Driving the revolution: AI & sensing steer automotive innovation – From the automotive White Paper, Vol. 1
From intelligent perception systems to real-time data fusion, discover how advanced sensing & imaging technologies are redefining mobility, safety, and user experience on the road.
With the development of AI and sensor technologies, the transformation of the automotive industry has expanded beyond just technical innovation to influence the entire industry ecosystem.
If AI is the “brain” of the autonomous vehicle, the sensor is like a “nerve”. Through the fusion of multiple sensors, AI enables the vehicle to perceive its environment in real time, accurately identifying and characterizing roads, vehicles, pedestrians, and much more. Combined with AI deep learning algorithms, ADAS can process more complex traffic scenes and make decisions similar to those of human drivers.
By 2030, 84% of new passenger cars and light commercial vehicles are expected to be equipped with ADAS functions, according to Yole Group’s experts.
In its latest automotive analyses, including market & technology reports, monitors and teardowns as well as in its automotive White Paper Vol. 1, Yole Group explores ADAS innovations and analyzes the strategies of the leading semiconductor companies.
Yole Group’s market & technology experts, Pierrick Boulay and Anas Chalak, as well as Celia Yuan Liu, market researcher deeply involved in tracking strategic information in Greater China, share their insights on the current state of AI-related technologies, their implications for ADAS functionalities and the impact on the supply chain. What is the status of Autonomous Driving (AD) today? What is the role of AI in the automotive industry? Who is doing what?…
Today, Yole Group invites you to dive into the future of AI & sensing innovation. Stay tuned as we hit the road again!
In imaging, computing was the first ADAS area in which processors could be found, starting with processors in camera systems. Today, most VPUs sold for automotive applications can be found in front ADAS camera systems.
Anas Chalak
Technology & Market analyst, Imaging at Yole Group
As the demands on cameras for detection, classification, and tracking have increased, AI has been incorporated into most processors through the addition of AI engines.
Consequently, computing automotive revenue increases. Yole Group announces a 13% CAGR from 2023 – 2029, which is the same order of magnitude as other automotive semiconductor components, explains Yole Group’s analysts in the Computing & AI for Automotive report.
How do you drive your car?
The way people interact with vehicles and the driving experience have undergone significant changes. For example, BYD’s “Palm Key” recognizes palm veins using macro radar, while some Cadillac and NIO models use 3D cameras to recognize faces, enabling keyless operation of vehicles. A camera in the cockpit uses biometric technology to automatically adjust personalized settings, such as seats, rearview mirrors, and interior temperature.
On the technical route, there has also been differentiation among car companies. Taking Tesla as an example, it is more inclined towards prioritizing visual capability. Its FSD V12 assistance with driving software has reduced the number of sensors needed from 26 to 12.
Celia Yuan Liu
Market Researcher, More than Moore activities
Some Chinese car companies, such as NIO, are more inclined towards multi-sensor fusion. Their NAD system adopts a fusion of LiDAR, 4D millimeter wave radar, and vision, greatly improving the stability of target tracking.
With the advances in commercialization, cost gaming is also crucial for car companies. At the software level, DeepSeek’s fast onboarding is closely related to its cost advantage. Nissan, following BYD, integrated DeepSeek’s R1 AI model into the N7 electric sedan to enhance the human-car interaction by better understanding driver intention, offering a smarter user experience, and staying competitive in China’s rapidly evolving EV market.
Pierrick Boulay
Principal Analyst, , Global Semiconductors at Yole Group
On the hardware level, taking LiDAR as an example, its cost has been reduced to even below $500, which has also increased the installation willingness of some car companies. Its cost is expected to decrease even more, to around $200, which will make it more affordable for OEMs.
Another example is cameras. Many component suppliers are now providing the entire camera module, offering lower prices compared to traditional OEMs, and enhancing the independence of the Chinese supply chain. The automotive LiDAR and camera markets are expected to grow at CAGRs of 27% and 7%, respectively.
What is the status of AI in China?
Today, China is the most dynamic market for ADAS. Dozens of automotive companies are developing around ADAS, including LiAuto, XPeng, Nio, and Leapmotors. All these companies are equipping their cars with the very latest in ADAS and infotainment processors: Nvidia’s latest processor (Orin) and Qualcomm’s latest Cockpit processor (SA8155, SA8295).
By releasing its Su7 car in 2024, Xiaomi exemplifies the popularity of ADAS and infotainment on the Chinese market.
