Global and China HD Map Industry Report, 2022
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HD maps have been applied on a large scale, spreading from freeways to cities

According to ResearchInChina, more than 100,000 Chinese passenger cars were equipped with HD maps by OEMs in the first half of 2022. OEMs will constantly speed up the installation of HD maps. HD maps were mainly regarded as an option in the past, but now they have been gradually included in the standard configuration of vehicles, such as Li L9, NIO ET7, HiPhi, etc.

HD map 1_副本.png

From the perspective of the layout of OEMs, advanced driver assistance in urban scenarios has become a new hot spot in intelligent field. At present, there are three technical routes for advanced driver assistance in cities:

(1) Pure vision: Companies represented by Tesla mainly rely on cameras, super powerful algorithms, etc. to realize assisted driving in cities. It is reported that Tesla may introduce FSD Beta to Chinese market.

(2) Perception + map: The solution does not depend heavily on pre-made HD maps. It builds real-time HD maps through vision systems in places where there are no HD maps. For example, the LiDAR version of WEY Mocha released by Great Wall in August 2022 adopts Haomo.AI's urban NOH technology with a weak HD map, which require fewer lane-level attributes than regular HD maps.

(3) Multi-sensor fusion + HD map: Companies represented by NIO, Li Auto and Xpeng enhance the intelligent driving experience by making use of HD maps and LiDAR to make up the insufficient computing power.

Xpeng expects to gradually introduce urban NGP functions to users in Guangzhou, Shenzhen, Beijing, Shanghai, Hangzhou and other cities since 2022.

After the launch of urban NGP by Xpeng, the point-to-point autonomous driving has been realized to some extent (except that drivers cannot take their hands off the steering wheel), covering more than 90% of daily driving scenarios including parking lots, cities and freeways.

HD map 2.png

NIO plans to make urban assisted driving possible on models such as ET7 and ET5 equipped with NAD system in 2022. When the driver sets a destination on the navigator, the IVI map shows the start and end sections of NOP. When the vehicle enters the sections, the driver can turn on or off the NOP function through the "Pilot Assist" in the lower left corner of the navigator.

Li L9 equipped with intelligent driving system “Li AD Max” can see navigation and assisted driving in all scenarios.

With the computing power as high as 400TOPS, Avatr 11 equipped with Huawei ADS can secure high-level intelligent driving functions at freeways, urban areas and parking.

BAIC ARCFOX αS HI Advance equipped with Huawei ADS can accomplish autonomous driving on freeways, high-level autonomous driving in urban areas, AVP and other functions.

In terms of mainstream solutions, OEMs except Tesla basically adopt the sensor + map solution, but they have different requirements for map accuracy. As per the development progress of HD maps, urban HD maps face long mileage, surveying and mapping restrictions and update challenges. Therefore, some OEMs consider using SD pro maps for urban assisted driving to avoid HD map elements as much as possible.

Map providers step up the layout of HD maps in urban scenarios

With a higher OEM installation rate of HD maps, the application in urban scenarios has become a new arena. Map players are aggressively deploying urban scenarios, mainly in the following ways:

Faster collection of urban HD map data
The mileage of China's freeways is about 300,000 kilometers, and the mileage of urban roads is close to 10 million kilometers. Mainstream map players have basically completed the collection of HD maps for freeways and urban expressways. Therefore, the production passenger cars equipped with HD maps can realize advanced driver assistance in high-speed scenarios. In the future, map players will make breakthroughs in HD maps for cities to meet the demand of OEMs.

HD map 3_副本.png

Integration of SD maps and HD maps
In high-speed scenarios, map companies can post-match SD maps with HD maps, with a high accuracy rate. However, in urban scenarios, SD maps and HD maps can't be associated in the later stage due to different production processes. Therefore, in order to facilitate advanced driver assistance in cities, map companies have begun to actively deploy the integrated production of SD maps and HD maps.

Baidu has developed SD-HD integrated AI map production platform, which integrates various data production structures and technological processes via a system. It satisfies the standardized and unified model expression of map data with different accuracy levels, thus solving the consistency problem.

