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스마트 로드 : 노변 인식 업계(2021년)

Smart Road-Roadside Perception Industry Report, 2021

리서치사 ResearchInChina
발행일 2021년 05월 상품코드 1015682
페이지 정보 영문 240 Pages 배송안내 1-2일 (영업일 기준)
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스마트 로드 : 노변 인식 업계(2021년) Smart Road-Roadside Perception Industry Report, 2021
발행일 : 2021년 05월 페이지 정보 : 영문 240 Pages

본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문목차를 참고해주시기 바랍니다.

중국의 지능형 노변 인식 기기 시장(RSU, 카메라, 레이더, LiDAR, 레이더 비디오 올인원 포함)은 2025년에 200억 위안 규모로 확대할 것으로 예측됩니다. 카메라와 레이더는 앞으로도 주류이며, 레이더 비디오 올인원과 LiDAR은 성장 페이스의 가속이 전망됩니다.

공식 통계에 따르면 중국에는 전부 14만 9,600km의 고속도로가 있으며, 도로망의 전체적인 밀도는 평균 6.1km/km2로, 도시의 총건설 면적은 36개의 주요 도시에서 2만 1,000km2에 달하고 있습니다. 지능형 노변 인식은 고속도로와 도시의 교차점을 커버하고 있습니다.

중국의 스마트 로드-노변 인식 업계에 대해 조사했으며, 시장 규모 및 예측, 주요 기술의 현황과 동향, 고속도로 및 도시의 교차점에서 노변 인식 장비의 도입 사례, 주요 노변 인식 시스템 통합사업자 및 기기 공급업체 등의 정보를 정리하여 전해드립니다.

목차

제1장 노변 인식에 관한 지도 방침과 기술 기준

  • 스마트 로드의 지도 방침
    • 지능형 운송의 국가 지도 방침
    • 스마트 하이웨이용 인텔리전스 테크놀러지의 레벨
    • 스마트 하이웨이 기술과 자율주행 간 레벨의 대응
    • 스마트 하이웨이의 개발 계획
    • 5G 스마트 하이웨이의 건설
  • 지능형 노변 표준 시스템 구축
    • 노변 기준 책정에서 최신의 진전(2020-2021)
    • 지능형 노변 표준 시스템 구축
    • CVIS 기반 자율주행의 표준화 프로세스(2020-2024)
    • 스마트 하이웨이 파일럿 프로젝트의 평가 내용과 기준
    • 스마트 하이웨이 프로젝트용 인프라의 표준 개선
    • 스마트 하이웨이 건설의 전체적인 산업 프레임워크

제2장 노변 인식 시장 규모와 개발 패턴

  • 지능형 노변 인식 시장의 개발 컨텍스트
    • 차량-인프라 클라우드 제휴에 기반하는 새로운 지능형 교통시스템
    • 지능형 교통에서 CVIS의 역할
    • 지능형 교통에서 노변 지능형 인식의 용도
  • 지능형 노변 인식 시장 규모
    • 시장 규모 : 추산 데이터와 전제조건
    • 고속도로 노변 인식 기기의 수요(2020-2025 E)
    • 고속도로 노변 인식 기기 시장 규모(2020-2025 E)
    • 도시 교차점 인식 장비의 수요(2020-2025 E)
    • 도시 교차점 인식 장비 시장 규모(2020-2025 E)
    • 중국의 노변 인식 시장 규모(2020-2025 E)
    • 노변 인텔리전스의 잠재적 시장 공간
  • 지능형 노변 인식 시장의 경쟁 패턴
    • 지능형 노변 인식 산업 체인
    • 노변 인식 업계 맵
    • 주요 프로바이더의 노변 인식 솔루션
    • 주요 프로바이더의 노변 인식 제품 레이아웃
  • 노변 인식 비지니스 모델의 조사
    • 성숙한 비지니스 모델을 구축하기 위해 해결할 필요가 있는 문제
    • 노변 인식 지능형 기기 비지니스 모델
    • 노변 인식 데이터 조작 모델의 조사

제3장 주요 노변 인식 기술과 개발 동향

  • 주요 노변 인식 기술
    • 중국의 스마트 도로 건설을 위한 주요 기술과 인프라
    • 공도용 5G CVIS의 건설 요소
    • 공도용 5G CVIS의 코어 구성요소(하드웨어 디바이스)
    • 지능형 노변 인식 장비의 역할
    • 지능형 노변 인식 솔루션
    • 지능형 노변 인식 시스템
  • 노변 인식의 기술적 과제
    • 노변 인식에서 중요한 기술적 과제-멀티 센서 퓨전
    • 노변 인식 구축에서의 장기적인 문제
  • 카메라
    • 노변 비디오의 지능형 분석의 역할
    • 노변 인식에서 카메라의 이점
    • 노변 카메라 공급업체의 패턴
    • 주요 공급업체 간 제품의 비교
    • 비전과 AI에 의한 노변 카메라의 지원
    • 노변 카메라 산업의 발전 동향 : 엔드 클라우드 협업
  • 레이더 기술
    • 노변 인식에서 레이더 애플리케이션의 이점
    • 노변 레이더 공급업체의 패턴
    • 주요 공급업체 간 제품 기술의 비교
    • 4D 레이더에 의한 노변 인식의 강화
  • LiDAR 테크놀러지
    • 노변 LiDAR의 역할
    • 노변 인식에서 LiDAR의 이점
    • RoadsideLiDAR에서 주요 벤더의 도입
    • 노변 인식에서 LiDAR의 우선 애플리케이션 시나리오
    • 노변 LiDAR 시장의 기회
  • 레이더 비디오 올인원 테크놀러지
    • 노변 인식에서 레이더 비디오 올인원의 이점
    • 레이더 비디오 올인원 공급업체의 패턴
    • 레이더 비디오 올인원/레이더 비디오 통합에서 주요 벤더의 도입
    • 레이더 비디오 통합에 의한 노변 인식의 동향 유지
  • RSU 테크놀러지의 동향
    • RSU의 도입 동향
  • 노변 인식의 개발 동향
    • 소프트웨어와 하드웨어의 통합
    • 멀티 센서 퓨전
    • 홀로그래픽 지각을 위한 멀티 센서 퓨전

제4장 노변 인식의 애플리케이션 도입 사례

  • 노변 인식 애플리케이션 시나리오의 조사
    • 초기 상업화에서 애플리케이션 시나리오의 선택의 아이디어
    • 시나리오 기반 애플리케이션 모델의 조사
    • 초기 단계에서 최적의 애플리케이션 시나리오-고속도로
    • 초기 단계에서 최적의 애플리케이션 시나리오-도시 도로
    • 초기 단계에서 최적의 애플리케이션 시나리오-폐쇄된 공원
    • 노변 지능형 디바이스의 상용 도입 프로세스
  • 고속도로 노변 인식의 응용 사례
    • 스마트 하이웨이의 현황
    • 스마트 하이웨이에서 노변 인식 기기의 도입 원리
    • 항저우-사오싱-닝보 스마트 하이웨이
    • 항저우-사오싱-닝보 스마트 하이웨이에 배치된 노변 기기
    • 상하이-항저우-닝보 고속도로
    • 옌칭-충리 고속도로
    • 옌칭-충리 고속도로에서 노변 인식 기기의 배치 계획
    • 옌칭-충리 고속도로의 솔루션 프로바이더
    • 옌칭-충리 고속도로의 노변 기기 공급업체
    • Hubei Ezhou 공항 고속도로
  • 도시 도로에서 노변 인식의 응용 사례
    • 스마트 교차점
    • 주요 스마트 교차점 솔루션
    • Beijing Yizhuang의 교차점 지각 솔루션
    • 윈난성 Chuxiong City의 스마트 교차점 솔루션
    • 스마트 폴
    • 스마트 폴의 이점
    • 스마트 대중교통기관

제5장 노변 인식 시스템 솔루션 프로바이더

  • Huawei
  • Dahua Technology
  • Hikvision
  • Hikailink
  • China TransInfo
  • eHualu
  • Gosuncn
  • Baidu
  • ZTE
  • SenseTime Technology
  • Vanjee Technology
  • Changsha Intelligent Driving Institute(CiDi)
  • OriginalTek
  • The Institute of Deep Perception Technology(IDPT)
  • 기타

제6장 노변 인식 기기 공급업체

  • Hurys
  • Raysun Radar
  • Beijing TransMicrowave Technology Co., Ltd.
  • DeGuRoon
  • Muniu Technology
  • Costone Technology
  • Nanoradar
  • ZTITS
  • Ouster
  • Radium Smart
  • Leishen Intelligent Systems
  • 기타
KSA 21.07.19

Roadside Perception Research: Giants Race to Deploy Radar Video All-in-one and Holographic Perception

Multi-sensor fusion holds a dominant trend for roadside perception.

Current roadside perception solutions are led by HD cameras and radars. In addition, the adoption of radar video all-in-one and LiDAR is becoming widespread. Multi-sensor fusion holds a dominant trend for roadside perception.

(1) AI-driven visual camera

Roadside cameras with visual AI analysis function enable more intuitive display of current traffic status and details. At present, vendors like Huawei, Dahua Technology and Hikvision have rolled out their AI-driven roadside cameras.

Based on the open architecture SDC OS, Huawei AI ultralow light camera allows for load of third-party algorithms through Huawei HoloSens Store, making "software-defined" cameras a reality. To make more types of targets detected by cameras, Huawei adds algorithms. For example, the perception and detection of non-motor vehicles only needs to load front-end equipment or ITS800 edge computing nodes with powerful non-motor vehicle video detection algorithms.

(2) Radar

Vendors are trying hard to improve the performance of roadside radars. Based on wide area radar front end and advanced data processing technologies, Hurys introduced a new-generation wide-area radar microwave intelligent perception system that offers more abundant, more diverse data; WAYV series ultra-long-range radars Muniu Technology launched in 2020 afford the longest detection range of 1,000 meters.

Moreover, 4D imaging radars are making their way into the roadside perception market. They provide all-round, three-dimensional, multi-dimensional monitoring and tracking of large intersections and highway scenarios, especially the holographic perception of CVIS at large complex intersections and in mixed traffic in cities. Vendors like Continental, Huawei and Oculii, which deploy roadside perception, have launched their 4D LiDARs.

(3) LiDAR

LiDAR that can acquire high-precision three-dimensional information about targets enables e-fence control and some special capabilities (target filtering, customized communication, etc.) in designated areas.

Traditional roadside perception solution providers such as VanJee Technology, Changsha Intelligent Driving Institute Ltd. (CiDi) and China TransInfo Technology already unveil their roadside LiDAR products.

In March 2021, VanJee Technology managed to deploy its smart base stations that integrate with V2X roadside antenna and LiDAR in Xiongan Civic Center V2X Demonstration Project and High-speed Railway Hub Road Intelligence Project.

Also, automotive LiDAR vendors like RoboSense and Ouster have started a foray into the roadside perception field. In 2020, Ouster and LiangDao Intelligence together created a LiDAR-based roadside solution.

(4) Radar video all-in-one

Radar video all-in-ones that feature integrated design and unified installation and share power supplies, can save a lot of costs of materials and installation. The fronted deployment of perception fusion algorithms at the terminal end leads to a marked reduction in perception latency and computing load at the edge end; and the combination of merits of video and radar offers higher target detection accuracy.

Currently, roadside vision-based HD camera vendors like Dahua Technology and Hikvision and roadside radar vendors such as Raysun Radar, Hurys and DeGuRoon have introduced their radar video all-in-ones. Among them, in 2019 Oculii released 4D radar video all-in-one that uses Falcon, its first-generation point cloud imaging radar; in the second half of 2021, Raysun Radar unveiled IET6LRR, its new-generation radar video all-in-one that provides the maximum detection range of 425 meters.

Huawei and Baidu have stepped into the field and launched "holographic perception intersection" solutions

Holographic perception is a foundation for the development of smart roads. It needs roadside perception equipment to provide comprehensive, high-quality, stable traffic data. Since 2000 Huawei, Baidu, OriginalTek and the Institute of Deep Perception Technology (IDPT), among others have rolled out their holographic perception solutions,

Huawei: in 2020 Huawei released the solution Holographic Perception Intersection 1.0; in March 2021, Huawei unveiled Holographic Perception Intersection 2.0, a combination of AI ultra-low light camera, radar, ITS800 edge computing node and intersection HD map, which is applicable to crossroads, T/X/Y-shaped intersections and super large intersections. Based on its holographic perception solutions, Huawei will create holographic road section solutions that enable convergence and access, analysis and communication capabilities at intersections and roadsides via edge computing units, and connect traffic signals and vehicle communication units to lay the foundation for CVIS services such as accurate public transit and driving assistance.

Baidu: Baidu ACE Intelligent Intersection Solution launched in March 2021 enables perception of all elements including road vehicles, roads, pedestrians, environments and traffic incidents, with perception and computing devices (camera, fisheye camera, LiDAR, edge computing unit, etc.) deployed at the roadside. The solution integrating with Baidu Map data delivers a data detection accuracy of over 97%. ACE Smart Intersection is an application of Baidu ACE Smart Traffic Engine (a full-stack intelligent transportation solution that integrates vehicle, infrastructure and pedestrian) in the intersection scenario.

In Baidu ACE Intelligent Intersection Solution, devices like camera, LiDAR, communication equipment and edge computing unit are customized by Baidu with its ecological partners.

IDPT: the deep fusion of raw data from cameras, LiDARs, radars, and radar video all-in-ones enables 360° image-level holographic perception around the clock in all weather conditions, offering the longest detection range of up to 500m and more reliable data for urban intersections.

In addition, Hikailink Technology achieves holographic intersection perception with radar, camera, and image-level solid-state LiDAR; OriginalTek deployed BotEye™ holographic perception devices in the test park where the 2020 C-V2X Cross-industry & Large-scale Pilot Plugfest was held.

The roadside perception market will be worth RMB20 billion in 2025

Intelligent roadside perception will firstly cover highways and urban intersections. The official statistics show that China has 149,600km highways in all, with the overall density of road networks averaging 6.1km/km2 and the total urban construction areas reaching 21,000 km2 in 36 major cities.

On our estimate, China's intelligent roadside perception equipment market (including RSU, camera, radar, LiDAR, and radar video all-in-one) will be valued at RMB20 billion or so in 2025. Camera and radar will be still mainstream devices for roadside perception, while radar video all-in-one and LiDAR will gather pace.

"Smart Road-Roadside Perception Industry Report, 2021" highlights the following:

  • Smart road industry (favorable policies, industry standards, industrial planning);
  • Intelligent roadside perception market (size, pattern);
  • Status quo and trends of key technologies (HD camera, radar, radar video all-in-one, LiDAR, multi-sensor fusion, etc.);
  • Deployment cases of roadside perception devices on highways and at urban intersections;
  • Major roadside perception system integrators and equipment suppliers.

Table of Contents

1 Guiding Policies and Technical Standards for Roadside Perception

  • 1.1 Guiding Policies for Smart Roads
    • 1.1.1 National Guiding Policies for Intelligent Transportation
    • 1.1.2 Levels of Intelligence Technology for Smart Highways
    • 1.1.3 Correspondence of Levels between Smart Highway Technology and Autonomous Driving
    • 1.1.4 Development Plan for Smart Highways
    • 1.1.5 Construction of 5G Smart Highways
  • 1.2 Intelligent Roadside Standard System Construction
    • 1.2.1 The Latest Progress in Formulation of Roadside Standards during 2020-2021
    • 1.2.2 Intelligent Roadside Standard System Construction
    • 1.2.3 Standardization Process of CVIS-based Automated Driving during 2020-2024
    • 1.2.4 Evaluation Content and Standards of Smart Highway Pilot Projects
    • 1.2.5 Standards for Infrastructure for Smart Highway Projects are Gradually Improved
    • 1.2.6 Overall Industrial Framework of Smart Highway Construction

2 Roadside Perception Market Size and Development Pattern

  • 2.1 Development Context for Intelligent Roadside Perception Market
    • 2.1.1 New Intelligent Transportation Systems Based on Vehicle-infrastructure-cloud Cooperation
    • 2.1.2 Role of CVIS in Intelligent Transportation
    • 2.1.3 Application of Roadside Intelligent Perception in Intelligent Transportation
  • 2.2 Intelligent Roadside Perception Market Size
    • 2.2.1 Market Size: Estimated Data and Assumptions
    • 2.2.2 Demand for Highway Roadside Perception Equipment, 2020-2025E
    • 2.2.3 Highway Roadside Perception Equipment Market Size, 2020-2025E
    • 2.2.4 Demand for Urban Intersection Perception Equipment, 2020-2025E
    • 2.2.5 Market Size of Urban Intersection Perception Equipment, 2020-2025E
    • 2.2.6 China's Roadside Perception Market Size, 2020-2025E
    • 2.2.7 Potential Market Space of Roadside Intelligence
  • 2.3 Competitive Pattern of Intelligent Roadside Perception Market
    • 2.3.1 Intelligent Roadside Perception Industry Chain
    • 2.3.2 Roadside Perception Industry Map
    • 2.3.3 Roadside Perception Solutions of Major Providers
    • 2.3.4 Roadside Perception Product Layout of Major Providers
  • 2.4 Exploration of Roadside Perception Business Models
    • 2.4.1 Problems that Need to be Solved to Build Mature Business Models
    • 2.4.2 Path of Exploring Roadside Intelligent Equipment Business Models
    • 2.4.3 Exploring Roadside Perception Data Operation Models

3 Key Roadside Perception Technologies and Development Trends

  • 3.1 Key Roadside Perception Technologies
    • 3.1.1 Key Technologies and Infrastructure for Smart Road Construction in China
    • 3.1.2 Construction Elements of 5G CVIS for Public Roads
    • 3.1.3 Core Construction Elements of 5G CVIS for Public Roads (Hardware Devices)
    • 3.1.4 Role of Intelligent Roadside Perception Equipment
    • 3.1.5 Intelligent Roadside Perception Solutions
    • 3.1.6 Intelligent Roadside Perception Systems
  • 3.2 Technical Challenges in Roadside Perception
    • 3.2.1 Key Technical Challenge in Roadside Perception-Multi-sensor Fusion
    • 3.2.2 Long-lasting Problems in Roadside Perception Construction
  • 3.3 Camera
    • 3.3.1 Role of Intelligent Analysis of Roadside Video
    • 3.3.2 Advantages of Cameras in Roadside Perception
    • 3.3.3 Pattern of Roadside Camera Suppliers
    • 3.3.4 Comparison of Products between Major Suppliers
    • 3.3.5 Vision and AI Empower Roadside Cameras
    • 3.3.6 Development Trend of Roadside Camera Industry: End-Cloud Cooperation
  • 3.4 Radar Technology
    • 3.4.1 Application Advantages of Radar in Roadside Perception
    • 3.4.2 Pattern of Roadside Radar Suppliers
    • 3.4.3 Comparison of Product Technology between Major Suppliers
    • 3.4.4 4D Radar Empowers Roadside Perception
  • 3.5 LiDAR Technology
    • 3.5.1 Role of Roadside LiDAR
    • 3.5.2 Advantages of LiDAR in Roadside Perception
    • 3.5.3 Deployments of Major Vendors in Roadside LiDAR
    • 3.5.4 Priority Application Scenarios of LiDAR in Roadside Perception
    • 3.5.5 Roadside LiDAR Market Opportunities
  • 3.6 Radar Video All-in-one Technology
    • 3.6.1 Advantages of Radar Video All-in-one in Roadside Perception
    • 3.6.2 Pattern of Radar Video All-in-one Suppliers
    • 3.6.3 Deployments of Major Vendors in Radar Video All-in-one/Radar Video Integration
    • 3.6.4 Radar Video Integration Holds a Trend for Roadside Perception
  • 3.7 Trends of RSU Technology
    • 3.7.1 Deployment Trends of RSU
  • 3.8 Development Trends of Roadside Perception
    • 3.8.1 Software and Hardware Integration
    • 3.8.2 Multi-sensor Fusion
    • 3.8.3 Multi-sensor Fusion for Holographic Perception

4 Application Deployment Cases of Roadside Perception

  • 4.1 Exploration of Roadside Perception Application Scenarios
    • 4.1.1 Ideas for Selection of Application Scenarios in Early Commercialization
    • 4.1.2 Exploration of Scenario-based Application Models
    • 4.1.3 Optimal Application Scenario in Early Stage-Highway
    • 4.1.4 Optimal Application Scenario in Early Stage-Urban Road
    • 4.1.5 Optimal Application Scenario in Early Stage-Closed Park
    • 4.1.6 Commercial Deployment Process of Roadside Intelligent Devices
  • 4.2 Application Cases of Highway Roadside Perception
    • 4.2.1 Status Quo of Smart Highways
    • 4.2.2 Deployment Principles of Roadside Perception Equipment on Smart Highways
    • 4.2.3 Hangzhou-Shaoxing-Ningbo Smart Expressway
    • 4.2.4 Roadside Equipment Deployed on Hangzhou-Shaoxing-Ningbo Smart Expressway
    • 4.2.5 Shanghai-Hangzhou-Ningbo Expressway
    • 4.2.6 Yanqing-Chongli Expressway
    • 4.2.7 Deployment Plan of Roadside Perception Equipment on Yanqing-Chongli Expressway
    • 4.2.8 Solution Providers of Yanqing-Chongli Expressway
    • 4.2.9 Roadside Equipment Suppliers of Yanqing-Chongli Expressway
    • 4.2.10 Hubei Ezhou Airport Expressway
  • 4.3 Application Cases of Roadside Perception on Urban Roads
    • 4.3.1 Smart Intersection
    • 4.3.2 Major Smart Intersection Solutions
    • 4.3.3 Intersection Perception Solution of Beijing Yizhuang
    • 4.3.4 Smart Intersection Solution in Chuxiong City, Yunnan
    • 4.3.5 Smart Pole
    • 4.3.6 Advantages of Smart Pole
    • 4.3.7 Smart Public Transit

5 Roadside Perception System Solution Providers

  • 5.1 Huawei
    • 5.1.1 Huawei Urban Road Holographic Intersection Solution
    • 5.1.2 Advantages of Holographic Intersection Solution
    • 5.1.3 AI Ultralow Light Camera
    • 5.1.4 Application of Holographic Intersection Solution
    • 5.1.5 Huawei Roadside CVIS Solution
  • 5.2 Dahua Technology
    • 5.2.1 Profile
    • 5.2.2 Highway Video Surveillance Solutions
    • 5.2.3 Radar Video All-in-One
  • 5.3 Hikvision
    • 5.3.1 Roadside Intelligent Perception Equipment
    • 5.3.2 Radar Video Perception Equipment
  • 5.4 Hikailink
    • 5.4.1 Profile
    • 5.4.2 Smart Road Solution for Intelligent Vehicles
    • 5.4.3 CVIS Solution
    • 5.4.4 Highway Scenario Roadside Perception Deployment Solution
    • 5.4.5 Roadside Perception Products
  • 5.5 China TransInfo
    • 5.5.1 Profile
    • 5.5.2 R&D System
    • 5.5.3 R&D Layout
    • 5.5.4 Roadside Equipment
    • 5.5.5 Roadside Equipment: Uniview Camera
    • 5.5.6 Roadside Perception Solutions
    • 5.5.8 Roadside Intelligent Perception Demonstration Cases
  • 5.6 eHualu
    • 5.6.1 Profile
    • 5.6.2 Intelligent Roadside Perception Equipment
  • 5.7 Gosuncn
    • 5.7.1 Profile
    • 5.7.2 Intelligent Transportation Layout
    • 5.7.3 Roadside Intelligent Perception Solution
    • 5.7.4 MEC
    • 5.7.5 RSU
    • 5.7.6 Roadside Perception Application
  • 5.8 Baidu
    • 5.8.1 CVIS Open Source Solution
    • 5.8.2 Apollo 6.0 Platform First Introduced Object-level Fusion of Vehicle Perception and Roadside Perception
    • 5.8.3 ACE Intelligent Intersection Solution
    • 5.8.4 Roadside Perception Application Cases
  • 5.9 ZTE
    • 5.9.1 Roadside Perception Business
    • 5.9.2 MEC Business
    • 5.9.3 Cloud Control Platform Business
  • 5.10 SenseTime Technology
    • 5.10.1 Automated Driving Layout
    • 5.10.2 Roadside Perception Solution
  • 5.11 Vanjee Technology
    • 5.11.1 Profile
    • 5.11.2 Intelligent Roadside Equipment
    • 5.11.3 Parameters of Intelligent Roadside Equipment Product
    • 5.11.5 Roadside Smart Base Station
    • 5.11.6 Roadside 3D LiDAR
    • 5.11.7 Roadside Monitoring Status of Roadside 3D LiDAR
    • 5.11.8 V2X+3D LiDAR Roadside Intelligent Perception Solution
    • 5.11.9 Features of Roadside Perception Products
    • 5.11.10 Roadside Intelligent Perception Demonstration Cases
  • 5.12 Changsha Intelligent Driving Institute (CiDi)
    • 5.12.1 Profile
    • 5.12.2 Products & Solutions
    • 5.12.3 "V2X + Bus Smart Mobility" Solution
    • 5.12.4 "V2X + Smart Highway" Solution
    • 5.12.5 "V2X + Mining Area" Solution
    • 5.12.6 V2X Cases
    • 5.12.7 Roadside Perception Application Cases
  • 5.13 OriginalTek
    • 5.13.1 Profile
    • 5.13.2 Holographic Perception Solution
    • 5.13.3 Radar Video All-in-One
  • 5.14 The Institute of Deep Perception Technology (IDPT)
    • 5.14.1 Holographic Perception System Solution for CVIS: Deep Sea-1
    • 5.14.2 Roadside Perception Radar
    • 5.14.3 Radar Video All-in-One: Smart Sea-3
  • 5.15 Others
    • 5.15.1 Roadside Perception Solutions of Beijing Juefei Technology
    • 5.15.2 Roadside Perception Solutions of Continental

6 Roadside Perception Equipment Suppliers

  • 6.1 Hurys
    • 6.1.1 Profile
    • 6.1.2 Features of Traffic Radar Products
    • 6.1.3 Roadside Intelligent Perception Solution
  • 6.2 Raysun Radar
    • 6.2.1 Profile
    • 6.2.2 Parameters of Roadside Perception Products
    • 6.2.3 Radar Video All-in-One
    • 6.2.4 V2X Holographic Road Surface Perception Solution
    • 6.2.5 Application Cases
  • 6.3 Beijing TransMicrowave Technology Co., Ltd.
    • 6.3.1 Roadside Intelligent Perception Equipment
    • 6.3.2 Roadside Speed Measuring Radar
  • 6.4 DeGuRoon
    • 6.4.1 Profile
    • 6.4.2 Roadside Radar Video All-in-One
    • 6.4.3 Omnidirectional Radar
    • 6.4.4 Edge Computing Server
    • 6.4.5 Roadside Perception Equipment Application
  • 6.5 Muniu Technology
    • 6.5.1 Roadside Radar
    • 6.5.2 Application Scenarios of Roadside Radar
  • 6.6 Costone Technology
    • 6.6.1 Radar Video All-in-One
    • 6.6.2 Application of Radar Video All-in-One to Highway Incident Detection
    • 6.6.3 Application of Radar Video All-in-One to Urban Road Signal Control
  • 6.7 Nanoradar
    • 6.7.1 Roadside Radar
    • 6.7.2 Radar Video All-in-One
  • 6.8 ZTITS
    • 6.8.1 Profile
    • 6.8.2 Product System
    • 6.8.3 Roadside Video Edge Computing Equipment
  • 6.9 Ouster
    • 6.9.1 Roadside LiDAR
    • 6.9.2 CVIS Solution Cooperated with LiangDao Intelligence
  • 6.10 Radium Smart
    • 6.10.1 Profile
    • 6.10.2 Roadside Perception Solution
  • 6.11 Leishen Intelligent Systems
    • 6.11.1 Profile
    • 6.11.2 Roadside LiDAR
  • 6.12 Other
    • 6.12.1 Roadside Perception Radar of Chuhang Technology
    • 6.12.2 Roadside Radar Products of Oculii
    • 6.12.3 Roadside Perception Products of LiangDao Intelligence
    • 6.12.4 5G Cloud-network Integrated All-in-one of Inspur
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