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Monthly Monitoring Report on China Automotive Intelligent Driving Technology and Data Trends (Issue 2, 2024)

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    Report

  • 200 Pages
  • September 2024
  • Region: China
  • Research In China
  • ID: 5971211

Insight into intelligent driving: ECARX self-develops intelligent driving chips, and L2.5 installation soared by 175% year on year.

Based on the 2023 version, the 2024 version of Monthly Monitoring Report on China Automotive Intelligent Driving Technology and Data Trends adds trend forecast, new vehicle research, OTA tracking and other contents, and further details the data indicators.

In the advanced intelligent driving market, the installations of L2.5 ADAS functions grew fastest.

According to statistics from the publisher, from January to February 2024, ADAS functions (L1-L2.9) were installed in a total of 1.977 million passenger cars in China, a like-on-like upsurge of 49.9%, with an installation rate of 61.2%, 8.1 percentage points higher than the same period last year. Wherein, L2 ADAS functions were installed in the largest number of passenger cars, up to 1.347 million units, jumping by 69.2% on an annualize basis, with an installation rate of 41.7%, up 9.6 percentage points. As seen from the growth in installations, vehicles equipped with L2.5 ADAS functions enjoyed the fastest growth, soaring by 174.9% to 76,000 units from 28,000 units in the prior-year period.

In terms of OEM types, joint venture brands boasted installations and installation rate of L2 ADAS functions higher than Chinese independent brands. The installations reached 804,000 vehicles, up 73.2% compared with the same period of the previous year, and the installation rate was 54.1%, up 16.7 percentage points, which were mainly driven by the vehicle sales of Volkswagen, Toyota and Honda, each selling up to more than 100,000 units. In addition, joint venture brands also took a certain share in the L2.5 and L2.9 ADAS markets, mainly boosted by the sales of Mercedes-Benz and Tesla, respectively.

Chinese independent brands had installations and installation rate of L2+ and above ADAS functions higher than joint venture brands. Wherein, L2.9 ADAS functions were installed in the largest number of passenger cars, up to 95,000 units, 84.2% more than in the same period of the previous year, with an installation rate of 5.4%, up 1.3 percentage points, which were mainly driven by the sales of brands such as AITO, Li Auto and ZEEKR, each selling more than 10,000 units.

As for energy type, most fuel-powered models were installed with L2 functions, with an installation rate of 48.1%, of which the installation rates of L2+ and above functions fell off a cliff and were all lower than 2% and L2.9 functions had yet to be available. The installation rates of L2.9 and above functions in new energy models were all higher than 5%, and showed an upward trend, of which L2.9 functions boasted the highest installation rate, up to 16.5%, and were mainly installed in Model Y, AITO M7 and Model 3.

From the perspective of the growth in installation rate, the installation rate of L2 ADAS functions in fuel-powered models grew fastest, up to 48.1% compared with 33.4% in the same period last year, which was primarily driven by the sales of models like Sagitar, Lavida and Mercedes-Benz C-Class. New energy models saw the fastest-growing installation rate of L2.5 ADAS functions, up to 6.0% compared with 3.9% in the prior-year period, which was mainly pushed up by the sales of Li Auto’s models, ZEEKR 007 and Blue Mountain DHT-PHEV.

Independent development of intelligent driving chips: ECARX joined the self-development camp, focusing on developing NPU.

ECARX positions itself as an 'incremental parts supplier' serving global automakers, and comprehensively deploy incremental parts for intelligent vehicles, such as chips, LiDAR, and computing platforms, for example:

In March 2024, ECARX and SiEngine announced AD1000, a self-developed advanced intelligent driving chip in Longying Series. It adopts a 7nm process and is manufactured by TSMC. With CPU compute of 250 KDMIPS and NPU compute of 256 TOPS, and through multi-chip synergy, it enables computing power of up to 1024 TOPS, meeting the requirements of L2++-L4 intelligent driving. It is expected to come into mass production in October 2024.

