China Roadside Edge Computing Industry Report, 2022

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Roadside Edge Computing Research: how edge computing enables intelligent connected vehicles?

Policies and standards for roadside edge computing are implementing one after another, favoring the boom of the industry.

In April 2020, the National Development and Reform Commission defined the scope of "new infrastructures" for the first time, which includes new infrastructures such as cloud computing and intelligent computing centers; in February 2021, the Ministry of Transport of China issued the "National Comprehensive Three-dimensional Transportation Network Planning Outline", suggesting promoting the digitization and connection of transportation infrastructures, deploying traffic perception systems in an all-round way, and facilitating the application of autonomous driving and vehicle-infrastructure cooperation.

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These policies facilitate the steady development of intelligent transportation industry, and help it transition from the information phase to the connection phase, and finally to the intelligent road phase. The powerful roadside perception, edge computing, network communication, and cloud control technologies provide support for efficient fully automated driving.

In addition to benign policies, the standards concerning roadside edge computing get improved:

In December 2021, the exposure draft of the group standard "Edge Computing Gateway Communication Interface Standard of Intelligent Road" was released. It specifies the communication interface requirements for the southbound heterogeneous device access and the northbound unified access platform of the intelligent road edge computing gateway.
In March 2022, the group standard "General Specification for Traffic Information Holographic Acquisition System of Road Intersection" jointly prepared by Huawei, Beijing MapABC Technology, Beijing Chinasoft Zhengtong Information Technology, Shenzhen Traffic Police Bureau, and Changzhou Traffic Police Division took into effect. This standard indicates that edge computing units should be uniformly deployed at intersections; the videos, images and structured data collected in all directions should be managed and calculated to offer the fusion information of intersections which will be uploaded to the business application platform.

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Based on the construction of standardized edge cloud, the standardized cooperation between the urban center cloud and the edge cloud will make a further improvement in the future, in a bid to realize the intercommunication and interconnection between edge cloud devices, and facilitate the unified management on large scale and the application of "terminal-edge-cloud" cooperation.

In the new technology architecture for intelligent roads, "edge computing" is being applied to more scenarios.

Intelligent transportation is transforming from informatization to intelligent connection. The construction of intelligent roads serves as an important part in intelligent transportation. At present, in China more than 20 provinces have completed the renovation and construction of over 40 intelligent highways, and "cloud-network-edge-terminal" is becoming a new-generation technology architecture for intelligent roads. In this new technology architecture, the "edge" is playing a more prominent role and making its way into more application scenarios.

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Edge devices with certain computing power can ease the pressure of cloud computing at the roadside. In addition, edge computing can cut the transmission time of data in the network, simplify the network structure, and also enables precise perception of traffic conditions. Edge computing thus has a decided advantage in construction of intelligent roads, especially in the telematics environment.

(1) Application of edge computing in vehicle-infrastructure cooperation

Through the lens of the three delivery modes of edge computing, 5G multi-access edge computing (MEC) best fits the intelligent transportation sector. As MEC is introduced into vehicle-infrastructure cooperation, edge computing devices allows direct, real-time reception of localized data from in-vehicle terminals and roadside sensors, analyze the data, and transmit the analysis results to other connected vehicles in the adjacent area with an ultralow latency. The whole process can be completed in milliseconds.

The new-generation vehicle-infrastructure cooperation technology architecture enables fusion application of MEC, C-V2X, 5G and more, delivering far stronger end-to-end communication capabilities. This architecture is also a solution to the problem of high construction complexity and costs posed by wired backhaul of the roadside data. Moreover, when the penetration rate of V2X equipment is not high enough, it provides N2V services for ordinary vehicles without OBU installed via the 4G/5G network, revving up the application and promotion of vehicle-infrastructure cooperation.

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(2) Application of edge computing in HD map

The use of HD maps helps to achieve the application of L4/L5 autonomous driving, but still faces some challenges such as real-time dynamic updates. The introduction of MEC is a better way to solve these problems.

