Glossary

Definitions

Table of contents

About the author

Companies cited in this report

What we got right, What we got wrong

Report Scope, objectives and methodology

Who should be interested in this report

Yole Group of Companies related reports

3-Pages summary

Executive summary

Context

• Automotive & mobility macro trends
• Semiconductor shortage

Market forecasts

• Automotive market (segmentation, volume, region, autonomy)
• Automotive ADAS car architecture evolution
• Automotive imaging ADAS processors volume (by sensors, by technology)
• Automotive imaging ADAS processors ASPs
• Automotive imaging ADAS processors revenue (by sensors, by technology)
• Automotive radar ADAS processors (volume, ASP, revenue)
• Automotive LiDAR ADAS processors (volume, ASP, revenue)
• Automotive ADAS processors (by application, sensors)
• Automotive infotainment processors forecast (volume, ASP, revenue)

Market trends

• From ADAS to AD
  • Function evolution
  • Safety incentive
  • Sensor evolution: Imaging, Radar, LiDAR
• In-cabin Sensing and Computing
  • Driver monitoring systems
  • Occupant monitoring systems
  • Gesture recognition
• Viewing, Infotainment and software
  • Viewing
  • Smart assistant integration

Technology trends

• Car architecture
  • E/E architecture and computing
  • Data fusion for automated driving
• Processors for ADAS & AD and in-cabin sensing
  • Processors for ADAS and AD description (Systems, ASPs, technologies specification)
  • Main systems teardown (front cameras, imaging ECUs, central platform, radar, LiDAR)
  • Technology segmentation
  • Main players technology overview
• Software for autonomy
  • Autonomy pipeline
  • Data fusion
  • CV vs AI
• Processors for infotainment
  • Centralization
  • Main computing drivers (pixel stream, number of cameras supported, etc.)
  • Processors for infotainment description (systems, teardowns, ASPs, technologies specification)
  • Main players technology overview
• Neuromorphic computing as the next trend?

Ecosystem, market, shares & supply chain

• Automotive market
  • Automotive industry noteworthy news of the Last 2 years
  • Automotive landscape – Main players (volume, revenue)
  • Disruptive OEMs vs traditional OEMs
  • Will OEM make their own chips?
  • Different automotive strategies
  • Player strategies
• ADAS to AD
  • Autonomous automotive general landscape
  • What is happening in China
  • AI ecosystem for automotive
  • Main players’ landscape and market shares for imaging and radar
  • Main players’ landscape for centralized platforms, DMS, LiDAR
  • Imaging supply chain
  • What about the robotic AV ecosystem?
• Infotainment and software
  • Main players’ landscape and market share for infotainment
  • Main strategies overview
  • Software automotive trends

Conclusion

Appendix – Artificial intelligence and beyond

Appendix – Processor definitions

How to use our data?

Appendix – Yole Développement

Processor revenue for ADAS and infotainment is growing strongly

Pushed by safety regulations, adoption of Advanced Driver Assistance Systems (ADAS) is increasing rapidly. ADAS sensors are very diverse and complementary and often require processors to function. This report covers processors for ADAS cameras, radars, and lidars, but also processors for ADAS central platforms. Computing for in-cabin cameras and radars with applications such as driver monitoring systems and occupant monitoring systems is also studied, as well as processors for infotainment. Computing revenue for ADAS and infotainment processor is increasing quickly with a Compound Annual Growth Rate from 2021-2027 (CAGR21-27) of 19%, reaching $12B value in 2027. This growth is driven by the growing number of shipments, but also the centralization trend, which needs more powerful and expensive processors. The growing Average Selling Price (ASP) is partly the consequence of the recent Covid-19 and related semiconductor shortage crises. It’s also partly due to integration of more functionalities into processors. Together, these factors are pushing up computing revenue from the automotive sector.

A crowded ecosystem with a large variety of players involved

There is growing diversity among carmakers. Traditional companies may be more or less involved in the development of autonomy functions. New electric and disruptive carmakers may create the new consumer audio-visual paradigm. Last year, some traditional carmakers announced processor developments, and the electric car giant Tesla did too. But considering the difficulty of the task and the huge investment necessary, we expect most carmakers won’t fully develop an entire chip. They will instead form partnerships and build buffer stocks.

Focusing more specifically on the processor ecosystem, the imaging ADAS processor market is today dominated by Mobileye, followed by other players such as Xilinx-AMD, Toshiba, and Texas Instruments. But many players are pushing to enter the market and have already announced design wins. These include Qualcomm and Ambarella, but also many start-ups including Hailo, Vsora, and Horizon Robotics. Most of these players are also positioning themselves for central computing processors, which is the next step for image processing. Chinese and new electric carmakers are adopting this type of architecture most rapidly. For the in-cabin sensing market, the situation is different. There are a wider variety of solutions that can be used to run the Tier-2 software solutions. Traditional automotive processors own the radar processor market. For lidar, most players use Xilinx’s programmable System-on-Chip (SoC). There is also some movement on the infotainment side, with the concentration of functions and the increasing importance of over-the-air updates in the carmakers’ software strategy.

The growing number of functions and sensors are driving the increase of processing value in cars

With ADAS development, ever more sensors are needed to add new functions and to increase the safety of the existing ones. This is directly leading to an increase in the number of processors in cars. Even if the centralization trend of computing is limiting the volume increase, it is still massive. The decentralized architecture with one processor per ADAS sensor/group of sensors is expected to remain dominant in the next five years. Moreover, this centralization trend directly implies a need for more powerful processors that need to handle all the different software layers coming on top of cameras, radar, and lidar raw data streams. The latest processor lithographic node will be used to perform these advanced tasks, with the best ratio between performance and energy consumption. This will directly increase processor prices.

Aisin, Alphabet, Algolux, Alibaba Group, Amazon, Ambarella, AMD, Apollo, Apple, Aptiv, Arbe, Argo, ARM, Arriver, Artosyn, Audi, Aurora, Autox, Baidu, BlackSesame Technologies, Blaize, Bosch, BMW Group, Cariad, Cambricon, Chery, Cipia, Continental, Cruise, Daimler, Delphi, Dena, Denso, Didi, EasyMile, Eeasy.Tech, Faurecia, FCA, Ford, Foxconn, Fujitsu, Geely, General Motors, Google, Harman, Hella, Honda, Horizon Robotics, Huawei, Hyundai, Infineon, Intel, Kalray, Leapmotor, Lyft, Magna, Mediatek, Melexis, Mercedes-Benz, Microship, Microsoft, Mobileye, Movento, Motional, Navya, Nio, Nissan, Nuance, Nvidia, NXP, Omnivision, Oppo, Pony.AI, PSA, Quadric, Qualcomm, Renault Nissan, Renesas, Samsung, Seres Automotive, SemiDrive, Siengine, SGMW, Smart Eye, Sony, Softkinetic, Stellantis, STMicroelectronics, Tesla, Texas Instruments, Toshiba, Toyota, TSMC, Uber, Valeo, Veoneer, Videantis, Volkswagen, Volvo, Vsora, Waymo, WeRide, Xiaomi, Xilinx, Xperi, Yandex, Zenseact, ZF Friedrichshafen, Zoox and more.