세계의 자율주행용 HD 지도 시장(-2032년) : 서비스 유형(맵핑 및 현지화, 업데이트 및 유지보수), 차량 유형(PC 및 CV), 솔루션 유형(임베디드 및 클라우드), 이용 형태, 자동화 수준(L2, L3, L4, L5), 지역별

The HD maps for autonomous driving market is projected to grow from USD 1.09 billion in 2025 to USD 2.19 billion by 2032, at a CAGR of 10.5%.

The HD maps for autonomous driving market is growing with the rise of semantic mapping, where maps show roads and interpret objects, such as traffic lights, crosswalks, and lane markings for contextual awareness. Another emerging trend is the use of blockchain and secure data-sharing frameworks to ensure reliability and trust in map updates across fleets. In addition, energy-efficient mapping techniques are gaining attention to reduce the computational load on autonomous vehicles while maintaining accuracy. Data for HD maps is typically collected through fleets of sensor-equipped vehicles using LiDAR, cameras, GPS, and radar, which continuously capture and update detailed road and environment information. This crowdsourced and sensor-fusion approach ensures maps remain precise and up to date for autonomous driving. All these factors are boosting the growth of the HD maps for autonomous driving market.

The embedded segment is projected to account for a significant share during the forecast period.

By solution type, the embedded segment is projected to account for a significant share during the forecast period. Embedded solutions offer real-time, high-precision localization and navigation directly within a vehicle's onboard systems, processing mapping data locally to reduce latency and enable faster response times critical for safety in dynamic driving environments. These systems operate independently of cloud connectivity, providing enhanced reliability and resilience, especially in areas with limited or no network coverage. By seamlessly integrating real-time data from sensors and vehicle-to-everything (V2X) communication, embedded solutions ensure that HD maps remain current and accurate, supporting the continuous updates required by autonomous vehicles. The growing complexity of urban infrastructure and the need for detailed environmental understanding further drive the demand for sophisticated embedded mapping systems capable of handling intricate road geometries and traffic scenarios. With advancements in semiconductor technology and sensor fusion algorithms, these systems are becoming increasingly cost-effective and efficient.

Companies such as HERE (Netherlands), Baidu Inc. (China), Hyundai Autoever Corporation (South Korea), and Mapbox (US) offer embedded HD Map solutions. The Volvo EX90 and Polestar 3 were among the first to feature Google's embedded HD maps to improve driver assistance. NIO also provides an offline mode for its HD maps in the Navigation on Pilot system of the NIO ET7, allowing use in areas with weak or no internet connection. Similarly, BMW's Personal Pilot Level 2+ system uses HERE Technologies' embedded HD maps to enable "on-map" driving.

The autonomous vehicles segment is projected to grow at a significant rate during the forecast period.

By level of automation, the autonomous vehicles segment is projected to grow at a significant rate during the forecast period. The growth of HD maps in autonomous vehicles, including Level 4 and Level 5 autonomy, is driven by major advancements in AI, HD mapping, LiDAR, and sensor fusion, making fully autonomous driving possible without human input. Increasing investments in robotaxis, autonomous shuttles, and logistics fleets, supported by government smart mobility programs, are speeding up large-scale adoption. The launch of commercial robotaxi services by companies such as Waymo, Uber, and Baidu Apollo in selected urban areas further boosts the market. These players use HD maps to provide centimeter-level localization, detailed road understanding, and real-time navigation for safe autonomous driving. This helps them improve ride reliability, enhance passenger safety, and ensure smooth operation in complex urban environments.

In September 2025, Uber Technologies (China) and Momenta (China) plan to begin testing Level 4 autonomous robotaxi services in Munich, Germany. Similarly, in August 2025, Kia partnered with Autonomous A2Z to develop Level 4 self-driving cars using Kia's PBV (Platform Beyond Vehicle) system, with plans to showcase these vehicles at the 2025 Asia Pacific Economic Cooperation summit in Gyeongju, South Korea. In addition, the use of autonomous driving in freight and delivery operations helps lower costs and tackle driver shortages, creating more opportunities for HD maps.