The MEC carrying HD maps enables rapid distribution of dynamic maps. Combined with 5G network slicing technology, it allows a vehicle to acquire HD map data in real time and save much storage space of the head unit.

(3) Application of edge computing in smart park

The introduction of edge computing into a smart park not only enables perception, monitoring, analysis, control, and integration of the resources at all key links of the park, but also realizes vehicle-infrastructure cooperation there.

Shougang Winter Olympics Park has built a 5G+C-V2X based cooperative vehicle-infrastructure system (CVIS) that enables global traffic situational awareness. The facility deploys sensing devices like cameras and radars, and connects intelligent devices such as signal lights on both sides of the trunk road and key intersections in the park, in a bid to achieve global traffic information collection. It also deploys perception-based multi-source heterogeneous fusion perception algorithms inside the roadside MEC, develops and optimizes algorithms for Winter Olympics scenarios, which enable traffic video detection and tracking in weather conditions, e.g., heavy snow and fog.

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(4) Application of edge computing in highway scenario

At the highway entrance ramp, traffic accidents are prone to happen when vehicles merge. Intelligent perception devices deployed at the ramp such as cameras and radars acquire vehicle movement trajectories and traffic flow data, then the deployed MEC devices are used for perception fusion and vehicle trajectory prediction, and eventually, the prediction results are distributed to the connected vehicles, through which capabilities including collision warning and ramp control in the merging area, lane change assistance, and vehicle speed guidance are enabled.

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The tremendous derived value of the industry brings about competition for layout among companies.

The large-scale construction of intelligent roads is accompanied by increasing companies deploying edge computing. Players of chips, computing platforms, software, communication and cloud services among other fields are working to explore the roadside edge computing market. Among them, cloud service providers with their superiorities in cloud computing technology tend to apply the cloud computing technology to the edge side. For example, Chinese giants such as BAT (Baidu, Alibaba and Tencent) have begun to sink their computing capabilities into the edge side since 2018, racing to roll out their edge computing products.

In terms of product layout, the three major operators (China Mobile, China Telecom and China Telecom) have made comprehensive deployments in edge computing, cloud control platform, and communication technology to connect the edge computing-network communication-cloud control links; in addition to edge computing units, Internet companies like Huawei, Alibaba, and Tencent, as well as some conventional roadside equipment suppliers also deploy roadside perception units to build a complete roadside perception-computing system solution.

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Huawei: the roadside perception units and ITS800 edge computing nodes used in the holographic intersection solution are all independently developed by Huawei.

At present, Huawei has built a complete intelligent road industry chain ecosystem, with R&D and production capabilities covering the whole chain from chip, edge computing and roadside perception to cloud platform. The Kunpeng + openEuler software-hardware cooperative edge computing platform uses Huawei's self-developed processor Kunpeng 920, TaiShan200 edge server (model: 2280E) and openEuler server operating system.

Huawei's edge computing unit features iteration and upgrade of algorithm cloud edge, real-time analysis and generation of structural data of road conditions, and access to V2X real-time service data.

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Alibaba Cloud: in 2021 it introduced a new "Cloud-Edge Integrated Small Station" where Neuro edge computing terminal, edge computing server, traffic big data all-in-one, and intelligent vehicle screen for vehicle-infrastructure cooperation help to reduce much of the cost of intelligent road projects and increase the return on investment. Among them, the Neuro edge computing terminal with small size boasts multiple capabilities and also supports cloud management.

Alibaba Cloud has deployed Neuro edge computing terminals on the Chengdu Second Ring Road Expressway and Chengdu-Yibin Expressway. The way to deploy a pole every 800 meters needs fewer devices arranged and saves the construction cost as much as possible.

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In addition, chip and computing platform providers have also launched roadside-related edge computing products.

