO 21434 cybersecurity process certification, which shows the scale of work needed to make a platform suitable for advanced autonomous applications. These requirements narrow the supplier base because consumer or data-center designs cannot be moved into vehicles without major redesign and validation. For the ADAS GPU market, the outcome is a smaller group of qualified platform vendors, premium pricing for compliant solutions, and slower capacity expansion than raw demand would otherwise support.

Other drivers and restraints analyzed in the detailed report include:

1. Growth Of Centralized And Zonal Vehicle Architectures
2. Expansion Of High-Resolution Digital Cockpits And Multi-Display Systems
3. Thermal And Power Envelope Constraints

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Integrated GPU and GPU-enabled SoC solutions accounted for 59.46% of revenue in 2025, which kept this format at the center of the ADAS GPU market. Automakers continue to favor integrated designs because a single chip can simplify packaging, reduce power overhead, and streamline safety qualification across multiple functions. This advantage becomes stronger as centralized vehicle architectures spread, since one platform can cover perception, infotainment, gateway, and monitoring workloads in a shared compute domain. NVIDIA says DRIVE Thor is built to run automated driving and in-vehicle experiences on one architecture, which supports the value case for integrated solutions in multi-function vehicle platforms.

Discrete GPU and accelerator solutions are projected to grow at a 24.99% CAGR through 2031, which makes them the faster-rising integration format within the ADAS GPU market. Their growth comes from programs that need sustained compute far above what a single monolithic SoC can comfortably deliver in a mainstream thermal envelope. WeRide and Lenovo introduced an automotive-grade HPC 3.0 platform using dual NVIDIA DRIVE AGX Thor processors, and that example shows where discrete compute demand is emerging most clearly in autonomous mobility programs. At the same time, Imagination Technologies highlights safety-focused GPU IP that lowers power and die-area overhead, which supports the continued competitiveness of integrated formats in volume vehicle lines. This balance explains why integrated solutions still carry the larger ADAS GPU market size today, while discrete accelerators are building momentum where compute headroom matters more than packaging simplicity.

Perception and sensor fusion accounted for 33.02% of revenue in 2025, giving this category the largest application position in the ADAS GPU market. Every ADAS-equipped vehicle needs a perception pipeline, which keeps this workload relevant across Level 1, Level 2, and higher-autonomy configurations. The segment also benefits from the broad use of cameras, radar, and driver-monitoring functions that all rely on high-throughput parallel processing. That is why perception remains the revenue anchor even as other application categories gain speed within the ADAS GPU market.

Autonomous driving compute is projected to expand at a 25.03% CAGR through 2031, making it the fastest-growing application area in the ADAS GPU market. NVIDIA said BYD, Geely, Isuzu, and Nissan have adopted DRIVE Hyperion for Level 4 vehicle programs, pointing to rising demand for platforms that can handle surround sensing, path planning, and in-cabin AI together. Path planning, decision-making, surround view, parking assistance, and driver or occupant monitoring continue to expand as part of the same compute stack, rather than as isolated modules on separate hardware. As those workloads converge, platform vendors that can unify them on a single chip or compute domain gain a stronger value proposition with automakers. This is also where the ADAS GPU market share of advanced application stacks becomes more meaningful, because the fastest growth is coming from software-rich deployments rather than from simple feature additions alone.

Complete Report Scope:

• By GPU Integration Type
  • Integrated GPU / GPU-Enabled SoC
  • Discrete Automotive GPU / Accelerator
• By ADAS Application
  • Perception and Sensor Fusion
  • Path Planning and Decision-Making
  • Driver Monitoring and Occupant Monitoring
  • Surround View and Parking Assistance
  • Autonomous Driving Compute
• By Vehicle Type
  • Passenger Vehicles
  • Commercial Vehicles
• By Level of Autonomy
  • Level 1
  • Level 2
  • Level 3
  • Level 4
  • Level 5
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • South Korea
    • India
    • Southeast Asia
    • Rest of Asia-Pacific
  • South America
  • Middle East and Africa

Geography Analysis

Asia-Pacific held 39.18% of revenue in 2025, which gave it the leading regional position in the ADAS GPU market. The region benefits from large vehicle production volumes, fast feature rollout in China, and strong links between domestic vehicle programs and compute platform suppliers. China remains the main demand center because it combines broad passenger vehicle output with rapid adoption of centralized compute and advanced assistance functions. Japan supports the regional base through commercial vehicle and autonomous bus activity, while South Korea adds strength through advanced semiconductor and vehicle platform development. NVIDIA said BYD, Geely, Isuzu, and Nissan adopted DRIVE Hyperion for Level 4 programs, which underlines the depth of regional engagement across both passenger and commercial platforms.

North America and Europe form the next major cluster in the ADAS GPU market, supported by premium vehicle programs, strict safety expectations, and active autonomous mobility development. Euro NCAP announced a 2026 protocol overhaul with a four-pillar safety framework, and that increases the importance of tightly integrated compute for vehicles targeting top safety scores. North America remains important for robotaxi development, simulation infrastructure, and partnerships between compute platform vendors and mobility operators. Mercedes-Benz presented its next-generation S-Class on NVIDIA DRIVE AV with an L4-ready architecture, which shows how Europe continues to influence the high end of the ADAS GPU market through premium vehicle innovation.

