The global HD maps for autonomous vehicles market is estimated to be USD 1.4 Billion in 2021 and is projected to grow at a CAGR of 31.7% during the forecast period, to reach USD 16.9 Billion by 2030.
HD maps are primarily used in autonomous vehicles. These are the maps designed for use by the machines that drive the autonomous vehicles. HD maps offer high-precision localization, environment perception, planning and decision making, and real-time navigation cloud services to autonomous vehicles. OEMs across the globe are investing in the development of autonomous vehicles. Although level 5 fully autonomous vehicles are not expected to be commercially available until 2025, many of the associated technologies have already been developed, and thousands of patent applications have been filed to secure intellectual property rights. Ford had the largest number of patents related to autonomous vehicle technology, followed by Toyota by the end of 2020. Since 2011, Ford submitted 14,354 patents and 13,000 patents were submitted by Toyota by the end of 2020.
With the growing trend of autonomous driving technology, the global HD maps market is expected to grow at a significant rate in the future. The promising market for self-driving car renting services and increased investments in autonomous driving technology startups are expected to boost the HD maps market. In addition, increasing R&D activities related to HD maps by leading HD map suppliers and several startups will further fuel the growth of HD maps for autonomous vehicle market. However, high investment costs and slow adoption rates in developing countries are considered the major restraints for this market.
North America is estimated to be the largest market for HD maps for autonomous vehicles during the forecast period. The North American market is principally driven by the increasing demand for a safe, efficient, and convenient driving experience; rising investment in autonomous vehicle technology; and a strong presence of HD map suppliers. The increase in government support and the availability of suitable infrastructure for semi-autonomous and autonomous vehicles are likely to drive market growth in the region. Asia Oceania is projected to grow at the highest CAGR of 34.3%. China, Japan, and South Korea are the key countries in the region leading the fast-paced development. The government support for autonomous vehicle technology is also a driving factor for the growth of the Asia Oceania market.
Some of the major players in the HD map for autonomous vehicle market are TomTom (the Netherlands), HERE Technologies (the Netherlands), Waymo (US), NVIDIA (US), Baidu (China), Dynamic Map Platform (Japan), NavInfo (China), and Zenrin (US). These players have long-term supply contracts with leading automotive manufacturers and autonomous vehicle technology developers. These companies have adopted the strategies of new product developments, acquisitions, agreements, collaborations, expansions, joint ventures, partnerships, and supply contracts to gain traction in the HD map for autonomous vehicle market. Partnership and collaboration are the most widely adopted strategies by major players. For instance, in September 2019, TomTom and HELLA Aglaia collaborated to update the TomTom High Definition Map in real-time using crowdsourced camera data from vehicles. As part of the collaboration, HELLA Aglaia will use AutoStream, which is TomTom’s innovative map delivery system, to access the latest TomTom HD Map on demand and will use the HD Map in the vehicle for accurate localization.
Wide adoption of HD maps in passenger mobility segment expected to lead to market growth
Personal mobility is estimated to be the largest segment of the HD map for autonomous vehicle market, by usage type, owing to the higher volume of semi-autonomous vehicle sales, and a majority of semi-autonomous vehicles would be used for personal transportation. OEMs such as Honda, Nissan, General Motors, and Mercedes-Benz promote the use of HD map and use it to develop its level 2 and level 3 semi-autonomous vehicles. The commercial mobility segment is projected to be the fastest-growing because of the high demand for ride-sharing services, predominant usage of autonomous vehicles for ride-sharing and robo-taxi services, and growing partnership between ride-sharing companies and HD map providers.
The transportation of goods by autonomous vehicles helps minimize the cost of delivery. E-commerce companies mostly drive the delivery of goods by autonomous vehicles. According to companies like Continental, 80% of all business-to-consumer deliveries will be done by driverless cars in the future. OEMs, autonomous vehicle technology providers, and logistics/transportation companies such as Pony.ai, FedX, and Ford are involved in testing autonomous last delivery vehicles across the world. For example, in June 2021, Ford and Hermes, a consumer delivery company in the UK, started testing autonomous vehicles for delivery. HD mapping companies can focus on developing HD maps and other related solutions for the commercial mobility segment as it can provide high growth opportunities, especially for new entrants.
Level 2&3 semi-autonomous vehicles to ensure dominant position of the segment
HD map market for Level 2&3 semi-autonomous vehicles is estimated to be the largest market, and the market for Level 4&5 autonomous vehicles is expected to be the fastest-growing market during the forecast period. The semi-autonomous vehicle segment dominates because of the demand for features such as Co-operative Adaptive Cruise Control, Highway Autopilot, Auto Lane Change, and Hands-free Auto Parking. Other factors include stringent laws concerning autonomous driving and a greater number of semi-autonomous vehicles on road than autonomous vehicles during the forecast period.
Rapid advancements and the decreasing cost of ADAS components and solutions are expected to spur the growth of the HD map market for semi-autonomous vehicles. For example, ZF unveiled its coASSIST level 2+ driving system in 2020 with a price range of USD 1,000. Such affordable ADAS solutions would increase the penetration of major ADAS features in a standard ADAS package. ZF offers copilot, a scalable ADAS solution for level 2+ to level 4 driving systems, was co-developed with NVIDIA. These affordable ADAS solutions would significantly boost the adoption of ADAS and the demand for HD maps for semi-autonomous vehicles. The autonomous vehicles segment is projected to have a significant growth rate during the forecast period.
The continuous improvement in HD map technology is also a major factor boosting the growth of the market. Increasing investments for the development of level 4 and level 5 technologies and the growth in the testing activities of level 4 and level 5 autonomous vehicles will drive the HD map market for autonomous vehicles.
Research Coverage
The report segments the HD maps for autonomous vehicles harness market and forecasts its size, by value, on the basis of service type (mapping, localization, updates and maintenance, and advertisement), level of automation (semi-autonomous driving vehicles, autonomous driving vehicles), solution type (cloud based, embedded), usage type (operational data, commercial mobility), vehicle type (passenger car, commercial vehicles) & region. It also covers the competitive landscape and company profiles of the major players in the HD maps for autonomous vehicles harness market ecosystem.
Major players profiled in the report are TomTom (Netherlands), HERE (Netherlands), NVIDIA (US), Waymo (US), Baidu (China), Dynamic Map Platform (Japan), and NavInfo (China).
The study contains insights from various industry experts, ranging from component suppliers to tier 1 companies and OEMs.
The break-up of the primaries is as follows:
- By Department: Sales/Marketing - 45%, Production & Procurement - 35%, and CXOs - 20%
- By Designation: C level - 40%, D level - 35%, and Others - 25%
- By Region: Asia Pacific- 40%, North America - 20%, Europe - 35%, and RoW - 5%
Key Benefits of Buying the Report
- The report will help market leaders/new entrants in this market with information on the closest approximations of revenue and value for the HD maps for autonomous vehicles harness market and its sub segments.
- This report will help stakeholders understand the competitive landscape and gain more insights to better position their businesses and plan suitable go-to-market strategies.
- The report will also help the market players understand the impact of COVID-19 on HD maps for autonomous vehicles harness market.
- The report also helps stakeholders understand the pulse of the market and provides them information on key market drivers, restraints, challenges, and opportunities.
Table of Contents
1 Introduction
1.1 Objectives of the Study
1.2 Market Definition
1.2.1 Segmental Definitions, Inclusions, and Exclusions
Table 1 Segmental Definitions, Inclusions, and Exclusions: HD Map for Autonomous Vehicle Market
Table 2 Other Key Definitions
1.3 Market Scope
1.3.1 Markets Covered
Figure 1 Markets Covered: HD Map for Autonomous Vehicle Market
1.3.2 Years Considered in the Study
1.4 Limitations
1.5 Stakeholders
1.6 Summary of Changes
2 Research Methodology
2.1 Research Data
Figure 2 HD Map for Autonomous Vehicle Market: Research Design
Figure 3 Research Design Model
2.2 Secondary Data
2.2.1 Key Secondary Sources for Base Numbers (HD Map for Autonomous Vehicle)
2.2.2 Key Secondary Sources for Market Sizing
2.2.3 Key Data from Secondary Sources
2.3 Primary Data
Figure 4 Breakdown of Primary Interviews
2.3.1 Primary Participants
2.4 Market Size Estimation
2.4.1 Top-Down Approach
Figure 5 Top-Down Approach: HD Map for Autonomous Vehicle Market
Figure 6 Illustration of HD Map for Autonomous Vehicle Company Revenue Estimation
Figure 7 HD Map for Autonomous Vehicle Market: Research Design & Methodology
2.4.2 Data Triangulation
2.5 Market Breakdown
2.6 Factor Analysis
2.7 Assumptions
2.7.1 Key Assumptions
2.7.2 Other Research Assumptions
2.8 Risk Assessment & Ranges
Table 3 Risk Assessment & Ranges
2.9 Research Limitations
3 Executive Summary
Figure 8 HD Map for Autonomous Vehicle Market: Market Overview
Figure 9 HD Map for Autonomous Vehicle Market, by Region, 2021-2030
Figure 10 Personal Mobility is Estimated to Lead the HD Map for the Autonomous Vehicle Market from 2021 to 2030
4 Premium Insights
4.1 Attractive Opportunities in the HD Map for Autonomous Vehicle Market
Figure 11 Increasing Demand for Semi-Autonomous Vehicles and Rising Investment for the Development of Autonomous Vehicle Will Propel the HD Map for Autonomous Vehicle Market
4.2 HD Map for Autonomous Vehicle Market, by Region
Figure 12 Asia Oceania is Projected to be the Fastest Growing Region in HD Map for Autonomous Vehicle Market During 2021−2030
4.3 North America: HD Map for Autonomous Vehicle Market, Level of Automation & Vehicle Type
Figure 13 North America: HD Map for Autonomous Vehicle Market, by Level of Automation & Vehicle Type, 2021 vs 2030 (USD Million)
4.4 HD Map for Autonomous Vehicle Market, by Solution Type
Figure 14 HD Map for Autonomous Vehicle Market, by Solution Type, 2021 vs 2030 (USD Million)
4.5 HD Map for Autonomous Vehicle Market, by Service Type
Figure 15 HD Map for Autonomous Vehicle Market, by Service Type, 2021 vs 2030 (USD Million)
5 Market Overview
5.1 Introduction
5.2 Market Dynamics
Figure 16 HD Maps Market: Market Dynamics
5.2.1 Drivers
5.2.1.1 Growing Trend of Autonomous Driving
Table 4 Investment by Automotive Companies in Autonomous Technology
5.2.1.2 Increasing Adoption of Level 2 and Level 3 ADAS Features in the Automotive Industry
5.2.1.3 Increasing Investment by Startups in the Development of HD Maps
Table 5 Worldwide Distribution of Startups by Type of Embedded Autonomous Technology
5.2.1.4 Increasing Partnerships and Joint Ventures by the Key Players
Table 6 HD Map Market: Partnerships/Collaborations in HD Maps Ecosystem
Table 7 HD Map Market: OEMs and Its HD Maps Suppliers
Table 8 HD Map Market: Key Investments in HD Maps Ecosystem
5.2.1.5 Growth in the Map Data Collection
Figure 17 Classification of Different Road Detection Approaches Depending on the Sensor and the Methodology
Figure 18 Different Strategies for Autonomous Driving with Road-Level Navigation and Lane-Level Navigation
5.2.1.6 Increasing Investments in Smart City Projects
Table 9 Smart City Initiatives and Investments
5.2.2 Restraints
5.2.2.1 Limited Standardization in HD Maps
5.2.2.2 Less Reliability in Untested Environments
5.2.3 Opportunities
5.2.3.1 Autonomous Car Renting Services
5.2.3.2 Advancement in 5G Technology
Figure 19 5G Technology Ecosystem
5.2.3.3 Increasing Demand for Real-Time Data
Figure 20 Architecture of Real-Time HD Map Change Detection
Figure 21 General Structure of Localization Procedure
5.2.4 Challenges
5.2.4.1 Legal & Privacy Issues Regarding HD Maps
5.2.4.2 High Cost of the Technology and Autonomous Vehicle Mapping
Figure 22 HD Mapping Process
5.2.4.3 Large Size Data Collection, Processing, and Transmission of HD Map Data
Figure 23 Data from an Autonomous Vehicle
5.3 Porter's Five Forces
Figure 24 Porter's Five Forces: HD Map for Autonomous Vehicle Market
5.3.1 Threat of New Entrants
5.3.1.1 The Key Players Have Collaborations with Key OEMs
5.3.2 Threat of Substitutes
5.3.3 Bargaining Power of Buyers
5.3.4 Bargaining Power of Suppliers
5.3.5 Rivalry Among Existing Competitors
5.3.5.1 Many HD Map Providers Partnered to Develop HD Maps and HD Mapping Datasets
5.3.5.2 Increasing Competition to Broaden the Customer Base
5.4 Roadmap of HD Map for Autonomous Vehicle
Figure 25 Roadmap of HD Map for Autonomous Vehicle in Urban Environment
5.5 Value Chain Analysis
Figure 26 Value Chain Analysis of HD Map for Autonomous Vehicle
5.6 Ecosystem Analysis
Figure 27 Ecosystem Analysis of HD Map for Autonomous Vehicle
Table 10 List of Key Player from HD Map for Autonomous Vehicle Ecosystem
Figure 28 HD Map for Autonomous Vehicle Ecosystem Matrix
5.7 Regulatory Analysis of Related Markets
5.7.1 General Data Protection Regulation
5.7.2 ADAS: Regulatory Overview
5.7.2.1 Canada
5.7.2.2 US
5.7.2.3 European Parliament
5.7.2.4 National Agency for Automotive Safety & Victims’ Aid (NASVA), Japan
5.7.3 Autonomous Vehicle: Regulatory Overview
5.7.3.1 Enacted Legislation and Executive Orders in the US
Figure 29 Enacted Legislation and Executive Orders in the US
5.7.3.2 Autonomous Vehicle Testing Area in China
Figure 30 Autonomous Vehicle Testing Area in China
5.7.3.3 Autonomous Vehicle Testing Area in Germany
Figure 31 Autonomous Vehicle Testing Area in Germany
5.7.3.4 Autonomous Vehicle Testing Area in Singapore
Figure 32 Autonomous Vehicle Testing Area in Singapore
5.8 HD Map for Autonomous Vehicle Market, Scenarios (2021-2030)
Figure 33 HD Map for Autonomous Vehicle Market- Future Trends & Scenarios, 2021-2030 (Units)
5.8.1 Most Likely Scenario
Table 11 HD Map for Autonomous Vehicle Market (Most Likely), by Region, 2021-2030 (Units)
5.8.2 Optimistic Scenario
Table 12 HD Map for Autonomous Vehicle Market (Optimistic Scenario), by Region, 2021-2030 (Units)
5.8.3 Pessimistic Scenario
Table 13 HD Map for Autonomous Vehicle Market (Pessimistic), by Region, 2021-2030 (Units)
6 Industry Trends
6.1 Technology Overview
Figure 34 Five Eras of Vehicle Safety
Figure 35 Connected Vehicle for Autonomous Driving
6.1.1 HD Maps Portfolio for All Automation Levels
Table 14 Automation Levels
Figure 36 HD Maps Portfolio for All Automation Levels
6.1.2 HD Map Layers
Figure 37 HD Map Layers
6.1.3 Components Used to Build HD Maps
6.1.3.1 Hardware
Figure 38 Sensors and Their Importance in Autonomous Vehicles
6.1.3.1.1 LiDAR
6.1.3.1.2 Camera
6.1.3.1.3 Radar
6.1.3.1.4 Inertial Measurement Unit (IMU)
6.1.3.1.5 Global Positioning System (GPS)
6.1.3.2 Software
Figure 39 Flow Chart for Production Process and Map Data Sources
6.1.4 Advancement in Slam Algorithm
6.1.5 Self-Healing Maps
Figure 40 Self-Healing Map Process
6.1.6 Mapping Standards
Figure 41 Features of Key Mapping Standards
6.1.6.1 SENSORIS
6.1.6.2 ADASIS
Figure 42 HD Map Standards
6.1.6.3 Navigation Data Standard
6.1.6.4 Vector Tile 3
6.1.6.5 Open Autodrive Forum
6.1.7 HD 3D Viewing Customer Experience
6.1.8 Emergence of AI and ML Technologies to Boost the 3D Content Accuracy
6.1.9 Advent of 3D-Enabled Display Devices for a Better Navigation Experience
6.1.10 3D Mapping Techniques
6.1.10.1 Photogrammetry
6.1.10.2 LiDAR
6.1.10.3 Radar
6.1.10.4 Sonar
Figure 43 IoT Devices in Autonomous Vehicles
6.1.11 HD Mapping and Blockchain
6.1.12 Machine Learning Powered Analytics
6.1.13 Supply Chain 4.0
6.1.14 LiDAR Drones for Mapping
Figure 44 LiDAR Ecosystem: Major Value Addition by LiDAR Component Manufacturers and Their Integrators & Distributors
6.1.15 Location of Things
6.1.16 HD Mapping for Autonomous Vehicle Proving Grounds
6.1.17 Potential Applications of HD Maps Other Than Autonomous Vehicles
Table 15 Business Model for Autonomous Last Mile Delivery
Figure 45 Algorithms and Analytics Supporting Autonomous Last Mile Delivery
6.1.17.1 Aerial Delivery Drones
Table 16 Evolution of Aerial Delivery Drones
6.2 Use Cases: Aerial Delivery Drones
6.2.1 Use of Project Wing of Alphabet to Deliver Food and Medicines in Australia
6.2.2 Regulators Approve Trial Flights of Urban Flight Delivery Systems of Drone Delivery Canada
6.2.3 Ele.me Starts Food Delivery Using Drones in Shanghai
6.2.4 SF Express Received License to Start Aerial Drone-based Network for Deliveries Within Pilot Zones of China
6.2.5 Emqopter Delivers Food Parcels in Germany Using Aerial Delivery Drones
6.2.6 Skyways UAV of Airbus Helicopters Conducts Its First Parcel Delivery in Singapore
6.2.7 Zipline Plans to Deliver Medicines in African Region Using Aerial Delivery Drones
6.2.8 Drone Deliveries to King's Walk Golf Course in Grand Forks, North Dakota
6.2.9 Amazon Plans to Transforming Parcel Delivery Using Prime Air Delivery Drone
6.2.10 DHL Has Successfully Completed Trails of BVLOS Medicine Delivery Flights Across Lake Victoria, Tanzania
6.2.10.1 Ground Delivery Vehicles
Table 17 Evolution of Ground Delivery Vehicles
6.3 Use Cases: Ground Delivery Vehicles
6.3.1 Nuro Autonomous Delivery Robots Providing Cost-Effective Grocery Delivery Services for Kroger
6.3.2 Kiwibots Deployed to Carry Out Low-Cost Food Delivery Services in University Campuses in California
6.3.3 PepsiCo Delivering Snacks to College Students by a Fleet of Ground Robots
6.3.4 FedEx Delivers Parcels Using Same-day Delivery Bot
6.3.5 Dominos Using Ground Delivery Robots to Deliver Pizza in New Zealand
6.3.6 Starship Technology Offering Food Deliveries at George Mason University's Fairfax Campus
6.3.7 JD.com Started Deliveries Using Al Equipped Ground Robots
6.3.8 Amazon's Scout Ground Robot to Deliver Parcels in Washington
6.3.9 Types of GNSS Receivers
6.3.9.1 Global Positioning System (GPS)
6.3.9.2 Galileo
6.3.9.3 Global Navigation Satellite System (GLONASS)
6.3.9.4 Satellite-based Augmentation System (SBAS)
Table 18 SBAS in Different Countries
6.3.9.5 Beidou Navigation Satellite System
6.3.10 GIS Data
6.3.10.1 Types of GIS Data Models
6.3.10.1.1 Vector Data Model
6.3.10.1.2 Raster Data Model
6.3.10.2 Key Trends in GIS
6.3.10.2.1 AR and VR Technologies
6.3.10.2.2 Unmanned Aerial Vehicles
6.3.10.2.3 Integration of Cloud Computing in GIS
6.3.10.2.4 Development of 4D GIS Software and Augmented Reality Platforms for GIS
7 HD Map for Autonomous Vehicle Market, by Service Type
7.1 Introduction
7.2 Research Methodology
7.3 Assumptions
Table 19 Assumptions, by Service Type
Figure 46 HD Map for Autonomous Vehicle Market, by Service Type, 2021 vs 2030 (USD Million)
Table 20 HD Map for Autonomous Vehicle Market, by Service Type, 2020-2030 (USD Million)
7.4 Mapping
Table 21 HD Map Semantic Information
Table 22 Road Segment Data (RSD) Applications
Table 23 Potentially Applicable Mapping Technologies, Their Strengths and Limitations
Table 24 Mapworks Software Development Kit
7.4.1 The Companies Offering End to End Mapping Solutions for Autonomous Vehicle is Expected to Drive North American Market
Table 25 Mapping: HD Map for Autonomous Vehicle Market, by Region, 2020-2030 (USD Million)
7.5 Localization
Table 26 Localization Techniques for Autonomous Vehicle and Their Accuracy
Table 27 Prior Information in HD Map Based Vehicle Localization
7.5.1 Increased Investment in the Localization of HD Maps to Drive the Market
Table 28 Localization: HD Map for Autonomous Vehicle Market, by Region, 2020-2030 (USD Million)
7.6 Updates & Maintenance
7.6.1 Need of Dynamic Traffic, Weather Information and Continuously Update in Data Gathered by Mapping and Localization Will Drive the Market
Table 29 Updates & Maintenance: HD Map for Autonomous Vehicle Market, by Region, 2020-2030 (USD Million)
7.7 Advertisement
7.7.1 Advertisement is Projected to be the Fastest-Growing Segment of HD Maps for the Autonomous Vehicles Market
Table 30 Advertisement: HD Map for Autonomous Vehicle Market, by Region, 2020-2030 (USD Million)
7.8 Key Industry Insights
8 HD Map for Autonomous Vehicle Market, by Level of Automation
8.1 Introduction
Figure 47 HD Map for Autonomous Vehicle Market, by Automation Level, 2021 vs. 2030 (USD Million)
8.2 Research Methodology
8.3 Assumptions
Table 31 Assumptions, by Level of Automation Type
8.4 Operational Data
Table 32 Recent and Ongoing Demonstration and Testing of Connected Autonomous Vehicles by Key Companies
Table 33 Economic Impact of Connected and Autonomous Vehicle and Its Breakdown
Table 34 HD Map for Autonomous Vehicle Market, by Automation Level, 2020-2030(USD Million)
8.5 Semi-Autonomous Driving Vehicles
8.5.1 Level 2
8.5.2 Level 3
8.5.3 Asia Oceania Region is Projected to Have the Highest Growth Rate
Table 35 HD Map for Semi-Autonomous Vehicle Market, by Region,2020-2030 (USD Million)
Table 36 HD Map for Semi-Autonomous Vehicle Market, by Level of Automation, 2020-2030 (USD Million)
8.6 Autonomous Driving Vehicles
Table 37 Expected Technology vs Current Technology Readiness Level of Autonomous Vehicle
8.6.1 Level 4 & 5 Autonomous Vehicle Development and Deployment
8.6.1.1 Daimler AG
8.6.1.2 TuSimple
8.6.1.3 Argo AI and Ford
8.6.1.4 Baidu
8.6.1.5 Didi
8.6.1.6 Toyota, Pony.ai, and Hyundai
8.6.1.7 Waymo
8.6.1.8 Voyage
8.6.1.9 General Motors and Cruise
8.6.1.10 Volvo
8.6.1.11 Einride
8.6.2 Level 4
8.6.3 Level 5
8.6.4 Technology Readiness of Autonomous Vehicles in the Europe Region is Expected to Drive the Market
Table 38 HD Map for Autonomous Vehicle Market, by Region, 2020-2030 (USD Million)
Table 39 HD Map for Autonomous Vehicle Market, by Level of Automation, 2020-2030 (USD Million)
8.7 Key Industry Insights
9 HD Map for Autonomous Vehicle Market, by Solution Type
9.1 Introduction
Figure 48 HD Map for Autonomous Vehicle Market, by Solution Type, 2021 vs. 2030 (USD Million)
9.2 Research Methodology
9.3 Assumptions
Table 40 Assumptions: by Solution Type
Table 41 HD Map for Autonomous Vehicle Market, by Solution Type, 2020-2030 (USD Million)
9.4 Cloud-based
Figure 49 HD Map Production Pipeline
9.4.1 High Flexibility and Accuracy Offered by Cloud-based HD Maps are Expected to Drive the Market
Table 42 Cloud-based: HD Map for Autonomous Vehicle Market, by Region, 2020-2030 (USD Million)
9.5 Embedded
9.5.1 Asia Oceania Region Offers a Huge Opportunity for the Growth of Embedded HD Maps
Table 43 Embedded: HD Map for Autonomous Vehicle Market, by Region, 2020-2030 (USD Million)
9.6 Key Industry Insights
10 HD Map for Autonomous Vehicle Market, by Usage Type
10.1 Introduction
Figure 50 HD Map for Autonomous Vehicle Market, by Usage Type, 2021 vs. 2030 (USD Million)
Table 44 HD Map for Autonomous Vehicle Market, by Usage Type, 2020-2030 (USD Million)
10.2 Research Methodology
10.3 Assumptions
Table 45 Assumptions, by Usage Type
10.4 Operational Data
Table 46 Few Popular Robo-Taxis Used for Passenger Transportation Across the World
10.5 Personal Mobility
10.5.1 North America is Estimated to be the Largest Market for the Personal Mobility Segment
Table 47 Personal Mobility: HD Map for Autonomous Vehicle, by Region, 2020-2030 (USD Million)
10.6 Commercial Mobility
10.6.1 Increasing Adoption of Ride-Sharing Services and Growing Partnership Between Key Ride-Sharing Companies with Providers of HD Maps Will Propel the Market Commercial Mobility Segment
Table 48 Commercial Mobility: HD Map for Autonomous Vehicle, by Region, 2020-2030 (USD Million)
10.7 Key Industry Insights
11 HD Map for Autonomous Vehicle Market, by Vehicle Type
11.1 Introduction
Figure 51 HD Map for Autonomous Vehicle Market, by Vehicle Type, 2021 vs. 2030 (USD Million)
11.2 Research Methodology
11.3 Assumptions
Table 49 Assumptions: by Vehicle Type
11.4 Operational Data
Table 50 Existing Products and Solutions Offered by HD Map Providers
Table 51 Few Popular Autonomous Shuttles from Companies Across the World
Table 52 Truck Routing Attributes and Considerations
Table 53 US Hours of Service Regulations
Table 54 Key Players in the Global Truck Platooning Market
Table 55 HD Map for Autonomous Vehicle Market, by Vehicle Type, 2020-2030 (USD Million)
11.5 Passenger Car
11.5.1 The Passenger Car Segment Holds the Largest Share of the HD Map for the Autonomous Vehicle Market
Table 56 Passenger Car: HD Map for Autonomous Vehicle Market, by Region, 2020-2030 (USD Million)
11.6 Commercial Vehicles
11.6.1 Growing Investment by Truck Manufacturers in Autonomous Vehicle Technology to Drive the Commercial Vehicle Segment Market
Table 57 Commercial Vehicle: HD Map for Autonomous Vehicle Market, by Region, 2020-2030 (USD Million)
11.7 Key Industry Insights
12 HD Map for Autonomous Vehicle Market, by Region
12.1 Introduction
Table 58 NCAP Regulations: US and European Union
Table 59 Phases in Autonomous Vehicle Development and Impacts
Figure 52 HD Maps for Autonomous Market, by Region, 2021 vs 2030 (USD Million)
Table 60 HD Map for Autonomous Vehicle Market, by Region,2020-2030 (USD Million)
12.2 North America
Figure 53 North America: HD Map for Autonomous Vehicle Market Snapshot
Table 61 North America: Autonomous Vehicle Efforts
Table 62 Phases in Autonomous Vehicle Development in the US and Its Impact on HD Maps
Table 63 North America: HD Map for Autonomous Vehicle Market, by Vehicle Type, 2020-2030 (USD Million)
Table 64 North America: HD Map for Autonomous Vehicle Market, by Automation Level, 2020-2030 (USD Million)
Table 65 North America: HD Map for Autonomous Vehicle Market, by Usage Type, 2020-2030 (USD Million)
Table 66 North America: HD Map for Autonomous Vehicle Market, by Solution Type, 2020-2030 (USD Million)
Table 67 North America: HD Map for Autonomous Vehicle Market, by Service Type, 2020-2030 (USD Million)
12.2.1 US
Table 68 US: Vehicle Production Data, 2018-2020 (Units)
12.2.2 Mexico
Table 69 Mexico: Vehicle Production Data, 2018-2020 (Units)
12.2.3 Canada
Table 70 Canada: Vehicle Production Data, 2018-2020 (Units)
12.3 Asia Oceania
Figure 54 Asia Oceania: Snapshot
Table 71 Asia Oceania: Autonomous Vehicle Efforts
Table 72 Asia Oceania: HD Map for Autonomous Vehicle Market, by Vehicle Type, 2020-2030 (USD Million)
Table 73 Asia Oceania: HD Map for Autonomous Vehicle Market, by Automation Level, 2020-2030 (USD Million)
Table 74 Asia Oceania: HD Map for Autonomous Vehicle Market, by Usage Type, 2020-2030 (USD Million)
Table 75 Asia Oceania: HD Map for Autonomous Vehicle Market, by Solution Type, 2020-2030 (USD Million)
Table 76 Asia Oceania: HD Map for Autonomous Vehicle Market, by Service Type, 2020-2030 (USD Million)
12.3.1 China
Table 77 China: Vehicle Production Data, 2018-2020 (Units)
Table 78 Key Companies in Autonomous Vehicle Technology and Their Known Partners in China
Table 79 China Autonomous Vehicle Testing Records
12.3.2 Japan
Table 80 Japan: Vehicle Production Data, 2018-2020 (Units)
12.3.3 India
Table 81 India: Vehicle Production Data, 2018-2020 (Units)
12.3.4 South Korea
Table 82 South Korea: Vehicle Production Data, 2018-2020 (Units)
12.4 Europe
Figure 55 Europe: HD Map for Autonomous Vehicle Market Snapshot
Table 83 Europe: Efforts Towards Autonomous Vehicles
Table 84 Europe: HD Map for Autonomous Vehicle Market, by Vehicle Type, 2020-2030 (USD Million)
Table 85 Europe: HD Map for Autonomous Vehicle Market, by Level of Automation, 2020-2030 (USD Million)
Table 86 Europe: HD Map for Autonomous Vehicle Market, by Usage Type, 2020-2030 (USD Million)
Table 87 Europe: HD Map for Autonomous Vehicle Market, by Solution Type, 2020-2030 (USD Million)
Table 88 Europe: HD Map for Autonomous Vehicle Market, by Service Type, 2020-2030 (USD Million)
12.4.1 Germany
Table 89 Germany: Vehicle Production Data, 2018-2020 (Units)
12.4.2 Spain
Table 90 Spain: Vehicle Production Data, 2018-2020 (Units)
12.4.3 Italy
Table 91 Italy: Vehicle Production Data, 2018-2020 (Units)
12.4.4 France
Table 92 France: Vehicle Production Data, 2018-2020 (Units)
12.4.5 UK
Table 93 UK: Vehicle Production Data, 2019-2020 (Units)
12.5 RoW
Figure 56 RoW: HD Map for Autonomous Vehicle Market, 2021 vs. 2030 (USD Million)
Table 94 RoW: HD Map for Autonomous Vehicle Market, by Vehicle Type, 2020-2030 (USD Million)
Table 95 RoW: HD Map for Autonomous Vehicle Market, by Automation Level, 2020-2030 (USD Million)
Table 96 RoW: HD Map for Autonomous Vehicle Market, by Usage Type, 2020-2030 (USD Million)
Table 97 RoW: HD Map for Autonomous Vehicle Market, by Solution Type, 2020-2030 (USD Million)
Table 98 RoW: HD Map for Autonomous Vehicle Market, by Service Type, 2020-2030 (USD Million)
12.5.1 Brazil
Table 99 Brazil: Vehicle Production Data, 2018-2020 (Units)
12.5.2 South Africa
Table 100 South Africa: Vehicle Production Data, 2018-2020 (Units)
12.5.3 Israel
13 Competitive Landscape
13.1 Overview
Table 101 Overview of Strategies Adopted by Key Players in the HD Map for Autonomous Vehicle Market
13.2 Market Ranking Analysis
Figure 57 Market Ranking Analysis: HD Map for Autonomous Vehicle Market
13.3 Competitive Leadership Mapping
13.3.1 Stars
13.3.2 Emerging Leaders
13.3.3 Pervasive
13.3.4 Participants
Figure 58 HD Maps for Autonomous Vehicles Market: Competitive Leadership Mapping, 2021
Table 102 HD Maps for Autonomous Vehicles Market: Company Footprint, 2021
Table 103 HD Maps for Autonomous Vehicles Market: Solution Footprint, 2021
Table 104 HD Maps for Autonomous Vehicles Market: Regional Footprint, 2021
13.4 SME Competitive Leadership Mapping
13.4.1 Progressive Companies
13.4.2 Responsive Companies
13.4.3 Dynamic Companies
13.4.4 Starting Blocks
Figure 59 HD Map for Autonomous Vehicles Market: SME/Startup Competitive Leadership Mapping, 2021
Table 105 Winners vs. Tail-Enders
14 Company Profiles
(Business Overview, Products Offerings, Recent Developments, Product Launches, Deals, Analyst's View, Key Strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats)*
14.1 Nvidia
Figure 60 Features of Nvidia Drive
Table 106 Nvidia: Business Overview
Figure 61 Nvidia: Company Snapshot
Table 107 Nvidia: Product Offerings
Table 108 Nvidia: Product Launches
Table 109 Nvidia: Deals
14.2 TomTom
Table 110 Maps Offered by TomTom and Its Features
Table 111 TomTom: Business Overview
Figure 62 TomTom: Company Snapshot
Table 112 TomTom: Product Offerings
Table 113 TomTom: Product Launches
Table 114 TomTom: Deals
14.3 Here
Table 115 Here: Business Overview
Figure 63 Here: Company Snapshot
Table 116 Here: Product Offerings
Table 117 Here HD: New Product Developments
Table 118 Here: Deals
14.4 NavInfo
Table 119 NavInfo: Business Overview
Figure 64 NavInfo: Company Snapshot
Table 120 Multi-Layer HD Map by NavInfo
Table 121 NavInfo: Product Offerings
Table 122 NavInfo: Product Launches
Table 123 NavInfo: Deals
14.5 Civil Maps
Table 124 Civil Maps: Business Overview
Table 125 Civil Maps: Product Offerings
Table 126 Civil Maps: Product Launches
Table 127 Civil Maps: Deals
14.6 The Sanborn Map Company
Table 128 The Sanborn Map Company: Business Overview
Table 129 The Sanborn Map Company: Product Offerings
Table 130 The Sanborn Map Company: Product Launches
Table 131 The Sanborn Map Company: Deals
14.7 Momenta
Table 132 Momenta: Business Overview
Table 133 Momenta: Product Offerings
Table 134 Momenta: Product Launches
Table 135 Momenta: Deals
14.8 Navmii
Table 136 Navmii: Business Overview
Table 137 Navmii: Product/Solution Offerings
14.9 Dynamic Map Platform
Table 138 Dynamic Map Company: Business Overview
Table 139 Dynamic Map Company: Product/Solution Offerings
Table 140 Dynamic Map Platform: Deals
14.10 MapMyIndia
Table 141 MapMyIndia: Business Overview
Table 142 MapMyIndia: Product/Solution Offerings
Table 143 MapMyIndia: Deals
14.11 Other Key Players
14.11.1 Asia Oceania
14.11.1.1 RMSI
14.11.1.2 Zenrin
14.11.1.3 Autonavi
14.11.1.4 Baidu
14.11.1.5 Woven Planet
14.11.2 Europe
14.11.2.1 Mapillary
14.11.2.2 Blickfeld
14.11.2.3 Geojunxion
14.11.3 North America
14.11.3.1 Carmera
14.11.3.2 Voxel Maps
14.11.4 RoW
14.11.4.1 Mobileye
*Details on Business Overview, Products Offerings, Recent Developments, Product Launches, Deals, Analyst's View, Key Strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats Might Not be Captured in Case of Unlisted Companies
15 Analyst's Recommendations
15.1 Asia-Pacific Expected to be a Fastest Growing Market
15.2 Cloud-based HD Map: Key Focus Area
15.3 Growing Adoption of HD Maps for Commercial Mobility
15.4 Conclusion
16 Appendix
16.1 Discussion Guide
16.2 Knowledge Store: The Subscription Portal
16.3 Available Customizations
Companies Mentioned
- Alphabet
- Amazon
- Argo AI
- Autonavi
- Baidu
- Blickfeld
- Carmera
- Civil Maps
- Cruise
- Daimler AG
- DHL
- Didi
- Dominos
- Dynamic Map Platform
- Einride
- Ele.me
- Emqopter
- FedEx
- Ford
- General Motors
- Geojunxion
- George Mason University
- Here
- Hyundai
- JD.com
- Kiwibots
- Kroger
- Mapillary
- MapMyIndia
- Mobileye
- Momenta
- NavInfo
- Navmii
- Nuro Autonomous Delivery Robots
- Nvidia
- PepsiCo
- Pony.ai
- RMSI
- SF Express
- Skyways UAV
- Starship Technology
- The Sanborn Map Company
- TomTom
- Toyota
- TuSimple
- University Campuses in California
- Volvo
- Voxel Maps
- Voyage
- Waymo
- Woven Planet
- Zenrin
- Zipline
Table Information
Report Attribute | Details |
---|---|
No. of Pages | 242 |
Published | July 2021 |
Forecast Period | 2021 - 2030 |
Estimated Market Value ( USD | $ 1.4 Billion |
Forecasted Market Value ( USD | $ 16.9 Billion |
Compound Annual Growth Rate | 31.7% |
Regions Covered | Global |
No. of Companies Mentioned | 53 |