自律走行車向けHDマップ市場

出版：MarketsandMarkets

HD Map for Autonomous Vehicles Market by Solution (Cloud-Based & Embedded), LOA(L2, L3, L4, & L5), Usage (Passenger & Commercial), Vehicle Type, Services (Advertisement, Mapping, Localization, Update & Maintenance), & Region – Global Forecast to 2030

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ソリューション別の自動運転車市場のHDマップ（クラウドベースおよび組み込み）、LOA（L2、L3、L4、L5）、使用法（乗用車および商用車）、車両タイプ、サービス（広告、マッピング、ローカリゼーション、更新および保守）

The 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.

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%, CXOs – 20%
•By Designation: C level – 40%, D level – 35%, Others – 25%
•By Region: Asia Pacific- 40%, North America – 20%, Europe – 35%, RoW-5%
Major players profiled in the report are TomTom (Netherlands), HERE (Netherlands), NVIDIA (US), Waymo (US), Baidu (China), Dynamic Map Platform (Japan), and NavInfo (China).

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.

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.

目次

1INTRODUCTION28
1.1OBJECTIVES OF THE STUDY28
1.2MARKET DEFINITION28
1.2.1SEGMENTAL DEFINITIONS, INCLUSIONS, AND EXCLUSIONS29
TABLE 1SEGMENTAL DEFINITIONS, INCLUSIONS, AND EXCLUSIONS: HD MAP FOR AUTONOMOUS VEHICLE MARKET29
TABLE 2OTHER KEY DEFINITIONS30
1.3MARKET SCOPE30
1.3.1MARKETS COVERED30
FIGURE 1MARKETS COVERED: HD MAP FOR AUTONOMOUS VEHICLE MARKET30
1.3.2YEARS CONSIDERED IN THE STUDY31
1.4LIMITATIONS31
1.5STAKEHOLDERS31
1.6SUMMARY OF CHANGES32
2RESEARCH METHODOLOGY33
2.1RESEARCH DATA33
FIGURE 2HD MAP FOR AUTONOMOUS VEHICLE MARKET: RESEARCH DESIGN33
FIGURE 3RESEARCH DESIGN MODEL34
2.2SECONDARY DATA34
2.2.1KEY SECONDARY SOURCES FOR BASE NUMBERS (HD MAP FOR AUTONOMOUS VEHICLE)35
2.2.2KEY SECONDARY SOURCES FOR MARKET SIZING36
2.2.3KEY DATA FROM SECONDARY SOURCES36
2.3PRIMARY DATA37
FIGURE 4BREAKDOWN OF PRIMARY INTERVIEWS37
2.3.1PRIMARY PARTICIPANTS37
2.4MARKET SIZE ESTIMATION38
2.4.1TOP-DOWN APPROACH39
FIGURE 5TOP-DOWN APPROACH: HD MAP FOR AUTONOMOUS VEHICLE MARKET39
FIGURE 6ILLUSTRATION OF HD MAP FOR AUTONOMOUS VEHICLE COMPANY REVENUE ESTIMATION40
FIGURE 7HD MAP FOR AUTONOMOUS VEHICLE MARKET: RESEARCH DESIGN & METHODOLOGY40
2.4.2DATA TRIANGULATION41
2.5MARKET BREAKDOWN42
2.6FACTOR ANALYSIS43
2.7ASSUMPTIONS44
2.7.1KEY ASSUMPTIONS44
2.7.2OTHER RESEARCH ASSUMPTIONS45
2.8RISK ASSESSMENT & RANGES45
TABLE 3RISK ASSESSMENT & RANGES45
2.9RESEARCH LIMITATIONS46
3EXECUTIVE SUMMARY47
FIGURE 8HD MAP FOR AUTONOMOUS VEHICLE MARKET: MARKET OVERVIEW47
FIGURE 9HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION, 2021–203049
FIGURE 10PERSONAL MOBILITY IS ESTIMATED TO LEAD THE HD MAP FOR THE AUTONOMOUS VEHICLE MARKET FROM 2021 TO 203049
4PREMIUM INSIGHTS51
4.1ATTRACTIVE OPPORTUNITIES IN THE HD MAP FOR AUTONOMOUS VEHICLE MARKET51
FIGURE 11INCREASING DEMAND FOR SEMI-AUTONOMOUS VEHICLES AND RISING INVESTMENT FOR THE DEVELOPMENT OF AUTONOMOUS VEHICLE WILL PROPEL THE HD MAP FOR AUTONOMOUS VEHICLE MARKET51
4.2HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION51
FIGURE 12ASIA OCEANIA IS PROJECTED TO BE THE FASTEST GROWING REGION IN HD MAP FOR AUTONOMOUS VEHICLE MARKET DURING 2021−203051
4.3NORTH AMERICA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, LEVEL OF AUTOMATION & VEHICLE TYPE52
FIGURE 13NORTH AMERICA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY LEVEL OF AUTOMATION & VEHICLE TYPE, 2021 VS 2030 (USD MILLION)52
4.4HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SOLUTION TYPE52