For Here, different maps share the same map data, the same specification, and the same database. Here produces three modes of maps - SD, ADAS and HDML with the same standard, production environment and production process, so that they are interrelated by sharing and the same data and standard.

Strict supervision amid pilot application of HD maps

Six cities start HD map pilot application projects
In August, 2022, the General Office of the Ministry of Natural Resources of China issued the “Notice on HD Map Pilot Application Projects of Intelligent Connected Vehicles”. The pilot projects will stage in six cities including Beijing, Shanghai, Guangzhou, Shenzhen, Hangzhou and Chongqing.

The Notice requires the provincial natural resources authorities in these pilot cities to work out pilot implementation plans, timetables and roadmaps in accordance with the deployment of the State Council and the national laws, regulations and policies on surveying, mapping, geographic information management and data security. Besides, they should rationally delineate the pilot scope according to the specific application scenarios of autonomous driving map data.

In August 2022, the Ministry of Transport of China issued "Opinions on HD map construction and other pilot projects of Beijing Baidu Netcom Science Technology Co., Ltd. for the purpose of building a transportation powerhouse". Baidu plans to provide centimeter-level HD map services on freeways and typical urban roads in three to five years, and make its integrated mobility service platform available in about 10 cities.

Strict supervision in HD map field
As China continues to strengthen the security management of geographic information, the Ministry of Natural Resources is intensifying the supervision over the HD map market while opening up pilot cities for application of intelligent connected vehicles.

Tightened supervision on surveying and mapping qualification:
by the end of 2021, a total of 31 companies were approved for a-level electronic navigation map qualification, which is valid for 5 years, many enterprises need to re-apply for A-level electronic navigation map qualification in 2022, and there are 19 companies of A-level mapping qualification for navigation electronic map production that completed the re-examination and renewal in 2022.

HD map 4_副本.png

Subjects of surveying and mapping: In August 2022, the Ministry of Natural Resources clearly pointed out that the following activities should be subject to the "Surveying and Mapping Law of the People's Republic of China": The intelligent connected vehicles installed or integrated with sensors such as satellite navigation and positioning modules, inertial measurement units, cameras and LiDAR collect, store, transmit and process spatial coordinates, images, point clouds, attributes and the like of vehicles and surrounding road facilities during operation, service and road testing.

China's first road HD electronic navigation map quality standard was officially established.
In September 2022, the Road HD Electronic Navigation Maps Quality Specification, recommended by Department of Land and Mapping of the Ministry of Natural Resources and led by Baidu, was officially approved by National Geographic Information Standardization Technical Committee, which is also the first industry standard for road HD electronic navigation map quality specification approved in China. It will solve “What to inspect, how to inspect, how to analyze and evaluate the inspection results, and how to compile the quality report”, which are concerned by map and car companies.

HD map 5_副本.png

Global and China HD Industry Report, 2022 highlights the following:
20120114.gifPolicies, regulations, standards and compliance about HD maps;
20120114.gifHD map market size, market structure, business models, etc.
20120114.gifHD map production technology, update technology, data distribution and fusion technology; the fusion application of HD maps and V2X; the application of HD maps in lane-level positioning, etc.
20120114.gifMain application scenarios of HD maps, such as autonomous passenger cars, automated parking of passenger cars, passenger and cargo transportation by autonomous driving, etc.;
20120114.gifHD map production and update technology, main products and application scenarios of major map companies at home and abroad;
20120114.gifHD map business layout and main technologies of major HD map technology providers at home and abroad.