Black Sesame Technologies: the company has unveiled FAD Edge, a roadside perception computing platform for vehicle-infrastructure cooperation scenarios. Based on Huashan No.2 A1000 autonomous driving chip (later to be upgraded to A1000 Pro), FAD Edge applies cloud computing to the edge side, and completes most of computing tasks at the edge computing nodes to meet the ultralow latency needs of vehicle-infrastructure cooperation; in addition, with 58 to 224TOPS computing power, FAD Edge supports multi-channel perception data access and multiple types of sensors; the built-in multi-channel perception device data fusion algorithms can be connected with the V2X system.

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Unlimited AI: the company launched a super roadside fusion domain controller in 2021. As the world's first MEC and RSU integrated design, this product has strong real-time computing power, and is easy to deploy and maintain. With no need to occupy ground and municipal space separately, it reduces 75% engineering construction cost and 80% maintenance fees, remaining outstanding in mass adoption.

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China Roadside Edge Computing Industry Report, 2022 highlights the following:
Research on status quo of smart city and intelligent transportation industry, main intelligent transportation solutions, etc.;
Research on edge computing (overview), computing modes, status quo of roadside edge computing standards, market size, status quo of industry chain, necessity of roadside application, etc.;
Research on the connection of roadside edge computing with network communication, the connection with cloud control, etc.;
Research on the main application directions of roadside edge computing (including intelligent highway, smart intersection, smart park, and parking lot), etc.;
Research on main roadside edge computing devices and solution providers (main roadside computing devices, overall roadside computing solutions and application, etc.).

1 Smart City and Intelligent Transportation Industry
1.1 Status Quo of Smart City
1.1.1 Foreign Policies for Supporting Smart City Development
1.1.2 China’s Policies Concerning Smart City
1.1.3 Smart City Market Size
1.1.4 Smart City Panorama
1.1.5 Challenges in Smart City Construction
1.1.6 Smart City in the Context of New Infrastructures
1.1.7 Smart City Architecture in the Context of New Infrastructures
1.1.8 Application of Computing Platform in Smart City (1)
1.1.9 Application of Computing Platform in Smart City (2)
1.2 Intelligent Transportation System Architecture
1.2.1 Intelligent Transportation Industry Is Supported by Policies
1.2.2 Intelligent Transportation Market Size
1.2.3 Intelligent Transportation Application Cases: Digital Road
1.2.4 Intelligent Transportation Application Cases: Key Transportation Hub Control
1.2.5 Intelligent Transportation Application Cases: Highway Control
1.2.6 Intelligent Transportation Application Cases: Traffic Emergency Control
1.3 Intelligent Transportation Architecture
1.3.1 Key Intelligent Transportation Technologies
1.3.2 Intelligent Transportation System Architecture
1.3.3 Intelligent Transportation Hardware Platform
1.3.4 Intelligent Transportation Software Platform
1.3.5 Intelligent Transportation Software Platform: Central Cloud Platform
1.3.6 Intelligent Transportation Software Platform: MEC Edge Cloud Platform
1.3.7 Intelligent Transportation Data Communication
1.3.8 Intelligent Transportation Network Architecture
1.3.9 Intelligent Transportation Safety Measures
1.4 Edge Computing in Intelligent Transportation
1.4.1 Introduction of Intelligent Transportation Framework to the Edge Side (1)
1.4.2 Introduction of Intelligent Transportation Framework to the Edge Side (2)
1.4.3 Role of “Edge” in Intelligent Highways (1)
1.4.4 Role of “Edge” in Intelligent Highways (2)
1.4.5 Role of “Edge” in Intelligent Highways (3)
1.4.6 Application of "Edge" in Intelligent Highway (1)
1.4.7 Application of "Edge" in Intelligent Highway (2)

2 Status Quo of Intelligent Road Edge Computing Market
2.1 Overview of Edge Computing
2.1.1 Edge Computing Concept
2.1.2 Difference between Edge Computing and Cloud Computing
2.1.3 Edge Computing System Architecture (1)
2.1.4 Edge Computing System Architecture (2)
2.1.5 Edge Cloud Management Platform
2.1.6 Edge Computing Security Architecture
2.1.7 Edge Computing Layout
2.1.8 Where to Deploy Edge Computing
2.2 Classification of Edge Computing Modes
2.2.1 Three Delivery Models of Edge Computing
2.2.2 Challenges in Different Models
2.2.3 MEC Is the Preferred Choice for Intelligent Transportation Scenarios
2.3 Status Quo of Roadside Edge Computing Standards
2.3.1 Edge Computing Standard System
2.3.2 Roadside Computing Standards Are in Urgent Need of Improvement
2.3.3 The Group Standard "Holographic Intersection" was Released
2.3.4 Jiangsu Implements the Local Standard "Guidelines of Roadside Facilities Setting for Vehicle-Infrastructure Coordination"
2.3.5 Roadside Edge Computing Standards Get Improved: Edge Computing Gateway Communication Interface Standard of Intelligent Road (1)
2.3.6 Roadside Edge Computing Standards Get Improved: Edge Computing Gateway Communication Interface Standard of Intelligent Road (2)
2.3.7 Trend for Standard Construction: Improve Cloud-Edge Cooperation Standards
2.4 Roadside Edge Computing Market Size
2.4.1 Edge Computing Business Models
2.4.2 Edge Computing Market Size
2.4.3 China’s Highway MEC Device Market Size
2.4.4 China’s Unban Intersection MEC Device Market Size
2.4.5 China's Intelligent Road MEC Device Market Size
2.5 Status Quo of Roadside Intelligent Computing Industry Chain
2.5.1 Edge Computing Industry Chain
2.5.2 Edge Computing Industry Chain Map
2.5.3 Main Players of Edge Computing
2.5.4 Edge Computing Industry Pattern
2.5.5 Competitive Factors of Edge Computing Industry
2.5.6 Cloud Service Providers Work towards Penetration into the Edge
2.5.7 Competitive Landscape of Roadside Edge Computing Market
2.5.8 Roadside Computing Product Line Layout of Main Manufacturers (1)
2.5.9 Roadside Computing Product Line Layout of Main Manufacturers (2)
2.5.10 Roadside Edge Computing Chip Products (1)
2.5.11 Roadside Edge Computing Chip Products (2)
2.5.12 Roadside Edge Computing Chip Products (3)
2.5.13 Roadside Edge Computing Platform Products of Main Suppliers (1)
2.5.14 Roadside Edge Computing Platform Products of Main Suppliers (2)
2.5.15 Roadside Edge Computing Platform Products of Main Suppliers (3)
2.6 Necessity of Edge Computing Application
2.6.1 Edge Computing Is A Digital Infrastructure
2.6.2 Edge Computing Has A Decided Advantages in Smart City
2.6.3 Edge Computing Is the Nerve Ending of Intelligent Transportation
2.6.4 Introduction of Edge Computing Is An Important Way to Achieve Vehicle-Infrastructure Cooperation (1)
2.6.5 Introduction of Edge Computing Is An Important Way to Achieve Vehicle-Infrastructure Cooperation (2)
2.6.6 5G+MEC+V2X Will Accelerate the Application of Vehicle-Infrastructure Cooperation
2.6.7 Edge Computing Is A Prerequisite for L4 Autonomous Driving
2.6.8 Fusion Application Trend of MEC

3 Connection of Roadside Computing with Each Side
3.1 Roadside Computing and Communication Network
3.1.1 Challenges Posed by Edge Computing to the Existing Network System
3.1.2 Edge Computing Network Technology System
3.1.3 Edge Computing Network Technologies: Access Network (1)
3.1.4 Edge Computing Network Technologies: Access Network (2)
3.1.5 Edge Computing Network Technologies: Intranet
3.1.6 Edge Computing Network Technologies: Internet
3.1.7 Computing Network
3.1.8 Deployment of Edge Computing in 4G Network
3.1.9 Deployment of Edge Computing in 5G Network
3.1.10 Edge Computing Networking
3.1.11 Communication Computing at Telematics Edge Nodes
3.1.12 Perception-Computing-Communication Fusion
3.1.13 Computing and Communication for Smart Intersection
3.2 Roadside Computing and Cloud Control
3.2.1 Connection of Edge Computing with Cloud and Terminals
3.2.2 Cloud Control System
3.2.3 Fusion of Edge Computing and Cloud
3.2.4 Edge-Cloud Cooperation Framework (1)
3.2.5 Edge-Cloud Cooperation Framework (2)

4 Main Application Directions of Roadside Computing
4.1 Application of Edge Computing
4.1.1 Application of Edge Computing in Smart City (1)
4.1.2 Application of Edge Computing in Smart City (2)
4.1.3 Application of Edge Computing in Smart City (3)
4.1.4 Application of Edge Computing in Intelligent Transportation (1)
4.1.5 Application of Edge Computing in Intelligent Transportation (2)
4.1.6 Application of Edge Computing in Telematics (1)
4.1.7 Application of Edge Computing in Telematics (2)
4.1.8 Application of Edge Computing in Telematics (3)
4.1.9 Application of Edge Computing in Smart Park
4.1.10 Application of Edge Computing in Holographic Intersection (1)
4.1.11 Application of Edge Computing in Holographic Intersection (2)
4.1.12 Application of Edge Computing in HD Map Distribution
4.2 Application of Edge Computing in Intelligent Highway
4.2.1 Comparison between Main Roadside Edge Computing Application Cases
4.2.2 Intelligent Highway Solutions of China TransInfo
4.2.3 Deployment Scheme on Yanqing-Chongli Expressway (1)
4.2.4 Deployment Scheme on Yanqing-Chongli Expressway (2)
4.2.5 Edge Device Deployment Scheme on Hangzhou–Ningbo Expressway
4.3 Application of Edge Computing in Smart Intersection
4.3.1 Comparison between Main Roadside Edge Computing Application Cases
4.3.2 Application of Edge Computing in 4D Reality Visualization Management Platform
4.3.3 Huawei Holographic Roadside Hardware
4.3.4 Smart Intersection Solution in Yizhuang, Beijing
4.3.5 Smart Intersection in Chuxiong Yi Autonomous Prefecture, Yunnan
4.4 Application of Edge Computing in Enclosed Park
4.4.1 Telematics System in Shougang Winter Olympics Park: Deployment Scheme
4.4.2 Telematics System in Shougang Winter Olympics Park: Communication Network
4.4.3 Telematics System in Shougang Winter Olympics Park: Device Deployment
4.4.4 Telematics System in Shougang Winter Olympics Park: Control Platform
4.5 Application of Edge Computing in Parking Lot
4.5.1 Application of Edge Computing in Smart Parking
4.5.2 ZTE Intelligent Indoor Parking Solution
4.5.3 Tokyo Institute of Technology’s Edge Computing + AI Smart Parking Model

5 Roadside Computing Software, Hardware and Platform Suppliers
5.1 Unlimited AI
5.1.1 Profile
5.1.2 MEC and RSU Integrated Roadside Computing Units (1)
5.1.3 MEC and RSU Integrated Roadside Computing Units (2)
5.2 Cookoo
5.2.1 Edge Computing Developer Platform
5.2.2 AI Roadside Edge Computing: ADU502
5.2.3 AI Roadside Edge Computing: ADU503
5.2.4 AI Roadside Edge Computing: ADU505
5.2.5 AI Roadside Edge Computing: Application Scenarios (1)
5.2.6 AI Roadside Edge Computing: Application Scenarios (2)
5.2.7 AI Roadside Edge Computing: Application Scenarios (3)
5.2.8 Road Perception System for Vehicle-Infrastructure Cooperation: AutoITS-J1
5.3 Black Sesame Technologies
5.3.1 Enabling both Vehicle Side and Road Side
5.3.2 Roadside Perception Computing Platform
5.3.3 Roadside Perception Computing Platform Technology Trends
5.3.4 Roadside Edge Computing Solutions for Intelligent Highways
5.4 Cambricon
5.4.1 Edge Computing Module: MLU220
5.4.2 Application of Edge Computing Modules
5.5 CICT Mobile
5.5.1 "5G+AI" Integrated Gateway: RDC5521
5.5.2 "5G+AI" Integrated Gateway: RDC5002
5.5.3 Released 5G+AI Edge Computing Roadside Fusion Gateway Together with Horizon Robotics
5.5.4 5G+AI Edge Computing Roadside Fusion Gateway Chips
5.6 Huawei
5.6.1 Building an Intelligent Computing Platform
5.6.2 Intelligent Edge Platform: Architecture
5.6.3 Intelligent Edge Platform: Security
5.6.4 Kunpeng + openEuler Cooperative Software and Hardware Edge Computing Platform: Kunpeng Processor
5.6.5 Kunpeng + openEuler Cooperative Software and Hardware Edge Computing Platform: Edge Server
5.6.6 Kunpeng + openEuler Cooperative Software and Hardware Edge Computing Platform: Server Operating System
5.6.7 Kunpeng + openEuler Cooperative Software and Hardware Edge Computing Platform: Application
5.7 Inspur
5.7.1 Profile
5.7.2 Roadside Computing Units (1)
5.7.3 Roadside Computing Units (2)
5.7.4 Edge Computing Server
5.8 Gosuncn
5.8.1 Intelligent Transportation Layout
5.8.2 Edge Computing Products (1)
5.8.3 Edge Computing Products (2)
5.9 Vanjee Technology
5.9.1 Edge Computing Products
5.9.2 Edge Computing Application: Smart Base Station
5.9.3 Edge Computing Application: Intelligent Roadside Perception Solution
5.10 ZTITS
5.10.1 Product System
5.10.2 Roadside Video Edge Computing Devices
5.11 Talkweb Information
5.11.1 AI Edge Server Products
5.11.2 Intelligent Highway Cloud-Edge Cooperation Solution
5.12 TZTEK Technology
5.12.1 AI Edge Computing Platform: GEAC91S Series
5.12.2 Enter Intelligent Transportation by Starting with Edge Computing
5.13 CiDi
5.13.1 Edge Computing Products
5.13.2 Edge Computing Application: Intelligent Highway
5.14 LiangDao Intelligence
5.14.1 Edge Computing Integrated Roadside Perception Fusion System
5.15 DeGuRoon
5.15.1 Edge Computing Server
5.16 AICC
5.16.1 Basic Software for Vehicle-Cloud Cooperation
5.16.2 Basic Software Architecture for Vehicle-Cloud Computing
5.17 Zhicheng Software
5.17.1 Develop Cloud-Native Edge Computing for Smart Parking
5.17.2 Smart Parking Operating System Based on Cloud-Native Architecture: Overall Architecture
5.17.3 Smart Parking Operating System Based on Cloud-Native Architecture: Edge Side Architecture
5.18 EMQ
5.18.1 Edge Computing Architecture for Vehicle-Infrastructure Cooperation
5.18.2 Edge Computing Architecture for Telematics
5.18.3 Edge Computing Architecture for Intelligent Cockpit

6 Roadside Computing Solution Integrators
6.1 China Unicom
6.1.1 Edge Service Platform Architecture
6.1.2 Edge Service Platform Architecture Design
6.1.3 Strategy of Building Each Layer of Edge Service Platform
6.1.4 Edge Computing Layout
6.1.5 Intelligent Edge Cloud Networking Structure
6.1.6 Intelligent Edge Cloud Functional Architecture (1)
6.1.7 Intelligent Edge Cloud Functional Architecture (2)
6.1.8 Intelligent Edge Cloud Application: Telematics
6.1.9 Intelligent Edge Cloud Application: Autonomous Driving
6.1.10 Intelligent Edge Cloud Application: Vehicle-Infrastructure Cooperation
6.1.11 5G MEC and C-V2X Fusion Test Bed of Changzhou City
6.2 China Mobile
6.2.1 Edge Computing Full Stack Platform System
6.2.2 Edge Computing Operation Platform: ECM
6.2.3 Edge Operating Platform: ECP
6.2.4 Edge Infrastructure: ECI
6.2.5 Edge Computing Open Services
6.2.6 Edge Computing General Platform: OpenSigma
6.2.7 Edge Application Incubation and Implementation Scheme
6.2.8 Industry Practice Cases of Edge Computing: Smart Park
6.2.9 Industry Practice Cases of Edge Computing: Smart Port
6.3 China Telecom
6.3.1 Self-developed Edge Computing
6.3.2 MEC Architecture for FMC
6.3.3 MEC Platform Application Deployment Architecture
6.3.4 MEC Nodes Deployment
6.4 Huawei
6.4.1 New Paradigm of Distributed Cloud × Cloud Native
6.4.2 Cloud-Edge Cooperation Technology
6.4.3 Features of Edge Computing Units
6.4.4 Fusion of Edge Computing Unit and Roadside Perception
6.4.5 Application of Edge Computing Devices: Holographic Intersection
6.5 Alibaba Cloud
6.5.1 Deploy Intelligent Roads
6.5.2 Edge Computing Terminals
6.5.3 Parameters of Edge Computing Terminals
6.5.4 Edge Computing Terminal Architecture
6.5.5 Edge Computing Layout
6.5.6 Building Edge Cloud Nodes Based on Apasra Architecture
6.5.7 Turnkey Software and Hardware Delivery Helps Corporate Customers to Transform
6.6 Tencent
6.6.1 TMEC Platform
6.6.2 TMEC Featured Services: 5G Services
6.6.3 TMEC Featured Services: 5G QoS and Network Slicing
6.6.4 TMEC Featured Services: Video Processing Capability
6.6.5 TKEStack in TMEC Architecture
6.6.6 TKEStack Allows Deployment of TMEC in Different Modes
6.6.7 TMEC-based Vehicle-Infrastructure Cooperation Practice: Telematics Platform
6.6.8 TMEC-based Vehicle-Infrastructure Cooperation Practice: Road Deployment Scheme
6.6.9 Vehicle-Infrastructure Cooperation Platform Ecosystem
6.7 ZTE
6.7.1 Distributed Precision Cloud
6.7.2 Edge Computing Products
6.7.3 Edge Computing Solutions (1)
6.7.4 Edge Computing Solutions (2)
6.7.5 Edge Computing Application: Cloud Control Platform
6.7.6 Edge Computing Application: Indoor Positioning
6.7.7 Edge Computing Application: Automated Parking System
6.7.8 Edge Computing Application: Real-time Risk Warning System at Level Crossings
6.8 CIECC
6.8.1 Main Roadside Products
6.8.2 Multi-scenario Vehicle-Infrastructure Cooperation for Mixed Traffic Flow
6.8.3 Application of Edge Computing in Intelligent Highway: Safety Protection at Tunnel Entrance
6.8.4 Application of Edge Computing in Intelligent Highway: Safety Protection at Merging Area
6.8.5 Application of Edge Computing in Intelligent Highway: Travel Guarantee on Road Sections with Frequent Fog
6.9 China TransInfo
6.9.1 Global Traffic Solution: Omni-T2.0
6.9.2 City-level Dynamic and Static Traffic Integrated Solution
6.9.3 Cloud-Edge-Terminal Technical Solution
6.9.4 Edge Agents
6.9.5 Edge Agent Application (1)
6.9.6 Edge Agent Application (2)
6.10 Hikailink
6.10.1 Edge Computing Products
6.10.2 Edge Computing Application: Vehicle-Road Cooperation Solution
6.10.3 Intelligent Connected Cloud Control Platform

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