Advanced Driver Assistance System functionality will attract customers and restart growth of the automotive business.
- Market data on key sensors, camera, LiDAR and radar:
- Revenue forecast and volume shipments for each sensor type
- Market shares with detailed breakdown by player
- Application focus of each sensor
- In-depth understanding of the main sensor value chain, infrastructure and players:
- Who are the sensor players and how they are related?
- What is the supply chain of these sensors?
- Key technical insights and analysis regarding future technology trends and challenges:
- Have a deep understanding of how these sensors work together in a car
- Analysis of the electric/electronic (E/E) architecture of a car and how it will evolve
- Analysis of the COVID19’s impact on the industry
Table of Contents
Market forecasts 69
- Initial statements
- Impact of COVID-19 on forecasts
- Image sensors and camera module forecast (in M units)
- Image sensors market revenue forecast (in $M)
- Camera module market revenue forecast (in $M)
- LiDAR volume and revenue forecast – Split by type
- Radar module volume and revenue forecast – Split by frequency
- Computing hardware volume and revenue forecast by segment
- Overview of sensors and computing market revenue
Market trends 88
- The road to automated driving
- Different sensor technologies embedded
- Euro NCAP 2025 roadmap – in pursuit of “vision zero”
- AEB is still perfectible
- Set of sensors per car segment
- The “10+ cameras per car” roadmap
Market shares & supply chain 99
- Industry overview
- Industry trends
- Market shares
- Supply chain
Technology trends 140
- Device and technology segmentation
- Comparison of cameras for different applications
- Forward ADAS cameras are becoming increasingly complex
- LiDAR principles and components
- Technology roadmap – Potential winner in the next five years?
- LiDAR integration in ADAS vehicles
- Radar capabilities
- From assisted driving to automated driving
- Main components in a radar system
- The road to high resolution
- Cost breakdown of sensors
- Camera teardown – Example of Denso
- LiDAR teardown – Example of Valeo LiDAR
- Radar teardown – Example of Aptiv Radar
- Camera teardown – Example of Denso
- E/E architecture and computing
- Evolution of E/E architecture
- The emergence of automotive Ethernet
- Evolution of sensors: From smart to dumb sensors
- ADAS implies more computing power
- Data fusion for automated driving
- Future car architecture
About Yole Développement 248
GREATER ADAS FUNCTIONALITY WILL RESTART THE INDUSTRY AFTER THE CORONAVIRUS CRISIS
The auto industry has seen the impact of the coronavirus crisis evolve from a supply shock to a global demand shock. The production of new cars is expected to decline by 30% compared to the 2019 production level. The direction of the automotive industry towards the four major megatrends of connected, autonomous, shared and electric driving is expected to remain unchanged going forward. However, the speed of adoption might change due to the emergency. Electrification will be the main focus for OEMs as restrictions and associated penalties on CO2 emissions should remain valid.
The second target for OEMs will be related to the development of Advanced Driving Assistance Systems (ADAS) for safety and automated driving features. The development of advanced emergency braking systems (AEB) is a great step to avoid forward collisions but is still perfectible, as demonstrated by the American Automobile Association (AAA) in October 2019. Automated driving features in traffic jams or on the highway will also be
developed by OEMs as consumers are looking for these to ease driving. The development of such features will be a way for OEMs to differentiate themselves.
To do so, the addition of more sensors, more computing power and a new electric/electronic (E/E) architecture will be required. Audi and Tesla have initiated this trend using a combination of radars, cameras and a LiDAR in Audi’s case. To fuse the data generated Audi and Aptiv developed a domain controller, the zFAS, for front sensors. Tesla goes one step further in the development of domain controllers with its Autopilot hardware. Autopilot is much more complex and has more functionality, with the ability to perform frequent over-the-air (OTA) software updates. Innovation brought by such
features will be a key differentiation factor for OEMs looking to relaunch the market.
This report presents a complete overview of E/E architecture and its possible evolution, including details on the computing power needed for data fusion.
A SENSOR MARKET WORTH $22.4B IN 2025, LED BY RADARS
The production of vehicles will be heavily impacted by the coronavirus crisis. It is expected that three years will be needed to recover and get back to the same level of output. In 2020, it is expected that the global market for radars, cameras, LiDARs and computing ADAS should reach $8.6B. Almost half of this market revenue will be generated by radars with $3.8B, followed by cameras with $3.5B. LiDARs will not be significant, accounting for $0.04B and computing ADAS will generate $1.3B.