"Europe is projected to grow at the highest rate during the forecast period."

Europe is projected to grow at the highest rate in the HD maps for autonomous driving market during the forecast period. The demand for HD maps in Europe will be driven by stringent EU safety regulations, the expansion of Level 2+ and Level 3 semi-autonomous driving features in premium vehicles, and strong government backing for smart mobility and connected infrastructure. Growing autonomous trials in urban mobility further accelerate adoption.

Companies such as HERE (Netherlands), TomTom International BV (Netherlands), and Navmii (UK) provide HD maps for autonomous driving vehicles in Europe. In August 2025, HERE partnered with DAF Trucks N.V. in the EU co-funded MODI Project to advance and test Level 4 automated freight transport across Europe. In this project, DAF contributes its expertise in commercial vehicles. At the same time, HERE provides its High-Definition Live Map (HDLM), which functions as an external sensor, with data collected from DAF's sensor-equipped automated trucks feeding into HERE's platform to keep the maps continuously updated for safe and reliable operations. Likewise, in April 2025, HERE signed an MoU with Lotus Robotics, the intelligent driving division of Lotus Technology, to develop an advanced Highway Navigation Pilot that delivers Level 2+ (L2+) automated driving functions. The partnership combined Lotus's sensor perception stack with HERE's high-precision maps to enable safer, more advanced driving features, including hands-off driving in certain conditions. The solution, planned for European approval in 2025, will be used in future Lotus vehicles and offered to other automakers.

In-depth interviews were conducted with CEOs, marketing directors, other innovation and technology directors, and executives from various key organizations operating in this market.

• By Company Type: OEM - 8%, Tier I - 74%, and Tier 2/3 - 8%
• By Designation: CXOs - 36%, Managers - 51%, and Executives - 13%
• By Region: North America - 24%, Europe - 30%, Asia Pacific - 38%, and ROW - 8%

The HD maps for autonomous driving market is dominated by major players, including HERE (Netherlands), Baidu, Inc. (China), TomTom International BV (Netherlands), NVIDIA Corporation (US), and Mobileye (Israel). These companies offer highly detailed, lane-level HD maps with real-time updates to support autonomous driving and ADAS. They also provide value-added services, such as dynamic map layers (traffic, road conditions, and weather), cloud-based map delivery platforms, crowdsourced data integration, sensor fusion solutions, and software tools for path planning, localization, and navigation.

Research Coverage

The report covers the HD maps for autonomous driving market by service type (mapping & localization, update & maintenance, and advertisement), vehicle type (passenger car and commercial vehicle), solution type (embedded and cloud-based), usage type, level of automation, and region. It covers the major HD maps' competitive landscape and company profiles for autonomous driving market ecosystem players.

The study also includes an in-depth competitive analysis of the key market players, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.

Key Benefits of Buying the Report

• The report will help market leaders/new entrants with information on the closest approximations of revenue numbers for the overall HD maps for autonomous driving market and its subsegments.
• This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and plan suitable go-to-market strategies.
• The report will help stakeholders understand the market pulse and provide information on key market drivers, restraints, challenges, and opportunities.

The Report Provides Insight into the Following Pointers:

• Analysis of key drivers (Rising penetration of autonomous vehicles in the global mobility ecosystem, focus on leveraging next-gen mapping and data collection for enhanced navigation, emergence of autonomous urban mobility applications, increasing adoption of L2 and L3 ADAS-equipped vehicles), restraints (lack of global standardization, less reliability in untested environments), opportunities (integration with traffic and infrastructure systems for optimized urban navigation, map-as-a-service enabling scalable and flexible adoption, adoption in emerging markets with 5G expansion), and challenges (high cost of development and maintenance, complex real-time merging of multi-sensor data, dependence on high-bandwidth networks and advanced edge computing infrastructure).
• Product Development/Innovation: Detailed insights into upcoming technologies and research & development activities in the HD maps for autonomous driving market
• Market Development: Comprehensive information about lucrative markets across varied regions
• Market Diversification: Exhaustive information about untapped geographies, recent developments, and investments in the HD maps for autonomous driving market
• Competitive Assessment: In-depth assessment of market share, growth strategies, and product offerings of leading players, such as HERE (Netherlands), Baidu, Inc. (China), TomTom International BV (Netherlands), NVIDIA Corporation (US), and Mobileye (Israel) in the HD maps for autonomous driving market

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
• 1.3 STUDY SCOPE
  • 1.3.1 MARKET SEGMENTATION AND REGIONAL SCOPE
  • 1.3.2 INCLUSIONS & EXCLUSIONS
• 1.4 YEARS CONSIDERED
• 1.5 CURRENCY CONSIDERED
• 1.6 UNIT CONSIDERED
• 1.7 STAKEHOLDERS
• 1.8 SUMMARY OF STRATEGIC CHANGES

2 RESEARCH METHODOLOGY

• 2.1 RESEARCH DATA
  • 2.1.1 SECONDARY DATA
    • 2.1.1.1 Key secondary sources
    • 2.1.1.2 Key data from secondary sources
  • 2.1.2 PRIMARY DATA
    • 2.1.2.1 Key data from primary sources
    • 2.1.2.2 Key primary participants
    • 2.1.2.3 Breakdown of primary interviews
    • 2.1.2.4 Key industry insights
    • 2.1.2.5 Primary interviewees
• 2.2 MARKET SIZE ESTIMATION
  • 2.2.1 TOP-DOWN APPROACH
  • 2.2.2 BASE NUMBER CALCULATION
  • 2.2.3 MARKET FORECAST APPROACH
    • 2.2.3.1 Supply side
    • 2.2.3.2 Demand side
• 2.3 DATA TRIANGULATION
• 2.4 FACTOR ANALYSIS
• 2.5 RESEARCH ASSUMPTIONS
• 2.6 RESEARCH LIMITATIONS
• 2.7 RISK ASSESSMENT

3 EXECUTIVE SUMMARY

• 3.1 KEY INSIGHTS AND MARKET HIGHLIGHTS
• 3.2 KEY MARKET PARTICIPANTS: INSIGHTS AND STRATEGIC DEVELOPMENTS
• 3.3 DISRUPTIVE TRENDS SHAPING MARKET
• 3.4 HIGH-GROWTH SEGMENTS & EMERGING FRONTIERS
• 3.5 SNAPSHOT: GLOBAL MARKET SIZE, GROWTH RATE, AND FORECAST

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN HD MAPS FOR AUTONOMOUS DRIVING MARKET
• 4.2 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY SERVICE TYPE
• 4.3 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY VEHICLE TYPE
• 4.4 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY SOLUTION TYPE
• 4.5 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY LEVEL OF AUTOMATION
• 4.6 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY USAGE TYPE
• 4.7 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY REGION

5 MARKET OVERVIEW

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Rising penetration of autonomous vehicles into global mobility ecosystem
    • 5.2.1.2 Focus on leveraging next-gen mapping and data collection for enhanced navigation
    • 5.2.1.3 Emergence of autonomous urban mobility applications
    • 5.2.1.4 Increasing adoption of L2 and L3 ADAS-equipped vehicles
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Lack of global standardization
    • 5.2.2.2 Less reliability in untested environments
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Integration with traffic and infrastructure systems for optimized urban navigation
    • 5.2.3.2 Map-as-a-service enabling scalable and flexible adoption
    • 5.2.3.3 Adoption in emerging markets with 5G expansion
  • 5.2.4 CHALLENGES
    • 5.2.4.1 High cost of development and maintenance
    • 5.2.4.2 Complex real-time merging of multi-sensor data
    • 5.2.4.3 Dependence on high-bandwidth networks and advanced edge computing infrastructure

6 INDUSTRY TRENDS

• 6.1 MACROECONOMIC INDICATORS
  • 6.1.1 INTRODUCTION
  • 6.1.2 GDP TRENDS AND FORECAST
  • 6.1.3 TRENDS IN GLOBAL AUTONOMOUS DRIVING INDUSTRY
  • 6.1.4 TRENDS IN GLOBAL AUTOMOTIVE & TRANSPORTATION INDUSTRY
• 6.2 ECOSYSTEM ANALYSIS
  • 6.2.1 HD MAP PROVIDERS
  • 6.2.2 AUTONOMOUS DRIVING SOFTWARE/PLATFORM PROVIDERS
  • 6.2.3 CLOUD INFRASTRUCTURE PROVIDERS
  • 6.2.4 SENSOR PROVIDERS
  • 6.2.5 TELEMATICS & CONNECTIVITY PROVIDERS
  • 6.2.6 OEMS
  • 6.2.7 FLEET OPERATORS/MOBILITY PROVIDERS
• 6.3 SUPPLY CHAIN ANALYSIS
• 6.4 PRICING ANALYSIS
  • 6.4.1 INDICATIVE PRICING OF AUTONOMOUS DRIVING SOFTWARE SUITE OFFERED BY KEY PLAYERS
  • 6.4.2 AVERAGE SELLING PRICE TREND, BY REGION
• 6.5 KEY STAKEHOLDERS & BUYING CRITERIA
  • 6.5.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 6.5.2 BUYING CRITERIA
  • 6.5.3 ADOPTION BARRIERS & INTERNAL CHALLENGES
  • 6.5.4 MARKET PROFITABILITY
    • 6.5.4.1 Revenue potential
    • 6.5.4.2 Cost dynamics
    • 6.5.4.3 Margin opportunities, by application
  • 6.5.5 DECISION-MAKING PROCESS
• 6.6 CASE STUDY ANALYSIS
  • 6.6.1 MERCEDES-BENZ INTEGRATED HERE'S HD LIVE MAP INTO ITS DRIVE PILOT SYSTEM
  • 6.6.2 INTELLIAS CONCEPTUALIZED, DEVELOPED, AND SCALED CLOUD-BASED HD MAPPING AND LOCATION DATA PLATFORM FOR AUTONOMOUS DRIVING
  • 6.6.3 MAGNASOFT DEPLOYED AI-DRIVEN CONTINUOUS IMPROVEMENT PROCESSES THAT ENABLED REAL-TIME DETECTION OF CHANGES IN TRAFFIC PATTERNS AND ROAD CONDITIONS
  • 6.6.4 INFOSYS DEPLOYED MULTI-SOURCE HD MAPPING SOLUTION SPECIFICALLY DESIGNED FOR ADAS IN URBAN ENVIRONMENTS
• 6.7 INVESTMENT & FUNDING SCENARIO
• 6.8 STRATEGIC OUTLOOK AND GROWTH OPPORTUNITIES
  • 6.8.1 INTERCONNECTED MARKETS AND CROSS-SECTOR OPPORTUNITIES
    • 6.8.1.1 Interconnected markets
    • 6.8.1.2 Cross-sector opportunities
  • 6.8.2 STRATEGIC MOVES BY OEMS AND TIER-1 & TIER-2/3 PLAYERS
• 6.9 TRADE ANALYSIS
  • 6.9.1 IMPORT SCENARIO (HS CODE 852691)
  • 6.9.2 EXPORT SCENARIO (HS CODE 852691)
• 6.10 KEY CONFERENCES & EVENTS, 2025-2026
• 6.11 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
• 6.12 REGULATORY LANDSCAPE
  • 6.12.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 6.12.2 KEY REGULATIONS
  • 6.12.3 REGULATIONS GOVERNING AUTONOMOUS VEHICLE USAGE, BY COUNTRY
• 6.13 PATENT ANALYSIS
  • 6.13.1 INTRODUCTION
  • 6.13.2 METHODOLOGY
  • 6.13.3 DOCUMENT TYPE
  • 6.13.4 INSIGHTS
  • 6.13.5 LEGAL STATUS OF PATENTS
  • 6.13.6 JURISDICTION ANALYSIS
  • 6.13.7 TOP PATENT APPLICANTS
  • 6.13.8 LIST OF PATENTS
• 6.14 IMPACT OF GENERATIVE AI ON HD MAPS FOR AUTONOMOUS DRIVING MARKET
  • 6.14.1 ACCELERATED MAP CREATION AND UPDATES
  • 6.14.2 ENHANCED LOCALIZATION ACCURACY
  • 6.14.3 COST REDUCTION THROUGH SYNTHETIC DATA
  • 6.14.4 DYNAMIC MAP PERSONALIZATION
• 6.15 HYBRID MAPPING STRATEGIES FOR ENHANCING ADAS DEVELOPMENT
• 6.16 IMPACT OF MAPLESS AUTONOMY CONCEPT ON HD MAPS
• 6.17 EVOLVING BUSINESS MODELS FOR HD MAPPING IN AUTONOMOUS MOBILITY
  • 6.17.1 LICENSING AND SUBSCRIPTION-BASED MODEL
  • 6.17.2 CROWDSOURCED MAPPING AND DATA-AS-A-SERVICE (DAAS)
  • 6.17.3 PAY-PER-USE MODEL
• 6.18 MNM INSIGHTS ON KEY INDUSTRY SOLUTIONS FOR LOCALIZATION
  • 6.18.1 GNSS AND AUGMENTED POSITIONING
  • 6.18.2 HD MAP-BASED LOCALIZATION
  • 6.18.3 LIDAR AND CAMERA-BASED LOCALIZATION
  • 6.18.4 SENSOR FUSION
  • 6.18.5 V2X-ENABLED COOPERATIVE LOCALIZATION
• 6.19 HD MAP DATA FORMATS AND STANDARDIZATION LANDSCAPE
  • 6.19.1 CORE COMPONENTS OF HD MAP DATA
    • 6.19.1.1 Geometric layer
    • 6.19.1.2 Semantic layer
    • 6.19.1.3 Localization layer
    • 6.19.1.4 Dynamic/Update layer
  • 6.19.2 KEY STANDARDS AND FORMATS
• 6.20 PHASED ADOPTION STRATEGY OF HD MAPS IN AV ECOSYSTEM
  • 6.20.1 ASSISTED DRIVING & PILOT DEPLOYMENTS
  • 6.20.2 LIMITED AUTONOMY IN CONTROLLED ENVIRONMENTS
  • 6.20.3 EXPANDED COVERAGE & REAL-TIME UPDATES
  • 6.20.4 FULL AUTONOMY & ECOSYSTEM INTEGRATION
• 6.21 KEY EMERGING TECHNOLOGIES
  • 6.21.1 INTRODUCTION
  • 6.21.2 MULTI-SENSOR FUSION FOR HIGH PRECISION HD MAPPING WITH LIDAR, RADAR, AND CAMERAS
  • 6.21.3 SLAM (SIMULTANEOUS LOCALIZATION AND MAPPING) IN HD MAPS FOR AUTONOMOUS DRIVING
  • 6.21.4 5G CONNECTIVITY AND VEHICLE-TO-EVERYTHING (V2X) TECHNOLOGY FOR AUTONOMOUS DRIVING
• 6.22 COMPLEMENTARY TECHNOLOGIES
  • 6.22.1 SECURING AND VALIDATING HD MAPS WITH BLOCKCHAIN
  • 6.22.2 ENHANCING HD MAPS WITH MACHINE LEARNING (ML)-POWERED ANALYTICS
• 6.23 TECHNOLOGY/PRODUCT ROADMAP
  • 6.23.1 SHORT-TERM (2025-2027) | FOUNDATION & EARLY COMMERCIALIZATION
  • 6.23.2 MID-TERM (2028-2030) | EXPANSION & STANDARDIZATION
  • 6.23.3 LONG-TERM (2031-2035+) | MASS COMMERCIALIZATION & DISRUPTION
• 6.24 HD MAPPING SERVICE PROVIDERS: COMPETITIVE LANDSCAPE
• 6.25 COMPARATIVE ANALYSIS OF OEM HD MAPPING SOLUTIONS
• 6.26 FUTURE APPLICATIONS OF HD MAPS
• 6.27 SUCCESS STORIES AND REAL-WORLD APPLICATIONS
  • 6.27.1 WAYMO'S COMMERCIAL ROBOTAXI OPERATIONS IN US
  • 6.27.2 MOBILEYE REM: CROWDSOURCED HD MAPPING ACROSS EUROPE
  • 6.27.3 BAIDU APOLLO GO: CHINA'S ROBOTAXI EXPANSION