1 HD Map Policies, Standards and Regulations
1.1 Policies Related to HD Maps
1.1.1 Latest Policy in 2022: Carry Out the Pilot Application of HD Maps for Intelligent Connected Vehicles
1.1.2 Latest Policy in 2022: Ministry of Transport Approves Baidu to Conduct HD Map Pilot
1.1.3 Latest Policy in 2022: Shanghai Accelerates the Innovation and Development of Intelligent Connected Vehicles
1.2 Regulations Related to HD Maps
1.2.1 Foreign Regulations Related to HD Maps
1.2.2 Domestic Regulations Related to HD Maps
1.2.3 Latest Regulation in 2022: Review of Mapping Qualifications for HD Maps Gradually Tightened (1)
1.2.4 Latest Regulation in 2022: Review of Mapping Qualifications for HD Maps Gradually Tightened (2)
1.2.5 Latest Regulation in 2022: Ministry of Natural Resources Clarifies that Automotive Sensors and Intelligent Connected Vehicle Manufacturing are Illegal Mapping Activities (3)
1.2.6 Latest Regulation in 2022: Chongqing Issued HD Map Management Measures for Intelligent Connected Vehicles (4)
1.3 Standards Related to HD Maps
1.3.1 Foreign Map Standard Ecology: Europe (1)
1.3.2 Foreign Map Standard Ecology: Japan (2)
1.3.3 Status Quo of Foreign HD Map Standard Development
1.3.4 Status Quo of China HD Map Standard Customization (Published)
1.3.5 Status Quo of China HD Map Standard Customization (Pre-research)
1.3.6 Progress of China's HD Map Standard: Crowdsourcing Update Standard Gradually Improved
1.3.7 Latest Standard in 2022: "General Specifications for Traffic Information Holographic Acquisition System of Road Intersections" Group Standard Officially Released (1)
1.3.8 Latest Standard in 2022: First Domestic Road HD Electronic Navigation Maps Quality Specification Industry Standard Approved (2) 
1.3.9 Latest Standard in 2022: Domestic Autonomous Parking Map Standard Coming Soon (3)
1.3.10 Latest Standard in 2022: First Provincial Local Standard Focusing on Intelligent Connected Vehicle Maps Launched (4)
1.4 Compliance of HD Map
1.4.1 State Increases Automotive Data Security Control
1.4.2 HD Map Data Compliance Production Process
1.4.3 HD Map Compliance Data Service
1.4.4 HD Map Compliance Development Path: Building a HD Dynamic Map Basic Platform

2 HD Map Market Size and Competitive Pattern
2.1 HD Map Market Size
2.1.1 Estimated Installations of HD Maps in Autonomous Vehicles in China in 2022
2.1.2 Market Size of OEM HD Maps for Passenger Cars in China (1)
2.1.3 Market Size of OEM HD Maps for Passenger Cars in China (2)
2.2 Competitive Landscape of HD Map Market
2.2.1 HD Map Market Pattern
2.2.2 HD Map Market Players (1): Top 10 Domestic Traditional Map Suppliers (1)
2.2.3 HD Map Market Players (1): Top 10 Domestic Traditional Map Suppliers (2)
2.2.4 HD Map Market Players (1): Product Comparison between Major Map Companies
2.2.5 HD Map Market Players (I): Comparison between Three Major Map Producers
2.2.6 HD Map Market Players (2): HD Map Layout of OEMs
2.2.7 HD Map Market Players (2): OEMs Tend to Self-develop HD Maps Instead of Outsourcing
2.2.8 HD Map Market Players (2): The OEMs That Develop Their Own HD Maps Are Facing Difficulties
2.2.9 HD Map Market Players (2): HD Map Layout Cases of OEMs (1)
2.2.10 HD Map Market Players (2): HD Map Layout Cases of OEMs (2)
2.2.11 HD Map Market Players (3): Foreign Map Companies
2.3 HD Map Business Models
2.3.1 Scenarios where HD maps have been commercialized 
2.3.2 HD Map Business Model 1: Autonomous Driving
2.3.3 HD Map Business Model 2: Parking Lots
2.3.4 Classification of HD Map Profit Models  
2.3.5 Summary of HD Map Business Models: Domestic Map Companies (1)
2.3.6 Summary of HD Map Business Models: Domestic Map Companies (2)
2.3.7 Summary of HD Map Business Models: Foreign Map Companies (1)
2.3.8 Summary of HD Map Business Models: Foreign Map Companies (2)
2.3.9 Cases of HD Map Profit Models: Cloud SaaS Service Model

3 Key Technologies for HD Map Mass Production
3.1 HD Map Production
3.1.1 HD Map Production Flow
3.1.2 HD Map Production Flow (I): Hard to Collect HD Maps of Urban Roads
3.1.3 HD Map Production Flow (II): Point Cloud HD Map Generation
3.1.4 HD Map Production Flow (II): Visual Fusion Point Cloud Mapping
3.1.5 HD Map Production Flow (II): LIDAR Point Cloud Mapping
3.1.6 HD Map Production Flow (III): Feature Extraction
3.1.7 HD Map Production Tools: Open Source Architecture Lanelet2
3.1.8 HD Map Production Tools: Open Source Architecture OpenDRIVE
3.1.9 HD Map Production Cases (I): Baidu
3.1.10 HD Map Production Cases (II): NavInfo’s Automatic Map Production Line
3.1.11 HD Map Production Cases (II): NavInfo’s New Automated Mapping Technology
3.1.12 Weak HD Map Production Flow
3.1.13 Weak HD Map Production Flow (I): Spatial Fusion of Different Sensors
3.1.14 Weak HD Map Production Flow (II): Environment Modeling
3.1.15 Weak HD Map Production Flow (III): Realize Online HD Vector Map Reconstruction 
3.1.16 HD Map Production Technology Trend: SD/HD Map Integrated Production
3.2 HD Map Update 
3.2.1 HD Map Update Trends: from Professional Collection to Crowdsourcing Update
3.2.2 HD Map Crowdsourcing Update Method
3.2.3 Challenges to HD Map Crowdsourcing Update (I)
3.2.4 Challenges to HD Map Crowdsourcing Update (II)
3.2.5 HD Map Crowdsourcing Update Solutions (I): Low-cost Collection + SLAM Algorithm
3.2.6  HD Map Crowdsourcing Update Solutions (II): Vision-only + Deep Learning + SLAM Algorithm (1)
3.2.7  HD Map Crowdsourcing Update Solutions (II): Vision-only + Deep Learning + SLAM Algorithm (2)
3.2.8  HD Map Crowdsourcing Update Solutions (II): Vision-only + Deep Learning + SLAM Algorithm (3)
3.2.9 HD Map Crowdsourcing Update Solutions (III): Cloud + Terminal Form An Update Closed Loop
3.2.10 HD Map Update Subjects (I): OEM’S Crowdsourcing Update Solutions (1)
3.2.11 HD Map Update Subjects (I): OEM’S Crowdsourcing Update Solutions (2)
3.2.12 HD Map Update Subjects (II): Technology Providers’ Crowdsourcing Update Solutions 
3.2.13 HD Map Crowdsourcing Update Cases (I): NavInfo's New Map Learning Platform (1)
3.2.14 HD Map Crowdsourcing Update Cases (I): NavInfo's New Map Learning Platform (2)
3.2.15 HD Map Crowdsourcing Update Cases (I): NavInfo's New Map Learning Platform (3)
3.2.16 HD Map Crowdsourcing Update Cases (I): NavInfo's Proprietary Data Processing Platform
3.2.17 HD Map Crowdsourcing Update Cases (II): TomTom Completes Crowdsourced Data Fusion over Cloud
3.3 HD Map Data Distribution and Fusion
3.3.1 HD Map Data Distribution and Fusion Process
3.3.2 Process 1: HD Map Data Distribution Engine Architecture
3.3.3 Process 1: Road Network Model of HD Map Data Distribution Engine
3.3.4 Process 1: Integration Forms of HD Map Data Distribution Engine
3.3.5 Process 1: HD Map Box in Integration Forms of HD Map Data Distribution Engine
3.3.6 Process 1: Major HD Data Distribution Engine Providers 
3.3.7 Process 2: HD Map Data Format Conversion (1)
3.3.8 Process 2: HD Map Data Format Conversion (2)
3.3.9 Process 3: Interaction between HD Map Data Distribution and Receiving Terminals
3.3.10 Process 4: HD Map Data Fusion
3.3.11 Process 4: Integration of HD Map Data Distribution and ADAS
3.3.12 Process 4: Relationship between HD Map Data Distribution and ADAS Applications
3.3.13 HD Map Data Distribution and Fusion Cases (I): NavInfo’s Cross-correlation Layer
3.3.14 HD Map Data Distribution and Fusion Cases (II): Amap’s Data Fusion and Application Methods
3.3.15 HD Map Data Distribution and Fusion Trend: Centralized Processing in the Central Domain Controller
3.4 Fusion Application of HD Map and V2X Technology
3.4.1 Roles of HD Map in V2X (I): Infrastructure
3.4.2 Roles of HD Map in V2X (II): Data Support
3.4.3 Roles of HD Map in V2X (III): Helping to Achieve High-Precision Positioning
3.4.4 Roles of V2X in HD Map (I): Data Storage
3.4.5 Roles of V2X in HD Map (II): Data Distribution (1)
3.4.6 Roles of V2X in HD Map (II): Data Distribution (2)
3.4.7 Roles of V2X in HD Map (III): map Data Update
3.4.8 HD Map and V2X Fusion Application Case: Traffic Lights Prompt 
3.5 HD Map Applied to Lane-Level Positioning
3.5.1 Structure of HD Map Based Lane-Level Positioning Solutions 
3.5.2 Map Matching Technologies in Lane-Level Positioning Solutions (I): Map Matching Based on Point Cloud
3.5.3 Map Matching Technologies in Lane-Level Positioning Solutions (I): Map Matching Algorithms Based on Point Cloud (1)
3.5.4 Map Matching Technologies in Lane-Level Positioning Solutions (I): Map Matching Algorithms Based on Point Cloud (2)
3.5.5 Map Matching Technologies in Lane-Level Positioning Solutions (II): Map Matching Based on Deep Learning (1)
3.5.6 Map Matching Technologies in Lane-Level Positioning Solutions (II): Map Matching Based on Deep Learning (2)
3.5.7 Providers of Lane-Level Positioning Solutions Based on HD Maps
3.5.8 Application Cases (I): Mxnavi’s Lane-Level Positioning Solutions Based on HD Maps
3.5.9 Application Cases (II): Voyah’s Urban Road HD Positioning Solutions Based on Weak HD Maps

4 Application Scenario for HD Map Mass Production
4.1 HD Map Demand for Different Autonomous Driving Levels
4.1.1 HD Map Road Element Demand for Different Autonomous Driving Level
4.1.2 Requirements of Autonomous Driving for HD Map Elements: L2 NOA
4.1.3 Requirements of Autonomous Driving for HD Map Elements: L2 Hands Free
4.1.4 Requirements of Autonomous Driving for HD Map Elements: L3
4.1.5 Requirements of Autonomous Driving for HD Map Elements: L4 (1)
4.1.6 Requirements of Autonomous Driving for HD Map Elements: L4 (2)
4.1.7 Autonomous Driving Development Stage : Human-car Co-Driving
4.1.8 HD Map Framework in the Human-car Co-driving Stage
4.1.9 Challenges of Human-car Co-driving Stage to HD Map Industry
4.2 HD Map Application Scenario 1: Highway Autonomous Driving for Passenger Cars
4.2.1 HD Map Installation of Independent Brand Mass-produced Passenger Cars (1)
4.2.2 HD Map Installation of Independent Brand Mass-produced Passenger Cars (2)
4.2.3 HD Map Installation of Independent Brand Mass-produced Passenger Cars (3)
4.2.4 HD Map Installation of Independent Brand Mass-produced Passenger Cars (4)
4.2.5 HD Map Installation of Independent Brand Mass-produced Passenger Cars (5)
4.2.6 HD Map Installation of Joint Venture Brand Mass-produced Passenger Cars
4.2.7 Mass Production Case 1: GAC Aion HD Map Installation Demand
4.2.8 Mass Production Case 1: GAC Aion HD Map Solution
4.2.9 Mass Production Case 1: GAC Aion EHP
4.2.10 Mass Production Case 1: GAC Aion HD Map Curvature and Slope
4.2.11 Mass Production Case 2: Xpeng HD Map Installation Solution
4.2.12 Mass Production Case 2: Functions of XPeng P7 HD Map
4.2.13 Mass Production Case 2: XPeng Enables Urban Assisted Driving Based on HD Map
4.2.14 Mass Production Case 3: GWM WEY Realizes Point-to-Point Autonomous Driving with HD Map
4.2.15 Mass Production Case 4: GM HD Map Installation Solution
4.2.16 Mass Production Case 5: Li Auto HD Map Installation
4.2.17 Mass Production Case 6: NIO Introduces HD Map from 2020
4.2.18 Mass Production Case 6: NIO NOP Integrated with HD Map
4.2.19 Mass Production Case 7: SAIC IM Autonomous Driving Hardware Solution
4.2.20 Mass Production Case 8: SAIC MAXUS MIFA 9
4.2.21 Mass Production Case 9: Geely ZEEKR 001
4.2.22 Mass Production Case 10: AVATR 11 with Highway + Urban Scenario Assisted Driving
4.2.23 Mass Production Plan 1: BMW HD map Installation Requirement and Solution (1)
4.2.24 Mass Production Plan 1: BMW HD Map Installation Demand and Solution (2)
4.2.25 Mass Production Plan 1: BMW HD Map Mass Production Function
4.2.26 New Battlefield for Passenger Car Autonomous Driving: Urban Scenarios
4.2.27 HD Map solution for Autonomous Driving in Urban Scenarios: SD Pro Map
4.2.28 Urban Autonomous Driving Passenger Car HD Map Installation Solution 1: Multi-sensor Fusion + HD map
4.2.29 Urban Autonomous Driving Passenger Car HD Map Installation Solution 2: Heavy on Perception + Light on Map
4.2.30 Heavy on Perception + Light on Map Application Case 1: IDRIVERPLUS
4.2.31 Heavy on Perception + Light on Map Application Case 2: Haomo AI
4.3 HD Map Application Scenario 2: Low-speed Autonomous Parking for Passenger Cars
4.3.1 AVP Map Type 1: HD Map
4.3.2 AVP Map Type 1: SLAM Real-time map
4.3.3 Top Five HD Map Suppliers for Parking Lots
4.3.4 Application Case 1: Roadgrids Parking Lot HD Map Building System
4.3.5 Application Case 2: ZongMu Technology HD Map-based Parking Product
4.3.6 Autonomous Parking Map Development Trend: One Map of Vehicle / Field / Cloud / APP
4.4 HD Map Application Scenario 3: Autonomous Driving for Cargo
4.4.1 Importance of HD Maps for Low-speed Autonomous Driving
4.4.2 HD Map Building Method for Low-speed Autonomous Driving: SLAM
4.4.3 HD Map Supplier Pattern of Autonomous Driving for Cargo (1)
4.4.4 HD Map Supplier Pattern of Autonomous Driving for Cargo (2)
4.4.5 Application Case 1 of Autonomous Driving for Cargo: Meituan Autonomous Delivery Vehicle
4.4.6 Application Case 1 of Autonomous Driving for Cargo: JD Autonomous Delivery Vehicle
4.5 HD Map Application Scenario 4: Autonomous Driving for People
4.5.1 HD Maps are a Must for High-level Autonomous Driving
4.5.2 Application Case 1 of Autonomous Driving for People: Autonomous Robotaxi HD Map Application
4.5.3 Application Case 1 of Autonomous Driving for People: Robobus HD Map Application
4.5.4 Application Case of Autonomous Driving for People: PIX Moving Autonomous Minibus

5 Chinese and Foreign HD Map Providers
5.1 Baidu Map
5.1.1 "Vehicle-Road-Cloud-Map" Coordinated Development
5.1.2 HD Map Product System
5.1.3 Human-Computer Co-Driving Map
5.1.4 Advantages of HD Map Products (I): SD/HD Map Integrated Production
5.1.5 Advantages of HD Map Products (II): Strong Data Closed-Loop Update Capability
5.1.6 Advantages of HD Map Products (III): High Update Frequency
5.1.7 Advantages of HD Map Products (IV): Wide Coverage
5.1.8 Advantages of HD Map Products (V): Verify Map Accuracy via Cockpit APP
5.1.9 Advantages of HD Map Products (VI): Support Rapid Mass Production
5.1.10 Advantages of HD Map Products (VII): Deep integration of Cockpit, Driving and Map
5.1.11 HD Map Product Planning
5.1.12 AVP HD Maps Are Collected in Real Time Using Machine Vision
5.1.13 Integrate HD Map and Autonomous Driving (I)
5.1.14 Integrate HD Map and Autonomous Driving (II)
5.1.15 HD Map Ecosystem and Partners
5.2 NavInfo
5.2.1 Advantages in HD Map Market (I): Provide All-scenario HD Map Products
5.2.2 Advantages in HD Map Market (II): Build Third-party HD Map Platforms
5.2.3 In-depth Layout of Software and Hardware Integrated Solutions with HD Maps as the Core
5.2.4 Build Barriers in the Key Link "Base Map-Update-Positioning" 
5.2.5 Major HD Map Products
5.2.6 The HD Map Capability Has Exceeded L2+
5.2.7 AVP Map
5.2.8 HD Map Engine
5.2.9 HD Map Update Technologies: UGC
5.2.10 HD Map Update Technologies: Algorithms & Tools
5.2.11 Data-Driven Open Platform for L5
5.2.12 HD Map Quality Control System
5.2.13 Partners Cover Automakers and Tier 1 Suppliers
5.3 eMapgo 
5.3.1 Profile 
5.3.2 eMapgo and Luokung Technology Cooperated to Build A HD Map Platform Provider
5.3.3 HD Map Products
5.3.4 HD Map Update
5.3.5 eHorizon (I)
5.3.6 eHorizon (II)
5.3.7 Parking Lot HD Map (I)
5.3.8 Parking Lot HD Map (II)
5.3.9 HD Map Cloud Platform
5.4 Amap
5.4.1 Profile 
5.4.2 Map Data Collection and Production
5.4.3 Integrated Solutions Based on HD Map and High-Precision Positioning
5.4.4 Third-generation Map Navigation for Vehicles
5.4.5 HD Map and SD Map Matching
5.5 Tencent
5.5.1 Profile
5.5.2 HD Map Solution
5.5.3 HD Map Update
5.5.4 Intelligent Driving Map for Human-Computer Co-Driving
5.5.5 "Vehicle-Cloud Integration" Strategic Layout
5.6 ECARX 
5.6.1 Financing
5.6.2 HD Map Business
5.7 BrightMap 
5.7.1 Profile
5.7.2 Advantages of Parking Lot HD Map Products 
5.7.3 AVP HD Map
5.7.4 AVP HD Map Data Delivery and Update
5.7.5 Parking Navigation HD Map
5.7.6 Secured Mass Production Orders for Parking Lot HD Maps
5.8 Mxnavi 
5.8.1 Business Layout
5.8.2 Full-link HD Map Service Capabilities
5.8.3 HD Map Fusion Platform
5.8.4 HD Map Crowdsourced Production Solution
5.9 Huawei
5.9.1 HD Map Layout
5.9.2 Autonomous Driving Map Data System
5.9.3 HD Map Cloud Services
5.9.4 Huawei Accomplishes Crowdsourced Updates of HD Maps Based on the Open Autonomous Driving Platform
5.9.5 HD Map Application: Holographic Intersections
5.9.6 HD Map Application: Advanced Autonomous Driving System (ADS)
5.10 Heading Data Intelligence
5.10.1 Profile
5.10.2 HD Map Business 
5.10.3 HD Map Updates 
5.10.4 HD Map Engines 
5.10.5 HD Map Application Scenarios: Parking
5.10.6 HD Map Application Scenarios: Freeways/Urban Areas
5.10.7 Products Based on HD Maps
5.10.8 Listing and Trading of HD Electronic Map Data Products 
5.11.1 HD Map Business
5.11.2 HD Map Application Scenarios
5.12 SFMAP Technology
5.12.1 HD Map Business 
5.13 Leador
5.13.1 Profile
5.13.2 Autonomous Driving Technology Based on HD Maps (1)
5.13.3 Autonomous Driving Technology Based on HD Maps (2)
5.13.4 Indoor Map Construction Based on SLAM Algorithms
5.13.5 HD Maps for Parking Lots
5.13.6 HD Map Application Scenarios
5.14 Momenta
5.14.1 Profile
5.14.2 HD Map Technology Route
5.14.3 The Role of HD Maps in Mpilot Parking
5.15 HERE
5.15.1 Profile
5.15.2 Map Evolution Mode 
5.15.3 HD Map Business
5.15. 4 HERE HD Live Map
5.15.5 HD Map Data Updates
5.15.6 HD Map Layout in China
5.15.7 HERE Supports China’s Automobile Brands to "Go Out"
5.16 TomTom
5.16.1 Profile
5.16.2 HD Map Business
5.16.3 TomTom AutoStream Delivery Service
5.16.4 HD Map Collection and Drawing
5.16.5 Crowdsourced Updates of HD Maps
5.16.6 integrated ADAS Software Based on Maps
5.16.7 Cooperation between TomTom and EB

6 HD Map-related Technology Companies 
6.1 Mobileye
6.1.1 HD Map Business
6.1.2 Map Data Coverage of Mobileye REM
6.1.3 Mobileye REM Technology Realizes Crowdsourced Updates
6.1.4 REM Reduces Map Production and Maintenance Cost
6.1.5 Functions Achieved by Mobileye REM
6.1.6 REM-based Map Extension Service of Mobileye
6.1.7 Progress of REM in the World
6.1.8 Mobileye Encounters Obstacles in the Chinese Market
6.1.9 Mobileye Updates ZEEKR’s Assisted Driving Functions via OTA
6.2 Nvidia
6.2.1 Nvidia acquired DeepMap to deploy HD maps
6.2.2 Nvidia's DRIVE Map for Autonomous Vehicles (1)
6.2.3 Nvidia's DRIVE Map for Autonomous Vehicles (2)
6.2.4 DeepMap's Crowdsourced Update Solution (1)
6.2.5 DeepMap's Crowdsourced Update Solution (2)
6.3 Bosch
6.3.1 Bosch Acquired Atlatec for HD Map Layout
6.3.2 Bosch's Low-cost and Easy-to-deploy Mapping Solution
6.4 DMP
6.4.1 Profile
6.4.2 DMP’s Dynamic Map
6.5 Carmera
6.5.1 Toyota Acquired Carmera
6.5.2 Carmera's Autonomous Driving 3D Map Solution
6.5.3 Carmera's Map Data Collection Mode
6.6 Kuandeng Technology
6.6.1 Kuandeng Technology’s HD Map Technology Solution
6.6.2 Kuandeng Technology's HD Map Quality Evaluation System
6.7 DeepMotion
6.7.1 DeepMotion Was Acquired by Xiaomi
6.7.2 DeepMotion’s HD Map Technology Solution
6.7.3 Features of DeepMotion’s HD Maps
6.8 Dilu Technology
6.8.1 Profile  
6.8.2 HD map solutions
6.8.3 Production Process of Dilu Technology’s HD Maps (1)
6.8.4 Production Process of Dilu Technology’s HD Maps (2)
6.9 Others
6.9.1 HD Map Update Solutions of Horizon Robotics
6.9.2 Mapbox's HD Map Services

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