“In ADAS computing, start-up Horizon Robotics is a showcase for China’s progress in this field,” explains Pierrick Boulay from Yole Group. “Today, all the major Chinese automakers are in contact with Horizon Robotics and are working on integrating its ADAS solutions into all or part of their models.”
LiAuto, China’s leading ADAS brand, has integrated Horizon Robotics’ Journey 5 into “Lite” versions of its vehicles, while, for the time being, retaining Nvidia Orin on advanced versions.
By announcing its own APU for LiDAR, followed by its first self-developed central processor equivalent to Nvidia’s Jetson Orin 4, Nio is following Tesla’s lead in mastering the technology at the very beginning of the design.
Over the years, Huawei has also pursued a strategy of partnerships and built a portfolio of automotive brands that integrate its ADAS technologies, including AITO, AVATR, Arcfox, Luxeed, and recently, Stelato. Huawei’s particularity lies in its integration of these models into a hardware full-stack solution, integrating its technologies in ADAS (MDC), Cockpit (Kirin), and Telematics. Today, only Qualcomm can achieve such technological synergy.
Only a few companies are currently shipping processors for use in cars: HiSilicon and Horizon Robotics for ADAS/AD processors, and SiEngine, SemiDrive, and HiSilicon for cockpit processors. However, this situation could soon change as a result of many recent partnerships and agreements for next-generation vehicles.
Autonomous driving (AD): What could we expect in the future?
AI will play a pivotal role in autonomous driving, enabling vehicles to perceive, decide, and act in complex environments. AI is a major tool for perception as early fusion of data from numerous sensors is necessary to achieve 360° environmental awareness and robust object detection and classification, even in adverse weather or low-light conditions. This is clearly the route taken by Waymo and other robotaxi players, as well as by passenger car OEMs targeting eyes-off driving applications, for example, using Nvidia’s Drive platform.
However, AI will be used in more day-to-day applications, such as AEB/P-AEB applications to meet some regulations such as FMVSS 127.While thermal imaging players are pushing to add one more sensors to allow the detection of pedestrians in low light conditions, Bosch has recently demonstrated that a system based on an existing smart forward camera and radar can be enough to fulfill the requirements of this application. To do so, they used AI model training and conducted tests in many different conditions and scenarios. In addition to a neural network engine, the system does not require a lot of computing power and will be affordable for implementation in any type of car.
AI and various sensors jointly build the technological foundation of intelligent transportation. When cars are no longer mere tools and develop towards the ultimate form of “perception thinking action”, they eventually become intelligent partners that can understand the environment, predict risks, and assist humans.
Yole Group continually tracks the evolution of the automotive semiconductor industry, spotlighting key innovations, emerging challenges, and major breakthroughs. With deep expertise in both market dynamics and technology, Yole Group’s analysts offer sharp insights into the future of mobility and the next generation of vehicles.
🔎 Stay connected at yolegroup.com for the latest updates on automotive innovation!
About the authors
Anas Chalak is Technology & Market analyst, Imaging at Yole Group.
Anas is a member of the Imaging & Display team within the More than Moore activities. He follows and researches imaging technology activity to provide market and technology analyses, as well as contributing to the production of relevant reports and projects.
Anas obtained a master’s degree in Nanoscale Engineering from École Centrale de Lyon, France, where he developed a highly multidisciplinary background in micro-nanoscale phenomena and semiconductor devices, and their applications.
Pierrick Boulay is Principal Analyst, Global Semiconductors at Yole Group.
Pierrick works in the fields of solid-state lighting and lighting systems, conducting technical, economic, and marketing analyses. In addition, he leads the automotive activities within the company.
Pierrick has authored several reports and custom analyses on topics such as automotive lighting, LiDAR, sensing for ADAS vehicles, and VCSELs.
Pierrick holds a Master of Science in Electronics from ESEO (Angers, France).
Celia Yuan Liu is a Market Researcher, More than Moore activities, at Yole Group. Her core expertise is imaging, display, photonics, power electronics, sensing, and radio frequency. In close collaboration with Yole Group’s analysts, Celia is deeply involved in the development of Yole Group’s market & technology analyses, with a special focus on the Greater China ecosystem. She daily investigates the Chinese semiconductor industry to track the latest strategic announcements made by leading companies as well as key developments throughout the supply chain.
Celia obtained a master’s degree in Materials Science and Engineering from Boston University (U.S.A.).
Anas Chalak Technology & Market analyst, Imaging at Yole GroupAs the demands on cameras for detection, classification, and tracking have increased, AI has been incorporated into most processors through the addition of AI engines.