The Middle East and Africa is projected to expand at a 25.11% CAGR through 2031, making it the fastest-growing regional segment in the ADAS GPU market. Growth there is supported by smart mobility investment, premium vehicle demand, and the early buildout of autonomous mobility ecosystems in Gulf markets. NVIDIA said its June 2026 DRIVE Hyperion ecosystem expansion included Middle East mobility collaborations, which signals active commercial interest rather than only exploratory positioning. South America remains smaller, but it is progressing through commercial fleet safety requirements and premium passenger vehicle adoption that gradually raise the compute content of locally relevant vehicle platforms.

1. NVIDIA Corporation
2. Qualcomm Technologies, Inc.
3. Intel Corporation
4. Advanced Micro Devices, Inc.
5. Mobileye Global Inc.
6. Renesas Electronics Corporation
7. NXP Semiconductors N.V.
8. Infineon Technologies AG
9. STMicroelectronics N.V.
10. Texas Instruments Incorporated
11. Samsung Electronics Co., Ltd.
12. MediaTek Inc.
13. Arm Ltd.
14. Imagination Technologies Limited
15. Huawei Technologies Co., Ltd.
16. Horizon Robotics
17. Black Sesame Technologies (Hong Kong) Limited
18. Valens Semiconductor Ltd.
19. Synopsys, Inc.
20. Cadence Design Systems, Inc.
21. Socionext Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Rising ADAS Content Per Vehicle
  • 4.2.2 Shift Toward Software-Defined Vehicles
  • 4.2.3 Growth of Centralized and Zonal Vehicle Architectures
  • 4.2.4 Expansion of High-Resolution Digital Cockpits and Multi-Display Systems
  • 4.2.5 Safety Regulation-Driven Compute Upgrades
  • 4.2.6 Automotive AI and Sensor Fusion Workload Growth
• 4.3 Market Restraints
  • 4.3.1 High Automotive Qualification and Functional Safety Burden
  • 4.3.2 Thermal and Power Envelope Constraints
  • 4.3.3 Semiconductor Supply Chain and Advanced Node Availability Risk
  • 4.3.4 Cost Pressure in Mass-Market Vehicle Platforms
• 4.4 Impact of Macroeconomic Factors on the Market
• 4.5 Market Positioning Analysis
• 4.6 Regulatory Landscape
• 4.7 Technological Outlook
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Bargaining Power of Suppliers
  • 4.8.2 Bargaining Power of Buyers
  • 4.8.3 Threat of New Entrants
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By GPU Integration Type
  • 5.1.1 Integrated GPU / GPU-Enabled SoC
  • 5.1.2 Discrete Automotive GPU / Accelerator
• 5.2 By ADAS Application
  • 5.2.1 Perception and Sensor Fusion
  • 5.2.2 Path Planning and Decision-Making
  • 5.2.3 Driver Monitoring and Occupant Monitoring
  • 5.2.4 Surround View and Parking Assistance
  • 5.2.5 Autonomous Driving Compute
• 5.3 By Vehicle Type
  • 5.3.1 Passenger Vehicles
  • 5.3.2 Commercial Vehicles
• 5.4 By Level of Autonomy
  • 5.4.1 Level 1
  • 5.4.2 Level 2
  • 5.4.3 Level 3
  • 5.4.4 Level 4
  • 5.4.5 Level 5
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 Europe
    • 5.5.2.1 Germany
    • 5.5.2.2 United Kingdom
    • 5.5.2.3 France
    • 5.5.2.4 Italy
    • 5.5.2.5 Rest of Europe
  • 5.5.3 Asia-Pacific
    • 5.5.3.1 China
    • 5.5.3.2 Japan
    • 5.5.3.3 South Korea
    • 5.5.3.4 India
    • 5.5.3.5 Southeast Asia
    • 5.5.3.6 Rest of Asia-Pacific
  • 5.5.4 South America
  • 5.5.5 Middle East and Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Positioning Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 NVIDIA Corporation
  • 6.4.2 Qualcomm Technologies, Inc.
  • 6.4.3 Intel Corporation
  • 6.4.4 Advanced Micro Devices, Inc.
  • 6.4.5 Mobileye Global Inc.
  • 6.4.6 Renesas Electronics Corporation
  • 6.4.7 NXP Semiconductors N.V.
  • 6.4.8 Infineon Technologies AG
  • 6.4.9 STMicroelectronics N.V.
  • 6.4.10 Texas Instruments Incorporated
  • 6.4.11 Samsung Electronics Co., Ltd.
  • 6.4.12 MediaTek Inc.
  • 6.4.13 Arm Ltd.
  • 6.4.14 Imagination Technologies Limited
  • 6.4.15 Huawei Technologies Co., Ltd.
  • 6.4.16 Horizon Robotics
  • 6.4.17 Black Sesame Technologies (Hong Kong) Limited
  • 6.4.18 Valens Semiconductor Ltd.
  • 6.4.19 Synopsys, Inc.
  • 6.4.20 Cadence Design Systems, Inc.
  • 6.4.21 Socionext Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment