China Smart-Road Roadside Perception Industry Report, 2022

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Top 10 roadside perception suppliers: quality suppliers come to the front in each market segment.

The growing number of roadside perception players comes with active industrial investment and financing.

The soaring demand for roadside perception is an enticement to ever more entrants. In addition to conventional roadside perception suppliers that make continuous efforts to deploy, technology giants and vehicle perception suppliers among others all have begun to step into the roadside perception field.

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The four tech tycoons, Huawei, Baidu, Alibaba and Tencent (HBAT), have all entered the smart-road roadside perception market:

Huawei with the ability to independently develop software and hardware can self-develop full-stack smart roadside perception solutions which have been seen in projects like Beijing–Taipei Expressway, Yanqing-Chongli Expressway and Shenyang Dadong District Smart Bus.
Baidu concentrates on application of vehicle-infrastructure cooperation technology, for example, in Beijing Yizhuang and Yanqing-Chongli Expressway. It provides some perception hardware (cameras), and the rest are customized by its ecosystem partners;
Alibaba has participated in construction of smart highways such as Hangzhou-Shaoxing-Ningbo Expressway in Zhejiang and the Middle Section of Jinan-Qingdao Expressway in Shandong. It provides software platforms and integrated solutions, and roadside perception hardware is offered by its partners;
Tencent has piloted the digital base map mode of radar + ETC real-time perception on Guangzhou-Qingyuan Expressway.

In addition, being optimistic about roadside perception, the capital market places more bets on roadside perception companies:

In May 2022, CiDi closed a Series C funding round and raised RMB300 million. This round was led by Chengdu Science and Technology Innovation Investment Group; China Xinxing Asset Investment was the co-investor; old shareholders such as Hunan Ruishi Private Equity Fund Management and Unifortune Investment Fund Management continued to follow up;
In April 2022, Raysun Radar raised tens of millions of yuan in a new funding round which was jointly invested by Yongxin Capital and Yijing Capital. The funds will be largely spent on developing roadside sensors for smart roads above C4, expanding existing capacity and enhancing market layout;
In July 2021, Xiangde Information Technology collected tens of millions of yuan in its Pre-A funding round in which Jianyuan Fund and ZTE Zhongchuang (Xi'an) Investment Management were co-financiers;
In April 2021, Hikailink closed a strategic funding round where CCCC Fund and China Merchants Capital both increased their share capital. The raised funds will be used to accelerate the research and development of new-generation intelligent connected roadside devices.

Quality suppliers stand out in each of the multiple roadside perception segments.

This report summarizes and analyzes the top 12 suppliers of roadside perception integrated solutions, and the top 10 suppliers in roadside camera/radar/LiDAR/radar-video all-in-one segments.

Take the roadside radar-video all-in-one as an example:

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Roadside perception technology evolves with market development.

Current roadside perception hardware products include cameras, radars, radar-video all-in-ones, and LiDARs. Cameras are used most widely, with the most mature market and technology; radars have been becoming a standard configuration for communication control systems after their application value was verified, and are more used in vehicle-infrastructure cooperation and smart highways.

(1) Cameras improve resolution and perception in low visibility conditions.

At present, cameras are still the most important perception device that produces the largest amounts of roadside data. The development of smart roads is accompanied by the ever higher requirements for roadside perception hardware. For conventional cameras collect and recognize small amount of information, AI computing power is therefore needed to improve resolution of cameras and add camera functions. Huawei, Dahua Technology, Baidu and Uniview Technologies among others have all introduced their AI cameras.

Furthermore, CiDi proposed a new method for daylight visibility detection and warning using vision + C-V2X technology, and has deployed and promoted it on highways. Utilizing existing surveillance cameras combined with C-V2X technology and roadside edge computing, this method enables roadside devices to response quickly even in low visibility conditions.

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(2) The radar frequency band is adjusted according to policies, and 80GHz has become a wide choice.

In December 2021, the Ministry of Industry and Information Technology (MIIT) issued the "Interim Regulations on the Administration of Automotive Radar Radios", indicating that the 76-79GHz frequency band is used for automotive radars, and shall not be applied by other types of ground-based radars unless otherwise specified by the national radio administration. The document came into effect on March 1, 2022. Considering the frequency band limitation of the MIIT, roadside radar suppliers have also adjusted their product lines. Now 80GHz is a wide choice.

Nanoradar: the MR76S roadside perception radar unveiled in April 2022 staggers the 76-79GHz frequency band for automotive radars and uses 80GHz, effectively preventing interference to 77GHz automotive radars. This radar enables accurate ranging, speed measurement and precise positioning for 128 targets, with the maximum detection range of 300 meters. It is available to holographic intersections.

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RACO Defense: in December 2021, Beijing Institute of Technology Ruixing Electronic Technology Co., Ltd., a subsidiary of RACO Defense, launched an 80GHz super range radar, which was developed with Hebei Provincial Communications Planning and Design Institute. This product breaks through the detection range of 500-1000 meters delivered by conventional super range radars, and detects as long as 1000-1500 meters at the 80GHz upgrade.

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(3) LiDAR starts massive adoption at the roadside.

The mass production and declining price of LiDAR at the vehicle end has laid a solid foundation for its application at the roadside. Among roadside LiDAR suppliers, VanJee Technology, CiDi, LeiShen Intelligent System and Innovusion have developed dedicated roadside LiDAR products; automotive LiDAR vendors like Zvision Technologies, Hesai Technology and RoboSense have set foot in this field as well.

From the completed smart road projects, it can be seen that the adoption of LiDAR has been widespread:

The project of reconstruction and expansion of the Tai'an-Zaozhuang two-way eight-lane section of the Beijing-Taipei Expressway spans 189.483 kilometers, and installs a total of 33 sets of LiDARs;
The all smart intersections in Yizhuang in Beijing and Jiading District in Shanghai use LiDARs. Yizhuang adopts LiDARs tailored by Baidu with its partners, and Jiading District’s LiDAR products are provided by Zvision Technologies and Hesai Technology;
The Xiong’an 5G+ Smart Bus Project deployed RoboSense’s LiDAR RS-LiDAR-M1 at the roadside.

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(4) As more radar-video all-in-ones are used, manufacturers’ pace of deploying accelerates.

Through the lens of bidding projects of local governments in the recent two years, the demand for radar-video all-in-one products has surged:
In 2021, the traffic signal control system project in the Intelligent Transportation Project of People’s Government of Puyang City planned to purchase 120 sets of radar-video all-in-ones;
In 2021, the Beijing Signal Renovation Project started to use radars and radar-video all-in-ones as the main perception approach, showing Beijing's acceptation of the radar-video all-in-one technology route. This marks that the radar-video all-in-one product market will enter a new phase of development.

Suppliers are also stepping up their efforts to develop radar-video all-in-one technology and deploy new products:

Raysun Radar: its 4D radar-video all-in-one is applicable to both intelligent transportation management and vehicle-infrastructure cooperation. Compared with the previous-generation products, the device can accurately recognize 9 types of targets within its detection range, effectively filter ground clutters with its height finding capability, and thus distinguish motor vehicles from non-motor vehicles and pedestrians, with the recognition accuracy above 90%.

Uniview Technologies: in September 2021, the company launched RV942, a 4MP low-light radar-video all-in-one that carries an 80GHz radar and integrates a camera with AI algorithms. Supported by video algorithms, the device can track up to 256 targets and offers a detection range as long as 250 meters.

China Smart-Road Roadside Perception Industry Report, 2022 highlights:
Roadside perception industry (development background, formulation of policies and standards, market size, market pattern, demand from autonomous driving, etc.);
Key roadside perception technologies (camera, radar, LiDAR, radar-video all-in-one, etc.) (status quo, development trends, etc.);
Roadside perception application deployment in scenarios, e.g., highways, urban intersections and smart bus routes;
Key roadside perception system integrators (main integrated solutions, application, etc.);
Key roadside perception hardware suppliers (main product lines, cooperation, product application, etc.).

1 Status Quo of Roadside Perception
1.1 Development Background for Intelligent Roadside Perception Market
1.1.1 Vehicle-Infrastructure-Cloud Cooperation Is A New Intelligent Transportation System (1)
1.1.2 Vehicle-Infrastructure-Cloud Cooperation Is A New Intelligent Transportation System (2)
1.1.3 Application of Intelligent Roadside Perception in Vehicle-Infrastructure Cooperation
1.1.4 Opportunities in Roadside Perception Field
1.1.5 Challenges in Roadside Perception Field
1.2 Guiding Policies for Smart Roads
1.2.1 The "14th Five-Year Plan for Roads" Promotes the Construction of Smart Roads
1.2.2 Guiding Policies in Intelligent Transportation Field: National
1.2.3 Guiding Policies in Intelligent Transportation Field: Local
1.2.4 Levels of Road Intelligence
1.3 Building of Intelligent Roadside Standard System
1.3.1 The 76-79GHz Frequency Band Is No Longer Used for Roadside Radars
1.3.2 The Latest Progress in Building of National Roadside Standards, 2020-2022
1.3.3 The Latest Progress in Building of Local Roadside Standards, 2020-2022
1.3.4 Local Guidelines on Smart Road Construction, 2020-2022
1.3.5 Guidelines of Yunnan Province on Smart Highway Construction
1.3.6 Building of Intelligent Roadside Standard System
1.3.7 Group Standards: Technical Requirements for Vehicle-Infrastructure Coordination System Information Interaction Part 2: Roadside Facilities and Cloud Control Platform
1.3.8 Group Standards: Technical Requirements for Roadside Millimeter-Wave Radar for Vehicle-Infrastructure Collaboration (1)
1.3.9 Group Standards: Technical Requirements for Roadside Millimeter-Wave Radar for Vehicle-Infrastructure Collaboration (2)
1.4 Intelligent Roadside Perception Market Size
1.4.1 Market Size - Estimates and Assumptions
1.4.2 Demand for Highway Roadside Perception Devices, 2021-2026E
1.4.3 Highway Roadside Perception Device Market Size, 2021-2026E (1)
1.4.4 Highway Roadside Perception Device Market Size, 2021-2026E (2)
1.4.5 Demand for Urban Intersection Perception Devices, 2021-2026E
1.4.6 Urban Intersection Perception Device Market Size, 2021-2026E (1)
1.4.7 Urban Intersection Perception Device Market Size, 2021-2026E (2)
1.4.8 China’s Roadside Perception Market Size, 2021-2026E
1.5 Intelligent Roadside Perception Industry Chain Pattern
1.5.1 Roadside Perception Product Layout of Major Suppliers (1)
1.5.2 Roadside Perception Product Layout of Major Suppliers (2)
1.5.3 TOP 12 Roadside Perception Integrated Solution Suppliers (1)
1.5.4 TOP 12 Roadside Perception Integrated Solution Suppliers (2)
1.5.5 TOP 12 Roadside Perception Integrated Solution Suppliers (3)
1.5.6 TOP 10 Roadside Camera Suppliers (1)
1.5.7 TOP 10 Roadside Camera Suppliers (2)
1.5.8 TOP 10 Roadside Radar Suppliers (1)
1.5.9 TOP 10 Roadside Radar Suppliers (2)
1.5.10 TOP 10 Roadside LiDAR Suppliers (1)
1.5.11 TOP 10 Roadside LiDAR Suppliers (2)
1.5.12 TOP 10 Roadside Radar-Video All-In-One Suppliers (1)
1.5.13 TOP 10 Roadside Radar-Video All-In-One Suppliers (2)
1.6 Exploration of Roadside Perception Business Models
1.6.1 Problems That Need To Be Solved To Build Mature Business Models
1.6.2 Use "Vehicle-Infrastructure-Cloud Integrated" Solutions to Create a Commercial Closed-Loop of Roadside Perception
1.6.3 Explore Different Profit Models for Cost Recovery
1.6.4 The Future Operators in the Roadside Market May Be Changed from Governments to Companies
1.7 Demand for Roadside Perception from Autonomous Driving
1.7.1 Vehicle-Infrastructure Cooperation Is One of the Key Technology Routes for the Development Autonomous Driving
1.7.2 Construction Elements of CVIS Roads
1.7.3 Roadside Cooperative Vehicle-Infrastructure Systems (CVIS) (1)
1.7.4 Roadside Cooperative Vehicle-Infrastructure Systems (CVIS) (2)
1.7.5 Dependency of CVIS on Roadside Perception in the Process of Development
1.7.6 L4 Roadside Technology Route
1.7.7 Demand for Roadside Perception from L4 Autonomous Driving

2 Key Technologies and Development Trends of Roadside Perception
2.1 Key Roadside Perception Technologies and Construction Challenges
2.1.1 Intelligent Roadside Perception Solutions
2.1.2 Advantages and Disadvantages of Main Roadside Perception Devices
2.1.3 Market Maturity of Main Roadside Perception Technologies
2.1.4 Challenges in Roadside Perception Construction
2.1.5 Enduring Problems in Development of Roadside Perception for L4 Autonomous Driving
2.2 Camera
2.2.1 Role of Intelligent Analysis of Roadside Videos
2.2.2 Roadside Camera Supplier Landscape
2.2.3 Comparison of Products between Major Suppliers (1)
2.2.4 Comparison of Products between Major Suppliers (2)
2.2.5 Roadside Camera Technology Trend 1: Vision AI Empowers Roadside Camera
2.2.6 Roadside Camera Technology Trend 2: Terminal-Cloud Cooperation
2.2.7 Roadside Camera Technology Trend 3: Vision + C-V2X Can Improve Detection Accuracy and Stability
2.3 Radar
2.3.1 Application Advantages of Radars at the Roadside
2.3.2 Optimal Layout Distance of Radars at the Roadside
2.3.3 Roadside Radar Supplier Landscape
2.3.4 Comparison of Products and Technologies between Major Suppliers (1)
2.3.5 Comparison of Products and Technologies between Major Suppliers (2)
2.3.6 Roadside Radar Technology Trend: 4D Radar
2.4 LiDAR
2.4.1 Role of Roadside LiDAR
2.4.2 Application Modes of Roadside LiDAR
2.4.3 Application of Roadside LiDAR Poses High Requirements for Edge Computing
2.4.4 Deployment of Roadside LiDAR by Major Suppliers (1)
2.4.5 Deployment of Roadside LiDAR by Major Suppliers (2)
2.4.6 Priority Application Scenarios of Roadside LiDAR: Intersections and Highways
2.4.7 Opportunities in Roadside LiDAR Market
2.5 Radar-Video All-In-One
2.5.1 Advantages of Radar-Video All-In-One in Roadside Perception
2.5.2 Radar-Video Integration Forms
2.5.3 Radar-Video Integration Market Players (1)
2.5.4 Radar-Video Integration Market Players (2)
2.5.5 Deployment of Major Suppliers in Radar-Video All-In-One/Integration (1)
2.5.6 Deployment of Major Suppliers in Radar-Video All-In-One/Integration (2)
2.5.7 Radar-Video All-In-One Will Become A Development Trend of Roadside Perception
2.5.8 Growing Demand for Radar-Video All-In-Ones
2.6 Development Trends of Roadside Perception
2.6.1 Roadside Perception Technology Trend 1: Combination of Software and Hardware
2.6.2 Roadside Perception Technology Trend 2: Multi-sensor Fusion (1)
2.6.3 Roadside Perception Technology Trend 2: Multi-sensor Fusion (2)
2.6.4 Roadside Perception Technology Trend 3: Map Base + Roadside Perception + Cloud Platform Combination (1)
2.6.5 Roadside Perception Technology Trend 3: Map Base + Roadside Perception + Cloud Platform Combination (2)
2.6.6 Roadside Perception Technology Trend 4: Multi-sensor Fusion + Unified Timing + Coordinate Synchronization

3 Roadside Perception Application Deployment Cases
3.1 Exploration of Roadside Perception Application Scenarios
3.1.1 Ideas for Selection of Application Scenarios in Early Commercialization: Traffic Safety
3.1.2 Ideas for Selection of Application Scenarios in Early Commercialization: Traffic Efficiency
3.1.3 Ideas for Selection of Application Scenarios in Early Commercialization: Technology Maturity
3.1.4 Exploration of Scenario-based Application Modes
3.1.5 Optimal Application Scenarios in the Early Stage - Expressways
3.1.6 Optimal Application Scenarios in the Early Stage - Urban Roads
3.1.7 Optimal Application Scenarios in the Early Stage - Closed Campuses
3.1.8 Rhythm of Commercial Deployment of Intelligent Roadside Devices
3.2 Smart Highway Roadside Perception Application Cases
3.2.1 Development of Highway Autonomous Driving
3.2.2 Development of Highway Vehicle-Infrastructure Cooperation
3.2.3 Application of Fusion Perception + Digital Twin in Highways
3.2.4 Principles for Deploying Smart Highway Roadside Perception Devices
3.2.5 Hangzhou-Shaoxing-Ningbo Smart Expressway in Zhejiang Province (1)
3.2.6 Hangzhou-Shaoxing-Ningbo Smart Expressway in Zhejiang Province (2)
3.2.7 Deployment of Roadside Devices on Hangzhou-Shaoxing-Ningbo Smart Expressway in Zhejiang Province
3.2.8 Changsha-Yiyang Expressway in Hunan Province
3.2.9 Yanqing-Chongli Expressway in Hebei Province (1)
3.2.10 Yanqing-Chongli Expressway in Hebei Province (2)
3.2.11 Deployment of Roadside Perception Devices on Yanqing-Chongli Expressway
3.2.12 Perception Solutions on Guangzhou-Qingyuan Expressway
3.2.13 Smart Highway on the Changshu Section of G524 (1)
3.2.14 Smart Highway on the Changshu Section of G524 (2)
3.2.15 Smart Section of Beijing-Taipei Expressway (1)
3.2.16 Smart Section of Beijing-Taipei Expressway (2)
3.2.17 Smart Highway on the Middle Section of Jinan-Qingdao Expressway in Shandong Province
3.2.18 Beijing-Xiong’an Expressway
3.2.19 Rongcheng-Wuhai Expressway (1)
3.2.20 Rongcheng-Wuhai Expressway (2)
3.2.21 Smart Highway Deployment Scheme of Hunan Province (1)
3.2.22 Smart Highway Deployment Scheme of Hunan Province (2)
3.2.23 Smart Highway V2X Deployment Scheme of Hunan Province (3)
3.3 Application Cases of Roadside Perception at Smart Intersections
3.3.1 Smart Intersection
3.3.2 Main Smart Intersection Solutions
3.3.3 Smart Intersections in Beijing Yizhuang (1)
3.3.4 Smart Intersections in Beijing Yizhuang (2)
3.3.5 Smart Intersection Solutions in Chuxiong City, Yunnan
3.3.6 Smart Intersection Construction Scheme of Jiading District, Shanghai
3.4 Smart Bus Roadside Perception Application Cases
3.4.1 Shenyang Dadong District Smart Bus (1)
3.4.2 Shenyang Dadong District Smart Bus (2)
3.4.3 Shenyang Dadong District Smart Bus (3)
3.4.4 Roadside Perception Hardware for Shenyang Dadong District Smart Bus Project
3.4.5 Xiong'an "5G + Smart Bus" Pilot Project (1)
3.4.6 Xiong'an "5G + Smart Bus" Pilot Project (2)

4 Roadside Perception System Integrators
4.1 Huawei
4.1.1 Roadside Perception System Product Lines (1)
4.1.2 Roadside Perception System Product Lines (2)
4.1.3 Holographic Intersection Solutions for Urban Roads
4.1.4 Advantages of Holographic Intersection Solutions
4.1.5 AI Ultralow Light Bayonet Camera
4.1.6 Holographic Road Network (1)
4.1.7 Holographic Road Network (2)
4.1.8 Application of Holographic Road Network
4.1.9 CVIS Solutions
4.1.10 High Speed Video Cloud Connected Road Network Perception Basis of Highway Industry
4.1.11 Good Hope Smart Highway Roadside Perception Solution
4.1.12 Highway Quasi-All-Weather Traffic Solutions
4.2 Dahua Technology
4.2.1 Profile
4.2.2 Highway Video Surveillance Solution
4.2.3 Radar-Video All-in-One
4.3 Hikailink
4.3.1 Profile
4.3.2 Roadside Perception Products (1)
4.3.3 Roadside Perception Products (2)
4.3.4 Smart Road Solutions for Intelligent Vehicles
4.3.5 CVIS Solutions
4.3.6 Roadside Perception Deployment Scheme for Highway Scenarios
4.3.7 Application of Roadside Perception: L4 Autonomous Bus Line in Fujian Province
4.4 China TransInfo
4.4.1 Profile
4.4.2 R&D Layout
4.4.3 Roadside Devices
4.4.4 Construction Mode of Roadside Facilities
4.4.5 TransInfo-Alibaba Highway Solutions
4.4.6 City-level Dynamic and Static Traffic Integrated Solution
4.5 Hualu Yiyun
4.5.1 Profile
4.5.2 Main Roadside Products
4.5.3 CVIS Solutions
4.6 Gosuncn
4.6.1 Profile
4.6.2 Intelligent Transportation Layout
4.6.3 Intelligent Roadside Perception Solutions
4.7 Baidu
4.7.1 Cooperative Vehicle-Infrastructure Open Source Solution
4.7.2 Apollo 6.0 Platform First Introduced the Object-level Fusion of Vehicle Perception and Roadside Perception
4.7.3 ACE Smart Intersection Solutions
4.7.4 Smart Highway CVIS Solutions
4.7.5 Smart Highway Product Family
4.8 ZTE
4.8.1 Intelligent Transportation Business
4.8.2 Intelligent Roadside Perception Integrated Solutions
4.9 SenseTime
4.9.1 Autonomous Driving Layout
4.9.2 Roadside Perception Solutions
4.9.3 Road Cloud Perception Platform
4.10 VanJee Technology
4.10.1 Profile
4.10.2 Intelligent Roadside Devices
4.10.3 Parameters of Intelligent Roadside Devices (1)
4.10.4 Parameters of Intelligent Roadside Devices (2)
4.10.5 Roadside Smart Base Station
4.10.6 Roadside 3D LiDAR
4.10.7 Features of Roadside Perception Products
4.10.8 Roadside Monitoring Status of Roadside 3D LiDAR
4.10.9 V2X+3D LiDAR Intelligent Roadside Perception Solution
4.10.10 BAAI-VanJee Roadside Dataset Serving CVIS-enabled Autonomous Driving
4.10.11 Propose the "1+2+4+N" Dual Smart City Construction Plan
4.11 CiDi
4.11.1 Profile
4.11.2 Intelligent Roadside Perception Devices
4.11.3 Intelligent Roadside Terminal Systems
4.11.4 Roadside Perception Application: Smart Intersections
4.12 OriginalTek
4.12.1 Profile
4.12.2 Holographic Perception Solutions
4.12.3 Radar-Video All-In-One
4.13 Institute of Deep Perception Technology (IDPT)
4.13.1 Cooperative Vehicle-Infrastructure Holographic Perception System Solution: Deep Sea-1
4.13.2 Roadside Perception Radar
4.13.3 Radar-Video All-In-One: Huihai-3 (1)
4.13.4 Radar-Video All-In-One: Huihai-3 (2)
4.13.5 Radar-Video All-In-One: Huihai-3 (3)
4.14 Nebula Link
4.14.1 Intelligent Holographic Intersection Perception System
4.14.2 Application of Roadside Perception System
4.15 JueFX Technology
4.15.1 Roadside Perception Solutions
4.15.2 Intelligent Architecture of Vehicle-Infrastructure Cooperation
4.15.3 Roadside Fusion Perception System: Zhihuan?
4.15.4 Application of Roadside Fusion Perception System: Ports
4.15.5 Application of Roadside Fusion Perception System: Urban Roads

5 Roadside Perception Device Suppliers
5.1 Hikvision
5.1.1 Intelligent Driving Industry Layout
5.1.2 Intelligent Roadside Perception Devices
5.1.3 Radar-Video Perception Devices (1)
5.1.4 Radar-Video Perception Devices (2)
5.2 ZTITS
5.2.1 Profile
5.2.2 Product System
5.2.3 Roadside Video Edge Computing Devices
5.3 Uniview Technologies
5.3.1 Roadside Camera Products
5.3.2 Roadside Radar Series
5.3.3 Radar-Video All-In-Ones
5.3.4 Highway Solutions (1)
5.3.5 Smart Highway Solutions (2)
5.3.6 Smart Intersection Solutions
5.4 Hurys
5.4.1 Profile
5.4.2 Features of Traffic Radar Products
5.4.3 Features of Radar-Video All-In-One Products
5.4.4 Intelligent Roadside Perception Solutions (1)
5.4.5 Intelligent Roadside Perception Solutions (2)
5.4.6 Intelligent Roadside Perception Solutions (3)
5.4.7 Intelligent Roadside Perception Solutions (4)
5.5 Raysun Radar
5.5.1 Profile
5.5.2 Financing
5.5.3 Parameters of Roadside Perception Products
5.5.4 Radar-Video All-In-Ones
5.5.5 4D Radar-Video All-In-One
5.5.6 Advantages of Roadside Perception Solutions Based on Raysun 4D Radar-Video All-In-One
5.5.7 V2X Holographic Road Surface Perception Solution
5.5.8 Application of Radar-Video Integration Technology to Smart Highways
5.6 TransMicrowave
5.6.1 Intelligent Roadside Perception Devices (1)
5.6.2 Intelligent Roadside Perception Devices (2)
5.6.3 Roadside Bayonet Velocity Radar
5.7 DeGuRoon
5.7.1 Profile
5.7.2 Roadside Cameras
5.7.3 Radar-Video All-In-One Devices
5.7.4 Omnidirectional Radars
5.7.5 Application of Roadside Perception Devices
5.8 Muniu Technology
5.8.1 Roadside Radars
5.8.2 Application Scenarios of Roadside Radars
5.9 HawkEye Technology
5.9.1 Roadside Radars
5.9.2 Released SDR Series High Performance Radar
5.9.3 Technical Strength
5.10 Xiangde Information Technology
5.10.1 Profile
5.10.2 Radar-Video All-In-Ones
5.10.3 Radars
5.10.4 Cooperative Radar-Vehicle-Infrastructure Roadside Perception System
5.11 RACO Defense
5.11.1 Multi-source Fusion Perception All-In-One
5.11.2 Roadside Radar Products (1)
5.11.3 Roadside Radar Products (2)
5.11.4 Roadside Radar Products (3)
5.11.5 Roadside Radar Products (4)
5.12 Costone Technology
5.12.1 Radar-Video All-In-Ones
5.12.2 Application of Radar-Video All-In-One to Highway Accident Detection
5.12.3 Application of Radar-Video All-In-One to Urban Road Signal Control
5.13 Nanoradar
5.13.1 Roadside Radars
5.13.2 MR76S Radar (1)
5.13.3 MR76S Radar (2)
5.14 Zvision Technologies
5.14.1 Roadside LiDAR Products
5.15 Hesai Technology
5.15.1 Roadside LiDAR Layout
5.16 Ouster
5.16.1 Roadside LiDAR
5.16.2 Launched CVIS Solutions in Cooperation with LiangDao Intelligence
5.16.3 Cooperated with Snowlake Technology to Empower Vehicle-Infrastructure Cooperation
5.17 LeiShen Intelligent Systems
5.17.1 Profile
5.17.2 Radar-Video All-In-Ones
5.17.3 LiDAR-enabled CVIS
5.17.4 LiDAR-enabled CVIS Flow
5.17.5 LiDAR-enabled CVIS Architecture
5.17.6 LiDAR-enabled CVIS Hardware
5.17.7 Application of Cooperative Vehicle-Infrastructure Roadside Perception System
5.18 Innovusion
5.18.1 Profile
5.18.2 Roadside LiDAR
5.19 LiangDao Intelligence
5.19.1 Roadside Perception Products
5.19.2 Roadside Perception Intelligent Transportation Solution: LDTelescope?
5.19.3 Application of Roadside Perception
5.20 RoboSense
5.20.1 Roadside LiDAR
5.20.2 Cooperated with China Information and Communication Technologies Group
5.21 Benewake
5.21.1 Roadside LiDAR Products
5.21.2 Application of CVIS LiDAR
5.22 Neuvition Technology
5.22.1 Roadside LiDAR Products
5.22.2 Smart Highway Solutions
5.23 RichBeam
5.23.1 Roadside LiDAR Products (1)
5.23.2 Roadside LiDAR Products (2)
5.24 Others
5.24.1 Roadside Perception Radars of Chuhang Technology
5.24.2 Roadside Radar Products of Oculii
5.24.3 TZTEK Technology's Roadside Edge Perception System for V2X Scenarios
5.24.4 Intelligent Perception Unit of Tsinghua University Suzhou Automotive Research Institute
5.24.5 Roadside Perception Products of iTarge Technology

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Research on Zonal Communication Topology: New Architectures Including 10 BASE-T1S+RCP, AVB/TSN Ethernet Are Under Rapid Development Vehicle communication networks are mainly divided into in-vehicle n...

Software-Defined Vehicles in 2026: Software Supply Chain Panorama and Business Models Research

Research on Automotive Software Business Models: Exploration of Token Economy, AI Service Revenue Sharing and Other Businesses Under the Trend of AI Agents: Exploration of Business Models Based on T...

New Energy Commercial Vehicle 800-1000V High-Voltage Platform & Supply Chain Panorama Research Report, 2026

Research on 800V Architecture of Commercial Vehicles: New Energy Penetration Rate Exceeds 35%, and 800V Full-Domain High-Voltage Architecture Rapidly Penetrates Heavy-Duty Trucks Explosive Growth in ...

ADAS and Autonomous Driving Tier 1 Suppliers Research Report, 2026 – Chinese Companies

Intelligent Driving Industry Leap: From Widespread L2.9 Adoption toward Physical AI and New Full?Domain Mobility Ecosystem As vehicle intelligence advances, the installations and penetration rate of...

Vehicle-Road-Cloud Integration and C-V2X Industry Report, 2026

Vehicle-Road-Cloud and C-V2X Research: with the three-tier promotion system of "top-level planning + mandatory pilot + evaluation binding", the industry turning point is approachingThis report focuses...

China OEM Data Capability Analysis Report, 2026

OEM Data Capability Research: 24 OEMs × 9 Capability Domains, Who Takes the Lead? An L4 autonomous driving R&D and test vehicle can generate approximately 10TB of raw data per single day — data v...

Autonomous Driving Domain Controller and Central Computing Unit (CCU) Industry Report, 2026

Autonomous Driving Domain Controller (ADCU) Research: One-Chip CCU solutions are quickly available in vehicles In China's passenger car market, autonomous driving systems involved in mass production ...

Automotive EMS and ECU Industry Research Report, 2026

Automotive EMS Research: The boundaries between EMS providers and Tier1 suppliers are becoming blurred, and the supply chain model is evolving from a linear chain to a networked structure Mainstream ...

Automotive Microcontroller Unit (MCU) and Application Scenario Research Report, 2026

Automotive MCU Research: Increased demand for redundant security drives ASIL D-compliant MCU shipments to exceed 100 million units In a vehicle EEA, MCUs are widely distributed in various functional ...

China Intelligent Cockpit Patent Analysis Report, 2026

Intelligent Cockpit Patent Research: Cockpit AI, In?vehicle Health, and Infotainment Are Upgrade to Scenario?based and Proactive Functions From a patent perspective, this report explores the cutting?...

Research Report on Application of VLA Large Model in Automobiles and Robots, 2026

Research on Automotive and Robot VLA: Hybrid Architectures Become Mainstream, VLA Integrates with General World Models, and Reinforcement Learning Serves as Core Engine Vision?Language?Action (VLA) m...

China Charging Infrastructure (Supercharging, Battery Swapping, V2G, etc.) and High-Performance Supercharging Battery Research Report, 2026

Charging and battery swapping research: as 5C+ supercharging vehicle models go into mass production, the pace of OEMs self-building supercharging networks quickens 800-1000V high-voltage platforms ar...

China Passenger Car Electronic Controlled Suspension Industry Report, 2026

Electronic Controlled Suspension Industry Research: As the First Year of Full Active Suspension Unfolds, Three Technical Routes Race Forward 1. Penetration Rate Surges Three Times, and Electronic Con...

Intelligent Driving SoC Research Report, 2026

Research on Intelligent Driving SoCs: Competition Focus Shifts to L3/L4 Embedded Hardware, and Computing Power of Flagship Vehicle Models Exceeds 1,000 TOPS In terms of intelligent driving system in...

Automotive AI Large Model Technology Research Report, 2026

Automotive AI Large Model Research: Competition Shifts from "Who Has the Stronger Model" to "Who Boasts Higher Link Efficiency" ResearchInChina released the Automotive AI Large Model Technology Resea...

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