FIGURE 14HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SOLUTION TYPE,
2021 VS 2030 (USD MILLION)52
4.5HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SERVICE TYPE53
FIGURE 15HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SERVICE TYPE,
2021 VS 2030 (USD MILLION)53
5MARKET OVERVIEW54
5.1INTRODUCTION54
5.2MARKET DYNAMICS55
FIGURE 16HD MAPS MARKET: MARKET DYNAMICS55
5.2.1DRIVERS55
5.2.1.1Growing trend of autonomous driving55
TABLE 4INVESTMENT BY AUTOMOTIVE COMPANIES IN AUTONOMOUS TECHNOLOGY56
5.2.1.2Increasing adoption of Level 2 and Level 3 ADAS features in the automotive industry56
5.2.1.3Increasing investment by startups in the development of HD maps57
TABLE 5WORLDWIDE DISTRIBUTION OF STARTUPS BY TYPE OF EMBEDDED AUTONOMOUS TECHNOLOGY57
5.2.1.4Increasing partnerships and joint ventures by the key players57
TABLE 6HD MAP MARKET: PARTNERSHIPS/COLLABORATIONS IN HD MAPS ECOSYSTEM58
TABLE 7HD MAP MARKET: OEMS AND ITS HD MAPS SUPPLIERS59
TABLE 8HD MAP MARKET: KEY INVESTMENTS IN HD MAPS ECOSYSTEM60
5.2.1.5Growth in the map data collection60
FIGURE 17CLASSIFICATION OF DIFFERENT ROAD DETECTION APPROACHES DEPENDING ON THE SENSOR AND THE METHODOLOGY61
FIGURE 18DIFFERENT STRATEGIES FOR AUTONOMOUS DRIVING WITH ROAD-LEVEL NAVIGATION AND LANE-LEVEL NAVIGATION61
5.2.1.6Increasing investments in smart city projects62
TABLE 9SMART CITY INITIATIVES AND INVESTMENTS62
5.2.2RESTRAINTS63
5.2.2.1Limited standardization in HD maps63
5.2.2.2Less reliability in untested environments63
5.2.3OPPORTUNITIES63
5.2.3.1Autonomous car renting services63
5.2.3.2Advancement in 5G technology64
FIGURE 195G TECHNOLOGY ECOSYSTEM64
5.2.3.3Increasing demand for real-time data65
FIGURE 20ARCHITECTURE OF REAL-TIME HD MAP CHANGE DETECTION65
FIGURE 21GENERAL STRUCTURE OF LOCALIZATION PROCEDURE66
5.2.4CHALLENGES66
5.2.4.1Legal & Privacy issues regarding HD maps66
5.2.4.2High cost of the technology and autonomous vehicle mapping66
FIGURE 22HD MAPPING PROCESS67
5.2.4.3Large size data collection, processing, and transmission of HD map data67
FIGURE 23DATA FROM AN AUTONOMOUS VEHICLE68
5.3PORTER’S FIVE FORCES68
FIGURE 24PORTER’S FIVE FORCES: HD MAP FOR AUTONOMOUS VEHICLE MARKET69
5.3.1THREAT OF NEW ENTRANTS69
5.3.1.1The key players have collaborations with key OEMs69
5.3.2THREAT OF SUBSTITUTES70
5.3.3BARGAINING POWER OF BUYERS70
5.3.4BARGAINING POWER OF SUPPLIERS70
5.3.5RIVALRY AMONG EXISTING COMPETITORS70
5.3.5.1Many HD map providers partnered to develop HD maps and HD mapping datasets70
5.3.5.2Increasing competition to broaden the customer base70
5.4ROADMAP OF HD MAP FOR AUTONOMOUS VEHICLE71
FIGURE 25ROADMAP OF HD MAP FOR AUTONOMOUS VEHICLE IN URBAN ENVIRONMENT71
5.5VALUE CHAIN ANALYSIS71
FIGURE 26VALUE CHAIN ANALYSIS OF HD MAP FOR AUTONOMOUS VEHICLE72
5.6ECOSYSTEM ANALYSIS73
FIGURE 27ECOSYSTEM ANALYSIS OF HD MAP FOR AUTONOMOUS VEHICLE73
TABLE 10LIST OF KEY PLAYER FROM HD MAP FOR AUTONOMOUS VEHICLE ECOSYSTEM74
FIGURE 28HD MAP FOR AUTONOMOUS VEHICLE ECOSYSTEM MATRIX75
5.7REGULATORY ANALYSIS OF RELATED MARKETS76
5.7.1GENERAL DATA PROTECTION REGULATION76
5.7.2ADAS: REGULATORY OVERVIEW76
5.7.2.1Canada76
5.7.2.2US76
5.7.2.3European Parliament77
5.7.2.4National agency for automotive safety & victims’ aid (NASVA), Japan77
5.7.3AUTONOMOUS VEHICLE: REGULATORY OVERVIEW77
5.7.3.1Enacted legislation and executive orders in the US78
FIGURE 29ENACTED LEGISLATION AND EXECUTIVE ORDERS IN THE US78
5.7.3.2Autonomous vehicle testing area in China79
FIGURE 30AUTONOMOUS VEHICLE TESTING AREA IN CHINA79
5.7.3.3Autonomous vehicle testing area in Germany79
FIGURE 31AUTONOMOUS VEHICLE TESTING AREA IN GERMANY79
5.7.3.4Autonomous vehicle testing area in Singapore80
FIGURE 32AUTONOMOUS VEHICLE TESTING AREA IN SINGAPORE80
5.8HD MAP FOR AUTONOMOUS VEHICLE MARKET, SCENARIOS (2021–2030)80
FIGURE 33HD MAP FOR AUTONOMOUS VEHICLE MARKET– FUTURE TRENDS & SCENARIOS, 2021–2030 (UNITS)81
5.8.1MOST LIKELY SCENARIO81
TABLE 11HD MAP FOR AUTONOMOUS VEHICLE MARKET (MOST LIKELY), BY REGION, 2021–2030 (UNITS)81
5.8.2OPTIMISTIC SCENARIO82
TABLE 12HD MAP FOR AUTONOMOUS VEHICLE MARKET (OPTIMISTIC SCENARIO), BY REGION, 2021–2030 (UNITS)82
5.8.3PESSIMISTIC SCENARIO82
TABLE 13HD MAP FOR AUTONOMOUS VEHICLE MARKET (PESSIMISTIC), BY REGION, 2021–2030 (UNITS)83
6INDUSTRY TRENDS84
6.1TECHNOLOGY OVERVIEW84
FIGURE 34FIVE ERAS OF VEHICLE SAFETY84
FIGURE 35CONNECTED VEHICLE FOR AUTONOMOUS DRIVING84
6.1.1HD MAPS PORTFOLIO FOR ALL AUTOMATION LEVELS85
TABLE 14AUTOMATION LEVELS85
FIGURE 36HD MAPS PORTFOLIO FOR ALL AUTOMATION LEVELS86
6.1.2HD MAP LAYERS86
FIGURE 37HD MAP LAYERS86
6.1.3COMPONENTS USED TO BUILD HD MAPS87
6.1.3.1Hardware87
FIGURE 38SENSORS AND THEIR IMPORTANCE IN AUTONOMOUS VEHICLES87
6.1.3.1.1LiDAR87
6.1.3.1.2Camera87
6.1.3.1.3Radar88
6.1.3.1.4Inertial Measurement Unit (IMU)88
6.1.3.1.5Global Positioning System (GPS)88
6.1.3.2Software88
FIGURE 39FLOW CHART FOR PRODUCTION PROCESS AND MAP DATA SOURCES88
6.1.4ADVANCEMENT IN SLAM ALGORITHM89
6.1.5SELF-HEALING MAPS89
FIGURE 40SELF-HEALING MAP PROCESS90
6.1.6MAPPING STANDARDS91
FIGURE 41FEATURES OF KEY MAPPING STANDARDS91
6.1.6.1SENSORIS91
6.1.6.2ADASIS91
FIGURE 42HD MAP STANDARDS92
6.1.6.3Navigation data standard92
6.1.6.4Vector tile 392
6.1.6.5Open AutoDrive forum92
6.1.7HD 3D VIEWING CUSTOMER EXPERIENCE93
6.1.8EMERGENCE OF AI AND ML TECHNOLOGIES TO BOOST THE 3D CONTENT ACCURACY93
6.1.9ADVENT OF 3D-ENABLED DISPLAY DEVICES FOR A BETTER NAVIGATION EXPERIENCE93
6.1.103D MAPPING TECHNIQUES93
6.1.10.1Photogrammetry93
6.1.10.2LiDAR94
6.1.10.3RADAR94
6.1.10.4SONAR94
FIGURE 43IOT DEVICES IN AUTONOMOUS VEHICLES94
6.1.11HD MAPPING AND BLOCKCHAIN95
6.1.12MACHINE LEARNING POWERED ANALYTICS95
6.1.13SUPPLY CHAIN 4.095
6.1.14LIDAR DRONES FOR MAPPING95
FIGURE 44LIDAR ECOSYSTEM: MAJOR VALUE ADDITION BY LIDAR COMPONENT MANUFACTURERS AND THEIR INTEGRATORS & DISTRIBUTORS96
6.1.15LOCATION OF THINGS96
6.1.16HD MAPPING FOR AUTONOMOUS VEHICLE PROVING GROUNDS96
6.1.17POTENTIAL APPLICATIONS OF HD MAPS OTHER THAN AUTONOMOUS VEHICLES97
TABLE 15BUSINESS MODEL FOR AUTONOMOUS LAST MILE DELIVERY98
FIGURE 45ALGORITHMS AND ANALYTICS SUPPORTING AUTONOMOUS LAST MILE DELIVERY98
6.1.17.1Aerial delivery drones98
TABLE 16EVOLUTION OF AERIAL DELIVERY DRONES99
6.2USE CASES: AERIAL DELIVERY DRONES99
6.2.1USE OF PROJECT WING OF ALPHABET TO DELIVER FOOD AND MEDICINES IN AUSTRALIA99
6.2.2REGULATORS APPROVE TRIAL FLIGHTS OF URBAN FLIGHT DELIVERY SYSTEMS OF DRONE DELIVERY CANADA99
6.2.3ELE.ME STARTS FOOD DELIVERY USING DRONES IN SHANGHAI99
6.2.4SF EXPRESS RECEIVED LICENSE TO START AERIAL DRONE-BASED NETWORK FOR DELIVERIES WITHIN PILOT ZONES OF CHINA99
6.2.5EMQOPTER DELIVERS FOOD PARCELS IN GERMANY USING AERIAL DELIVERY DRONES100
6.2.6SKYWAYS UAV OF AIRBUS HELICOPTERS CONDUCTS ITS FIRST PARCEL DELIVERY IN SINGAPORE100
6.2.7ZIPLINE PLANS TO DELIVER MEDICINES IN AFRICAN REGION USING AERIAL DELIVERY DRONES100
6.2.8DRONE DELIVERIES TO KING’S WALK GOLF COURSE IN GRAND FORKS, NORTH DAKOTA100
6.2.9AMAZON PLANS TO TRANSFORMING PARCEL DELIVERY USING PRIME AIR DELIVERY DRONE100
6.2.10DHL HAS SUCCESSFULLY COMPLETED TRAILS OF BVLOS MEDICINE DELIVERY FLIGHTS ACROSS LAKE VICTORIA, TANZANIA100
6.2.10.1Ground delivery vehicles100
TABLE 17EVOLUTION OF GROUND DELIVERY VEHICLES101
6.3USE CASES: GROUND DELIVERY VEHICLES101
6.3.1NURO AUTONOMOUS DELIVERY ROBOTS PROVIDING COST-EFFECTIVE GROCERY DELIVERY SERVICES FOR KROGER101
6.3.2KIWIBOTS DEPLOYED TO CARRY OUT LOW-COST FOOD DELIVERY SERVICES IN UNIVERSITY CAMPUSES IN CALIFORNIA101
6.3.3PEPSICO DELIVERING SNACKS TO COLLEGE STUDENTS BY A FLEET OF GROUND ROBOTS101
6.3.4FEDEX DELIVERS PARCELS USING SAMEDAY DELIVERY BOT102
6.3.5DOMINOS USING GROUND DELIVERY ROBOTS TO DELIVER PIZZA IN NEW ZEALAND102
6.3.6STARSHIP TECHNOLOGY OFFERING FOOD DELIVERIES AT GEORGE MASON UNIVERSITY’S FAIRFAX CAMPUS102
6.3.7JD.COM STARTED DELIVERIES USING AL EQUIPPED GROUND ROBOTS102
6.3.8AMAZON’S SCOUT GROUND ROBOT TO DELIVER PARCELS IN WASHINGTON102
6.3.9TYPES OF GNSS RECEIVERS102
6.3.9.1Global Positioning System (GPS)102
6.3.9.2Galileo103
6.3.9.3Global Navigation Satellite System (GLONASS)104
6.3.9.4Satellite-based Augmentation System (SBAS)104
TABLE 18SBAS IN DIFFERENT COUNTRIES105
6.3.9.5BeiDou Navigation Satellite System105
6.3.10GIS DATA105
6.3.10.1Types of GIS data models105
6.3.10.1.1Vector data model105
6.3.10.1.2Raster data model105
6.3.10.2Key trends in GIS106
6.3.10.2.1AR and VR technologies106
6.3.10.2.2Unmanned AERIAL Vehicles106
6.3.10.2.3Integration of cloud computing in GIS106
6.3.10.2.4Development of 4D GIS software and augmented reality platforms for GIS107
7HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SERVICE TYPE108
7.1INTRODUCTION109
7.2RESEARCH METHODOLOGY109
7.3ASSUMPTIONS110
TABLE 19ASSUMPTIONS, BY SERVICE TYPE110
FIGURE 46HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SERVICE TYPE,
2021 VS 2030 (USD MILLION)110
TABLE 20HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SERVICE TYPE,
2020–2030 (USD MILLION)111
7.4MAPPING112
TABLE 21HD MAP SEMANTIC INFORMATION112
TABLE 22ROAD SEGMENT DATA (RSD) APPLICATIONS112
TABLE 23POTENTIALLY APPLICABLE MAPPING TECHNOLOGIES, THEIR STRENGTHS AND LIMITATIONS113
TABLE 24MAPWORKS SOFTWARE DEVELOPMENT KIT113
7.4.1THE COMPANIES OFFERING END TO END MAPPING SOLUTIONS FOR AUTONOMOUS VEHICLE IS EXPECTED TO DRIVE NORTH AMERICAN MARKET114
TABLE 25MAPPING: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION, 2020–2030 (USD MILLION)114
7.5LOCALIZATION114
TABLE 26LOCALIZATION TECHNIQUES FOR AUTONOMOUS VEHICLE AND THEIR ACCURACY115
TABLE 27PRIOR INFORMATION IN HD MAP BASED VEHICLE LOCALIZATION115
7.5.1INCREASED INVESTMENT IN THE LOCALIZATION OF HD MAPS TO DRIVE THE MARKET116
TABLE 28LOCALIZATION: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION, 2020–2030 (USD MILLION)116
7.6UPDATES & MAINTENANCE116
7.6.1NEED OF DYNAMIC TRAFFIC, WEATHER INFORMATION AND CONTINUOUSLY UPDATE IN DATA GATHERED BY MAPPING AND LOCALIZATION WILL DRIVE THE MARKET116
TABLE 29UPDATES & MAINTENANCE: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION, 2020–2030 (USD MILLION)116
7.7ADVERTISEMENT117
7.7.1ADVERTISEMENT IS PROJECTED TO BE THE FASTEST-GROWING SEGMENT OF HD MAPS FOR THE AUTONOMOUS VEHICLES MARKET117
TABLE 30ADVERTISEMENT: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION, 2020–2030 (USD MILLION)117
7.8KEY INDUSTRY INSIGHTS118
8HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY LEVEL OF AUTOMATION119
8.1INTRODUCTION120
FIGURE 47HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY AUTOMATION LEVEL, 2021 VS. 2030 (USD MILLION)121
8.2RESEARCH METHODOLOGY121
8.3ASSUMPTIONS122
TABLE 31ASSUMPTIONS, BY LEVEL OF AUTOMATION TYPE122
8.4OPERATIONAL DATA122
TABLE 32RECENT AND ONGOING DEMONSTRATION AND TESTING OF CONNECTED AUTONOMOUS VEHICLES BY KEY COMPANIES122
TABLE 33ECONOMIC IMPACT OF CONNECTED AND AUTONOMOUS VEHICLE AND ITS BREAKDOWN123
TABLE 34HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY AUTOMATION LEVEL, 2020–2030(USD MILLION)123
8.5SEMI-AUTONOMOUS DRIVING VEHICLES124
8.5.1LEVEL 2124
8.5.2LEVEL 3124
8.5.3ASIA OCEANIA REGION IS PROJECTED TO HAVE THE HIGHEST GROWTH RATE125
TABLE 35HD MAP FOR SEMI-AUTONOMOUS VEHICLE MARKET, BY REGION,
2020–2030 (USD MILLION)125
TABLE 36HD MAP FOR SEMI-AUTONOMOUS VEHICLE MARKET, BY LEVEL OF AUTOMATION, 2020–2030 (USD MILLION)125
8.6AUTONOMOUS DRIVING VEHICLES126
TABLE 37EXPECTED TECHNOLOGY VS CURRENT TECHNOLOGY READINESS LEVEL OF AUTONOMOUS VEHICLE126
8.6.1LEVEL 4 & 5 AUTONOMOUS VEHICLE DEVELOPMENT AND DEPLOYMENT126
8.6.1.1Daimler AG126
8.6.1.2TuSimple127
8.6.1.3Argo AI and Ford127
8.6.1.4Baidu128
8.6.1.5DiDi128
8.6.1.6Toyota, Pony.ai, and Hyundai128
8.6.1.7Waymo129
8.6.1.8Voyage129
8.6.1.9General Motors and Cruise129
8.6.1.10Volvo129
8.6.1.11Einride129
8.6.2LEVEL 4130
8.6.3LEVEL 5130
8.6.4TECHNOLOGY READINESS OF AUTONOMOUS VEHICLES IN THE EUROPE REGION IS EXPECTED TO DRIVE THE MARKET131
TABLE 38HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION,
2020–2030 (USD MILLION)131
TABLE 39HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY LEVEL OF AUTOMATION, 2020–2030 (USD MILLION)131
8.7KEY INDUSTRY INSIGHTS132
9HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SOLUTION TYPE133
9.1INTRODUCTION134
FIGURE 48HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SOLUTION TYPE,
2021 VS. 2030 (USD MILLION)134
9.2RESEARCH METHODOLOGY135
9.3ASSUMPTIONS135
TABLE 40ASSUMPTIONS: BY SOLUTION TYPE135
TABLE 41HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SOLUTION TYPE,
2020–2030 (USD MILLION)136
9.4CLOUD-BASED136
FIGURE 49HD MAP PRODUCTION PIPELINE136
9.4.1HIGH FLEXIBILITY AND ACCURACY OFFERED BY CLOUD-BASED HD MAPS ARE EXPECTED TO DRIVE THE MARKET137
TABLE 42CLOUD-BASED: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION, 2020–2030 (USD MILLION)137
9.5EMBEDDED137
9.5.1ASIA OCEANIA REGION OFFERS A HUGE OPPORTUNITY FOR THE GROWTH OF EMBEDDED HD MAPS138
TABLE 43EMBEDDED: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION, 2020–2030 (USD MILLION)138
9.6KEY INDUSTRY INSIGHTS138
10HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY USAGE TYPE139
10.1INTRODUCTION140
FIGURE 50HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY USAGE TYPE,
2021 VS. 2030 (USD MILLION)141
TABLE 44HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY USAGE TYPE,
2020–2030 (USD MILLION)141
10.2RESEARCH METHODOLOGY142
10.3ASSUMPTIONS142
TABLE 45ASSUMPTIONS, BY USAGE TYPE142
10.4OPERATIONAL DATA143
TABLE 46FEW POPULAR ROBO-TAXIS USED FOR PASSENGER TRANSPORTATION ACROSS THE WORLD143
10.5PERSONAL MOBILITY143
10.5.1NORTH AMERICA IS ESTIMATED TO BE THE LARGEST MARKET FOR THE PERSONAL MOBILITY SEGMENT143
TABLE 47PERSONAL MOBILITY: HD MAP FOR AUTONOMOUS VEHICLE, BY REGION, 2020–2030 (USD MILLION)143
10.6COMMERCIAL MOBILITY144
10.6.1INCREASING ADOPTION OF RIDE-SHARING SERVICES AND GROWING PARTNERSHIP BETWEEN KEY RIDE-SHARING COMPANIES WITH PROVIDERS OF HD MAPS WILL PROPEL THE MARKET COMMERCIAL MOBILITY SEGMENT145
TABLE 48COMMERCIAL MOBILITY: HD MAP FOR AUTONOMOUS VEHICLE, BY REGION, 2020–2030 (USD MILLION)145
10.7KEY INDUSTRY INSIGHTS145
11HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY VEHICLE TYPE146
11.1INTRODUCTION147
FIGURE 51HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY VEHICLE TYPE,
2021 VS. 2030 (USD MILLION)148
11.2RESEARCH METHODOLOGY148
11.3ASSUMPTIONS149
TABLE 49ASSUMPTIONS: BY VEHICLE TYPE149
11.4OPERATIONAL DATA149
TABLE 50EXISTING PRODUCTS AND SOLUTIONS OFFERED BY HD MAP PROVIDERS149
TABLE 51FEW POPULAR AUTONOMOUS SHUTTLES FROM COMPANIES ACROSS THE WORLD150
TABLE 52TRUCK ROUTING ATTRIBUTES AND CONSIDERATIONS150
TABLE 53US HOURS OF SERVICE REGULATIONS150
TABLE 54KEY PLAYERS IN THE GLOBAL TRUCK PLATOONING MARKET151
TABLE 55HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY VEHICLE TYPE,
2020–2030 (USD MILLION)151
11.5PASSENGER CAR152
11.5.1THE PASSENGER CAR SEGMENT HOLDS THE LARGEST SHARE OF THE HD MAP FOR THE AUTONOMOUS VEHICLE MARKET153
TABLE 56PASSENGER CAR: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION, 2020–2030 (USD MILLION)153
11.6COMMERCIAL VEHICLES154
11.6.1GROWING INVESTMENT BY TRUCK MANUFACTURERS IN AUTONOMOUS VEHICLE TECHNOLOGY TO DRIVE THE COMMERCIAL VEHICLE SEGMENT MARKET154
TABLE 57COMMERCIAL VEHICLE: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION, 2020–2030 (USD MILLION)154
11.7KEY INDUSTRY INSIGHTS155
12HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION156
12.1INTRODUCTION157
TABLE 58NCAP REGULATIONS: US AND EUROPEAN UNION158
TABLE 59PHASES IN AUTONOMOUS VEHICLE DEVELOPMENT AND IMPACTS158
FIGURE 52HD MAPS FOR AUTONOMOUS MARKET, BY REGION,
2021 VS 2030 (USD MILLION)159
TABLE 60HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY REGION,
2020–2030 (USD MILLION)160
12.2NORTH AMERICA161
FIGURE 53NORTH AMERICA: HD MAP FOR AUTONOMOUS VEHICLE MARKET SNAPSHOT161
TABLE 61NORTH AMERICA: AUTONOMOUS VEHICLE EFFORTS162
TABLE 62PHASES IN AUTONOMOUS VEHICLE DEVELOPMENT IN THE US AND ITS IMPACT ON HD MAPS163
TABLE 63NORTH AMERICA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY VEHICLE TYPE, 2020–2030 (USD MILLION)163
TABLE 64NORTH AMERICA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY AUTOMATION LEVEL, 2020–2030 (USD MILLION)164
TABLE 65NORTH AMERICA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY USAGE TYPE, 2020–2030 (USD MILLION)164
TABLE 66NORTH AMERICA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SOLUTION TYPE, 2020–2030 (USD MILLION)164
TABLE 67NORTH AMERICA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SERVICE TYPE, 2020–2030 (USD MILLION)164
12.2.1US165
TABLE 68US: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)165
12.2.2MEXICO165
TABLE 69MEXICO: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)165
12.2.3CANADA166
TABLE 70CANADA: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)166
12.3ASIA OCEANIA166
FIGURE 54ASIA OCEANIA: SNAPSHOT167
TABLE 71ASIA OCEANIA: AUTONOMOUS VEHICLE EFFORTS167
TABLE 72ASIA OCEANIA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY VEHICLE TYPE, 2020–2030 (USD MILLION)168
TABLE 73ASIA OCEANIA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY AUTOMATION LEVEL, 2020–2030 (USD MILLION)168
TABLE 74ASIA OCEANIA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY USAGE TYPE, 2020–2030 (USD MILLION)168
TABLE 75ASIA OCEANIA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SOLUTION TYPE, 2020–2030 (USD MILLION)168
TABLE 76ASIA OCEANIA: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SERVICE TYPE, 2020–2030 (USD MILLION)169
12.3.1CHINA169
TABLE 77CHINA: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)170
TABLE 78KEY COMPANIES IN AUTONOMOUS VEHICLE TECHNOLOGY AND THEIR KNOWN PARTNERS IN CHINA170
TABLE 79CHINA AUTONOMOUS VEHICLE TESTING RECORDS171
12.3.2JAPAN171
TABLE 80JAPAN: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)171
12.3.3INDIA172
TABLE 81INDIA: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)172
12.3.4SOUTH KOREA172
TABLE 82SOUTH KOREA: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)172
12.4EUROPE172
FIGURE 55EUROPE: HD MAP FOR AUTONOMOUS VEHICLE MARKET SNAPSHOT173
TABLE 83EUROPE: EFFORTS TOWARDS AUTONOMOUS VEHICLES173
TABLE 84EUROPE: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY VEHICLE TYPE, 2020–2030 (USD MILLION)175
TABLE 85EUROPE: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY LEVEL OF AUTOMATION, 2020–2030 (USD MILLION)175
TABLE 86EUROPE: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY USAGE TYPE, 2020–2030 (USD MILLION)176
TABLE 87EUROPE: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SOLUTION TYPE, 2020–2030 (USD MILLION)176
TABLE 88EUROPE: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SERVICE TYPE, 2020–2030 (USD MILLION)176
12.4.1GERMANY177
TABLE 89GERMANY: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)177
12.4.2SPAIN177
TABLE 90SPAIN: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)177
12.4.3ITALY178
TABLE 91ITALY: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)178
12.4.4FRANCE178
TABLE 92FRANCE: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)178
12.4.5UK179
TABLE 93UK: VEHICLE PRODUCTION DATA, 2019-2020 (UNITS)179
12.5ROW179
FIGURE 56ROW: HD MAP FOR AUTONOMOUS VEHICLE MARKET,
2021 VS. 2030 (USD MILLION)180
TABLE 94ROW: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY VEHICLE TYPE, 2020–2030 (USD MILLION)180
TABLE 95ROW: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY AUTOMATION LEVEL, 2020–2030 (USD MILLION)180
TABLE 96ROW: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY USAGE TYPE, 2020–2030 (USD MILLION)181
TABLE 97ROW: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SOLUTION TYPE, 2020–2030 (USD MILLION)181
TABLE 98ROW: HD MAP FOR AUTONOMOUS VEHICLE MARKET, BY SERVICE TYPE, 2020–2030 (USD MILLION)181
12.5.1BRAZIL182
TABLE 99BRAZIL: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)182
12.5.2SOUTH AFRICA182
TABLE 100SOUTH AFRICA: VEHICLE PRODUCTION DATA, 2018-2020 (UNITS)182
12.5.3ISRAEL182
13COMPETITIVE LANDSCAPE183
13.1OVERVIEW183
TABLE 101OVERVIEW OF STRATEGIES ADOPTED BY KEY PLAYERS IN THE HD MAP FOR AUTONOMOUS VEHICLE MARKET183
13.2MARKET RANKING ANALYSIS184
FIGURE 57MARKET RANKING ANALYSIS: HD MAP FOR AUTONOMOUS VEHICLE MARKET184
13.3COMPETITIVE LEADERSHIP MAPPING185
13.3.1STARS185
13.3.2EMERGING LEADERS185
13.3.3PERVASIVE186
13.3.4PARTICIPANTS186
FIGURE 58HD MAPS FOR AUTONOMOUS VEHICLES MARKET: COMPETITIVE LEADERSHIP MAPPING, 2021186
TABLE 102HD MAPS FOR AUTONOMOUS VEHICLES MARKET: COMPANY FOOTPRINT, 2021187
TABLE 103HD MAPS FOR AUTONOMOUS VEHICLES MARKET: SOLUTION FOOTPRINT, 2021188
TABLE 104HD MAPS FOR AUTONOMOUS VEHICLES MARKET: REGIONAL FOOTPRINT, 2021189
13.4SME COMPETITIVE LEADERSHIP MAPPING190
13.4.1PROGRESSIVE COMPANIES190
13.4.2RESPONSIVE COMPANIES190
13.4.3DYNAMIC COMPANIES190
13.4.4STARTING BLOCKS190
FIGURE 59HD MAP FOR AUTONOMOUS VEHICLES MARKET: SME/STARTUP COMPETITIVE LEADERSHIP MAPPING, 2021191
TABLE 105WINNERS VS. TAIL-ENDERS192
14COMPANY PROFILES193
(Business overview, Products offerings, Recent developments, Product launches, Deals, MNM view, Key strengths/Right to win, Strategic choices made, and Weaknesses and competitive threats)*
14.1NVIDIA193
FIGURE 60FEATURES OF NVIDIA DRIVE193
TABLE 106NVIDIA: BUSINESS OVERVIEW194
FIGURE 61NVIDIA: COMPANY SNAPSHOT194
TABLE 107NVIDIA: PRODUCT OFFERINGS195
TABLE 108NVIDIA: PRODUCT LAUNCHES195
TABLE 109NVIDIA: DEALS196
14.2TOMTOM198
TABLE 110MAPS OFFERED BY TOMTOM AND ITS FEATURES198
TABLE 111TOMTOM: BUSINESS OVERVIEW199
FIGURE 62TOMTOM: COMPANY SNAPSHOT200
TABLE 112TOMTOM: PRODUCT OFFERINGS200
TABLE 113TOMTOM: PRODUCT LAUNCHES201
TABLE 114TOMTOM: DEALS201
14.3HERE204
TABLE 115HERE: BUSINESS OVERVIEW204
FIGURE 63HERE: COMPANY SNAPSHOT205
TABLE 116HERE: PRODUCT OFFERINGS205
TABLE 117HERE HD: NEW PRODUCT DEVELOPMENTS206
TABLE 118HERE: DEALS206
14.4NAVINFO209
TABLE 119NAVINFO: BUSINESS OVERVIEW209
FIGURE 64NAVINFO: COMPANY SNAPSHOT210
TABLE 120MULTI-LAYER HD MAP BY NAVINFO210
TABLE 121NAVINFO: PRODUCT OFFERINGS211
TABLE 122NAVINFO: PRODUCT LAUNCHES211
TABLE 123NAVINFO: DEALS211
14.5CIVIL MAPS214
TABLE 124CIVIL MAPS: BUSINESS OVERVIEW214
TABLE 125CIVIL MAPS: PRODUCT OFFERINGS214
TABLE 126CIVIL MAPS: PRODUCT LAUNCHES215
TABLE 127CIVIL MAPS: DEALS215
14.6THE SANBORN MAP COMPANY216
TABLE 128THE SANBORN MAP COMPANY: BUSINESS OVERVIEW216
TABLE 129THE SANBORN MAP COMPANY: PRODUCT OFFERINGS216
TABLE 130THE SANBORN MAP COMPANY: PRODUCT LAUNCHES217
TABLE 131THE SANBORN MAP COMPANY: DEALS217
14.7MOMENTA218
TABLE 132MOMENTA: BUSINESS OVERVIEW218
TABLE 133MOMENTA: PRODUCT OFFERINGS219
TABLE 134MOMENTA : PRODUCT LAUNCHES219
TABLE 135MOMENTA: DEALS220
14.8NAVMII222
TABLE 136NAVMII: BUSINESS OVERVIEW222
TABLE 137NAVMII: PRODUCT/SOLUTION OFFERINGS222
14.9DYNAMIC MAP PLATFORM223
TABLE 138DYNAMIC MAP COMPANY: BUSINESS OVERVIEW223
TABLE 139DYNAMIC MAP COMPANY: PRODUCT/SOLUTION OFFERINGS223
TABLE 140DYNAMIC MAP PLATFORM: DEALS224
14.10MAPMYINDIA226
TABLE 141MAPMYINDIA: BUSINESS OVERVIEW226
TABLE 142MAPMYINDIA: PRODUCT/SOLUTION OFFERINGS226
TABLE 143MAPMYINDIA: DEALS227
14.11OTHER KEY PLAYERS228
14.11.1ASIA OCEANIA228
14.11.1.1RMSI228
14.11.1.2Zenrin229
14.11.1.3AutoNavi229
14.11.1.4Baidu230
14.11.1.5Woven Planet231
14.11.2EUROPE232
14.11.2.1Mapillary232
14.11.2.2Blickfeld233
14.11.2.3Geojunxion234
14.11.3NORTH AMERICA235
14.11.3.1CARMERA235
14.11.3.2Voxel Maps236
14.11.4ROW237
14.11.4.1Mobileye237
*Details on Business overview, Products offerings, Recent developments, Product launches, Deals, MNM view, Key strengths/Right to win, Strategic choices made, and Weaknesses and competitive threats might not be captured in case of unlisted companies.
15RECOMMENDATIONS BY MARKETSANDMARKETS238
15.1ASIA PACIFIC EXPECTED TO BE A FASTEST GROWING MARKET238
15.2CLOUD-BASED HD MAP: KEY FOCUS AREA238
15.3GROWING ADOPTION OF HD MAPS FOR COMMERCIAL MOBILITY239
15.4CONCLUSION239
16APPENDIX240
16.1DISCUSSION GUIDE240
16.2KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL244
16.3AVAILABLE CUSTOMIZATIONS246
16.4AUTHOR DETAILS247

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