With high penetration rates of radars and cameras in cars, the associated market revenues will recover rapidly from the coronavirus crisis. Radar market revenue is expected to surpass 2019’s revenue in 2021 and will reach $9.1B in 2025 at a Compound Annual Growth Rate (CAGR) of 19%. Camera market revenue will also surpass 2019’s revenue in 2021 and will reach $8.1B in 2025 at a CAGR of 18%. Market revenue from computing ADAS is expected to reach $3.5B in 2025 at a CAGR of 22%. LiDAR market revenue is quite limited today as only one OEM like BMW or Volvo are implementing this sensor as an option in some of its cars. Other OEMs like BMW or Volvo are expected to follow in coming years, but the implementation will remain limited to high-end vehicles, and therefore limited volumes are expected. In this context, LiDAR market revenue is expected to reach $1.7B in 2025 at a CAGR of 113%. LiDAR is a complex sensor for OEMs and Tier-1s to integrate and radars and cameras are, at the same time, continuously improving their performance.
This reports presents the main sensors needed for ADAS and their associated market revenue for the period 2020 – 2025, with details concerning the industry related to each sensor.
BETTER SENSOR PERFORMANCE TO ENABLE AUTOMATED DRIVING
Today, radars and cameras are the main sensors used by OEMs to develop safety and automated driving features. Consequently, the penetration rate of forward ADAS mono cameras will increase from 51% in 2020 to 85% in 2025. This type of camera is multi-purpose and is used for AEB for also for other functionalities like Lane Keeping Assist (LKA) or Traffic Sign Recognition (TSR) in mainstream cars. For most advanced cars, forward ADAS triple cameras are used to develop advanced automated driving features like Tesla’s.
Radars are keeping pace, and the technology is continuously improving. Starting in 2019, the use of 3D radar with a better vertical field of view enabled detection of vehicle height. Radar performance will keep increasing with the implementation of imaging radars expected to start in 2021. This use of imaging radar will be combined with the use of artificial intelligence and deep learning.
On the LiDAR side, technology is moving from a macro-mechanical scanning to MEMS scanning and flash. Most LiDAR manufacturers are involved in these solid-state technologies. One of the issues for LiDAR is its integration into the vehicle. Today it is integrated in the grill, but that may not be the ideal solution. Two other positions, in headlamps or behind the windshield, are targeted by Tier-1s and OEMs.
To do so, more R&D will be necessary to reduce the volume of this sensor and allow its integration. Another issue for LiDAR is the need to process the large quantity of data it generates. High computing power, over 25 teraoperations per second (Tops), will be necessary. The last issue with LiDAR is its cost compared to the two other technologies. It is about 10 times costlier than an ADAS mono camera. Alongside volume reduction, cost reduction will also be required for significant adoption by OEMs.
The report presents the camera, LiDAR and radar sensors with details concerning their supply chain, the trends and roadmaps.
AGC, Algolux, Altera, Ambarella, ams, Apple, Aptiv, Argo, ARM, Audi, Aurora, Avis, Baidu, Blackmore, Blickfeld, BMW, Bolloré, Bosch, BrightWayVision, Cambricon, Cepton, Chevrolet, Continental, Cruise, Delphi, Denso, Didi, Dodge, Excelitas, EyeSight, Fiat, First Sensor, Flir, Ford, Freescale, Fujitsu, Geely, GM, Google, Hella, Hitachi, Honda, Horizon Robotics, Hyundain Hyundai-Mobis, Ibeo, II-VI, Infineon, Innoviz, Jabil, Jaguar, Kalray, Koito, Kostal, Land Rover, Laser Components, Lattice, LeddarTech, Lexus, Lumileds, Luminar, Lumotive, Lyft, Magna, Marelli, Maxel, May Mobility, Mazda, Melexis, Mercedes, Metawave, Micron, Mobileye, Nichia, Nidec, Nissan, Nvidia, NXP, Omnivision, OnSemiconductor, Osram, Ouster, Panasonic, Peugeot, Pioneer, Pony.ai, Porsche, Qualcomm, Quanergy, Renault, Renesas, Robosense, SAIC, Samsung, Seeing Machine, Seminex, Silc, Smart Eye, Sony, STmicroelectronics, Sunny Optical Technology, Tesla, Texas Instrument, Toshiba, Toyota, Trieye, Trilumina, Trumpf, TSMC, Uber, Valeo, Velodyne, Veoneer, Volkswagen, Volvo, Waymo, Xenomatix, Xilinx, Xperi, ZF, ZKW and more.
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