Momenta, a Tier 1 supplier of intelligent driving software, also makes layout. In July 2023, several former key staffs of OPPO ZEKU joined Momenta to develop autonomous driving chips. In January 2024, Momenta entered the IP phase in development of autonomous driving chips. In December 2023, Xinxin Hangtu (Suzhou) Technology Co., Ltd. was established as the chip project company of Momenta. The new company raised funds independently and closed the angel funding round. Currently, Momenta’s chip team has nearly 100 people.

In addition, emerging carmakers NIO, Xpeng and Li Auto, and conventional OEM BYD are also representatives in independent development of intelligent driving chips. For example, in December 2023 NIO unveiled Shenji NX9031, a chip with CPU compute of 615K DMIPS, enabling microsecond-level dynamic wake-up of various subsystems, and having been installed on NIO ET9. Xpeng’s intelligent driving chip was brought up in late 2023 and is scheduled to be mounted on cars in 2025. BYD planned to develop dedicated intelligent driving chips in house from 2022. This project is led by BYD's semiconductor team. Currently, BYD has carried out the self-development projects of intelligent driving sensors, chips and domain controllers.

Whether it is ECARX or OEMs, they put their focus on NPU (Neural Processing Unit) in self-developing intelligent driving chips. Their self-developed NPUs can better adapt to their intelligent driving algorithms and enable higher peak performance, energy efficiency and area efficiency, achieving the aim of quickly processing AI inference tasks. For example, according to ECARX, compared with NVIDIA Orin X, its Longying intelligent driving chip AD1000 has 100% higher NPU capabilities and 185% more local storage space in NPU. Li Auto began to work hard to self-develop intelligent driving chips in November 2023, concentrating on developing NPU modules.

Leveraging the 18C rules of the Hong Kong Exchanges and Clearing Limited (HKEX), China’s local intelligent driving chip vendors are concentrating their efforts on going public.

In addition to independent development, China’s local intelligent driving chip vendors are doing their utmost to be listed on HKEX. In March 2024, Horizon Robotics submitted a prospectus to the stock exchange. At the same time, Black Sesame Technologies also submitted its application for listing on the main board to HKEX again.

On March 31, 2023, the Chapter 18C of the Rules Governing the Listing of Securities on The Stock Exchange of Hong Kong Limited officially came into effect. Chapter 18C is a new listing regime for specialist technology companies, involving listing applications from companies operating in one of five Specialist Technology Industries: (i) next-generation information technology; (ii) advanced hardware and software; (iii) advanced materials; (iv) new energy and environmental protection; and (v) new food and agriculture technologies. The 18C rules help some technology start-ups which are not profitable to quickly gain support from the capital market for listing, lowering the listing threshold requirements for commercialized and uncommercialized specialist technology companies.

Table of Contents

Section 1 Insight into Topics
1.1 Topic 1: Software-defined Vehicle Radar Industry Research in 2024
Chapter 1 Overview of Software-Defined Radar
1.1 Definition and Features of Software-defined Radar
1.2 Block Diagram of Software-defined Radar
1.3 Comparison between Software-defined Radar and Other 4D Radar Technology Routes
1.4 Classification of Software-defined Radar Technology Routes
1.5 Summary of Main Software-defined Radar Suppliers - Software Algorithm Suppliers
1.6 Summary of Main Software-defined Radar Suppliers - Hardware and Solution Suppliers
1.7 Comparison between Main Software-defined Radar Products
1.8 Software-defined Radar Business Models
Chapter 2 Status Quo and Development Trends of Software-Defined Radar
2.1 4D Radar Installations, 2030E
2.2 Software-defined Radar Architecture - Discussion on Satellite Architecture
2.2.1 Automotive Radar Architecture Evolution
2.2.2 Comparison of Design between Smart Radar Sensor and Satellite Radar Sensor
2.2.3 Comparison of Signal Processing between Smart Radar Sensor and Satellite Radar Sensor
2.2.4 Comparison of Architecture between Smart Radar Sensor and Satellite Radar Sensor
2.2.5 Advantages and Challenges
2.2.6 Satellite Architecture Case 1 (1)
2.2.7 Satellite Architecture Case 1 (2)
2.2.8 Satellite Architecture Case 2
2.2.9 Satellite Architecture Case 3 (1)
2.2.10 Satellite Architecture Case 3 (2)
2.2.11 Satellite Architecture Case 4
2.3 Trend 1
2.3.1 Case 1
2.3.2 Case 2
2.3.3 Case 3
2.4 Trend 2
2.4.1 Case 1
2.5 Trend 3
Chapter 3 Software-defined Radar Suppliers - Main Software Algorithm Suppliers
3.1 Oculii
3.1.1 Profile and Business Model
3.1.2 Technical Features of Software-defined Radars
3.1.3 Software-defined Radar Technology - Virtual Aperture Imaging Software
3.1.4 Software-defined Radar Product Lineup
3.1.5 Software-defined Radar Products - Front Radar
3.1.6 Software-defined Radar Products - Corner Radar
3.1.7 Next-generation Software-defined Radar Route: Algorithm + Central Domain Control Architecture
3.1.8 Central Domain Control 4D Imaging Radar Architecture - Software Algorithm
3.1.9 Central Domain Control 4D Imaging Radar Architecture - Hardware Design
3.1.10 Central Domain Control 4D Imaging Radar Architecture - Sensor Fusion
3.1.11 Solution - Autonomous Driving
3.1.12 Cooperation Dynamics
3.2 Zadar
3.2.1 Profile and Software-Defined Imaging Radar (SDIR) Platform
3.2.2 Composition of SDIR Platform - zVUE Software-defined Radar Operating System
3.2.3 Composition of SDIR Platform - Radar Sensor Platform Product Lineup
3.2.4 Composition of SDIR Platform - zPRIME Radar Sensor
3.3 Provizio
3.3.1 Profile and Business Model
3.3.2 Software-defined Digital Imaging Perception Radar Products
3.3.3 Main Technologies and Software Algorithms of Software-defined Digital Imaging Perception Radar
3.3.4 Solution - 5D Perception Platform
3.4 Predictive Perception Software of BlueSpace.ai 4D
3.5 Neural Propulsion Systems
3.5.1 Profile and Technology Direction
3.5.2 Atomic Norm Software Platform
3.5.3 Solution - Multi-sensor Platform for L4 and Above
3.6 Zendar
3.6.1 Profile and Product Classification
3.6.2 Distributed Aperture Radar (DAR) Technology
3.6.3 Solution - Satellite Radar System
3.7 Spartan
3.7.1 Profile and Partners
3.7.2 Software-defined Radar Technology - Software Algorithm
3.7.3 Solution - Commercial Vehicle Collision Warning Solution Hoplo
Chapter 4 Software-defined Radar Suppliers - Main Hardware and Solution Suppliers
4.1 NXP
4.1.1 Software Layout of Software-defined Radar - Using Distributed Aperture Radar (DAR) Technology
4.1.2 Hardware Layout of Software-defined Radar - Release of Third-generation Automotive Radar Single Chip
4.1.3 Third-generation Automotive Radar Single Chip Design
4.1.4 ADAS Functions Supported by Third-generation Automotive Radar Single Chip
4.1.5 Architecture of Software-defined Radar - Distributed Streaming Sensor Architecture
4.1.6 Functions Enabled by Distributed Streaming Sensor Architecture: 360o Sensor Fusion
4.2 Mobileye
4.2.1 Key Features of Software-defined Imaging Radar
4.2.2 Imaging Effect of Software-defined Imaging Radar
4.2.3 Solution - Future Autonomous Driving Sensing Subsystem: Three-channel Redundancy
4.2.4 Software-defined Imaging Radar Mass Production and Cooperation Trends
4.3 CubTEK
4.3.1 Profile and Development History
4.3.2 Software-defined 4D Imaging Radar Solution - Software Algorithm
4.3.3 Software-defined 4D Imaging Radar Solution - Hardware Platform
4.3.4 Main Performance of Radars
4.4 Geometrical-PAL
4.4.1 Profile and Product Classification
4.4.2 Software-defined Radar - Software Algorithm
4.4.3 Solution - Multi-sensor Fusion Solution
4.4.4 Cooperation Dynamics
4.5 Freetech
4.5.1 Profile
4.5.2 Radar Product Lineup
4.5.3 Software-defined Radar
4.5.4 Sensor Fusion Algorithm: Advanced Intelligent Driving Algorithm Architecture
4.5.5 Solution - Advanced Intelligent Driving Solution Roadmap
4.5.6 Front 4D Radar-based Solutions
4.5.7 4D Radar-based Solutions
4.6 Cheng-Tech
4.6.1 Profile and Product Classification
4.6.2 Radar Product Planning
4.6.3 Main Software-defined Radars
4.6.4 Radar-based Solutions (1)
4.6.5 Radar-based Solutions (2)
1.2 Topic 2: OEM OTA Tracking (March 2024)
1.2.1 Summary of OEM OTA
1.2.2 Jiyue AI DAY 2024
1.2.3 ZEEKR 009 Pushed OS5.0, Adding Navigation ZEEKR Pilot (NZP)
1.2.4 Luxeed S7 Pushed OTA 4.0.1, Adding Urban NCA and Urban LCC PLUS
1.2.5 Avatr 11 Started OTA Updates, Pushing NOA That Does Not Rely on HD Maps
1.2.6 Xpeng Xmart OS 4.6.0 OTA, with Intersection Traffic Capacity Surging by 72%
1.2.7 OTA Updates for Full Range of AITO Models, Adding Urban Navigation Cruise Assist (NCA)
1.2.8 Tesla Pushed Software Update 2024.8, Adding Adaptive High Beam for Some Models
1.2.9 Tesla Released A More Robust Autopark Version in Software Update 2024.2.11
1.2.10 Lynk & Co 05 LYNK OS N Started Updating and Optimizing NOA
Section 2 Market Trends
2.1 Market Trends
2.1.1 Market Trend 1
2.1.2 Market Trend 2
2.1.3 Market Trend 3
2.1.4 Market Trend 4
2.1.5 Market Trend 5
2.1.6 Market Trend 6
2.1.7 Market Trend 7
2.1.8 Market Trend 8
2.1.9 Market Trend 9
2.1.10 Market Trend 10
2.1.11 Market Trend 11
Section 3 Research on New Cars
Overview of New Cars
3.1 Leapmotor C10
3.1.1 Leapmotor C10: Highlights of Intelligent Cockpit
3.1.2 Leapmotor C10: Highlights of Intelligent Driving
3.2 Xiaomi SU7
3.2.1 Xiaomi SU7: Highlights of Intelligent Cockpit
3.2.2 Xiaomi SU7: Highlights of Intelligent Driving
3.3 Changan UNI-Z
3.3.1 Changan UNI-Z: Highlights of Intelligent Cockpit
3.3.2 Changan UNI-Z: Highlights of Intelligent Driving
3.4 Changan NEVO A07 Zhenxiang Edition
3.4.1 Changan NEVO A07 Zhenxiang Edition: Highlights of Intelligent Cockpit/Intelligent Driving
3.5 EXEED Stellar C-DM
3.5.1 EXEED Stellar C-DM: Highlights of Intelligent Cockpit
3.5.2 EXEED Stellar C-DM: Highlights of Intelligent Driving
Section 4 Data Monitoring
4.1 ADAS Data by Level
4.1.1 Installations of L1-L2.9 in Passenger Cars in China
4.1.2 Installation Rate of L1-L2.9 in Passenger Cars in China
4.1.3 Installations and Installation Rate of L1 in Passenger Cars by OEM/Price in China
4.1.4 Installations and Installation Rate of L1 in Passenger Cars by Brand/Model in China
4.1.5 Installations and Installation Rate of L2 in Passenger Cars by OEM/Price in China
4.1.6 Installations and Installation Rate of L2 in Passenger Cars by Brand/Model in China
4.1.7 Installations and Installation Rate of L2+ in Passenger Cars by OEM/Price in China
4.1.8 Installations and Installation Rate of L2+ in Passenger Cars by Brand/Model in China
4.1.9 Installations and Installation Rate of L2.5 in Passenger Cars by OEM/Price in China
4.1.10 Installations and Installation Rate of L2.5 in Passenger Cars by Brand/Model in China
4.1.11 Installations and Installation Rate of L2.9 in Passenger Cars by OEM/Price in China
4.1.12 Installations and Installation Rate of L2.9 in Passenger Cars by Brand/Model in China
4.1.13 Installations and Installation Rate of L2+ and Above in Passenger Cars by OEM/Price in China
4.1.14 Installations and Installation Rate of L2+ and Above in Passenger Cars by Brand/Model in China
4.2 ADAS Data by Function
4.2.1 Overall Installations and Installation Rate of ADAS Functions in Passenger Cars in China
4.2.2 Monthly Installations and Installation Rate of ADAS Functions in Passenger Cars in China
4.2.3 Installations of ADAS Functions in Passenger Cars by Price in China
4.2.4 Installation Rate of ADAS Functions in Passenger Cars by Price in China
4.2.5 Installations and Installation Rate of LCA in Passenger Cars by Brand/Model
4.2.6 Installations and Installation Rate of AEB in Passenger Cars by Brand/Model
4.2.7 Installations and Installation Rate of ACC in Passenger Cars by Brand/Model
4.2.8 Installations and Installation Rate of ACC STOP&GO in Passenger Cars by Brand/Model
4.2.9 Installations and Installation Rate of LKA in Passenger Cars by Brand/Model
4.2.10 Installations and Installation Rate of TJA in Passenger Cars by Brand/Model
4.2.11 Installations and Installation Rate of ICA in Passenger Cars by Brand/Model
4.2.12 Installations and Installation Rate of ALC in Passenger Cars by Brand/Model
4.2.13 Installations and Installation Rate of APA in Passenger Cars by Brand/Model
4.2.14 Installations and Installation Rate of APA in Passenger Cars by Brand/Model
4.2.15 Installations and Installation Rate of DMS in Passenger Cars by Brand/Model
4.2.16 Installations and Installation Rate of OMS in Passenger Cars by Brand/Model
4.2.17 Installations and Installation Rate of AVS in Passenger Cars by Brand/Model
4.3 Market Data of ADAS Domain Controller/Chip Suppliers
4.3.1 Market Share of L2+ and Above Domain Controller Suppliers in China’s Passenger Car Market
4.3.2 Market Share of L2+ and Above Domain Control Software Suppliers in China’s Passenger Car Market
4.3.3 Market Share of L2+ and Above Chip Suppliers in China’s Passenger Car Market
4.3.4 Market Share of L2+ and Above Domain Control Master Chip Solutions in China’s Passenger Car Market
4.3.5 Market Share of L2+ Domain Control Master Chip Solutions in China’s Passenger Car Market
4.3.6 Market Share of L2.5 Domain Control Master Chip Solutions in China’s Passenger Car Market
4.3.7 Market Share of L2.9 Domain Control Master Chip Solutions in China’s Passenger Car Market
4.4 Market Date of ADAS HD Map Suppliers
4.4.1 Market Share of HD Map Suppliers in China’s Passenger Car Market
4.4.2 Installation of HD Map Suppliers in China’s Passenger Car Market
Section 5 News Events
5.1 Related Policies
5.2 OEMs
5.3 ADAS and Autonomous Driving Solution Suppliers
5.4 Intelligent Driving Industry Chain

Companies Mentioned

  • Oculii
  • Zadar
  • Provizio
  • BlueSpace.ai
  • Zendar
  • Spartan
  • NXP
  • Mobileye
  • CubTEK
  • Geometrical-PAL
  • Freetech
  • Cheng-Tech
  • Jiyue
  • ZEEKR
  • Leapmotor
  • Xiaomi
  • Changan
  • EXEED

Methodology

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