7 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY LEVEL OF AUTOMATION

• 7.1 INTRODUCTION
• 7.2 SEMI-AUTONOMOUS VEHICLE
  • 7.2.1 GROWING DEMAND FOR ADVANCED ADAS-EQUIPPED VEHICLES TO DRIVE MARKET
  • 7.2.2 LEVEL 2
  • 7.2.3 LEVEL 3
• 7.3 AUTONOMOUS VEHICLE
  • 7.3.1 RISING USE OF AUTONOMOUS DRIVING VEHICLES IN URBAN MOBILITY OPERATIONS TO DRIVE DEMAND
  • 7.3.2 LEVEL 4
  • 7.3.3 LEVEL 5
• 7.4 KEY PRIMARY INSIGHTS

8 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY SERVICE TYPE

• 8.1 INTRODUCTION
• 8.2 MAPPING & LOCALIZATION
  • 8.2.1 INTEGRATION OF AI, 5G, AND CROWDSOURCED DATA IN HD MAPS TO DRIVE MARKET
• 8.3 UPDATE & MAINTENANCE
  • 8.3.1 RISING NEED FOR REAL-TIME HD MAP UPDATES AND PREDICTIVE MAINTENANCE TO DRIVE MARKET
• 8.4 ADVERTISEMENT
• 8.5 KEY PRIMARY INSIGHTS

9 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY SOLUTION TYPE

• 9.1 INTRODUCTION
• 9.2 EMBEDDED
  • 9.2.1 DEMAND FOR ONBOARD MAPPING AND SENSOR FUSION TECHNOLOGIES TO DRIVE MARKET
• 9.3 CLOUD-BASED
  • 9.3.1 FOCUS ON ADOPTING SCALABLE CLOUD PLATFORMS FOR AUTONOMOUS NAVIGATION TO DRIVE MARKET
• 9.4 KEY PRIMARY INSIGHTS

10 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY USAGE TYPE

• 10.1 INTRODUCTION
• 10.2 PERSONAL MOBILITY
  • 10.2.1 RISING DEMAND FOR ADAS-EQUIPPED PASSENGER CARS TO DRIVE MARKET
• 10.3 COMMERCIAL MOBILITY
  • 10.3.1 GROWING REGULATORY EMPHASIS ON APPROVALS FOR AUTONOMOUS VEHICLE TESTING TO DRIVE MARKET
• 10.4 KEY PRIMARY INSIGHTS

11 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY VEHICLE TYPE

• 11.1 INTRODUCTION
• 11.2 PASSENGER CAR
  • 11.2.1 POPULARITY OF CONNECTED-CAR ECOSYSTEMS EQUIPPED WITH REAL-TIME MAPPING TO DRIVE MARKET
• 11.3 COMMERCIAL VEHICLE
  • 11.3.1 AUTONOMOUS FLEET NAVIGATION AND PREDICTIVE ROUTING TO DRIVE MARKET
• 11.4 KEY PRIMARY INSIGHTS

12 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY REGION

• 12.1 INTRODUCTION
• 12.2 ASIA PACIFIC
  • 12.2.1 MACROECONOMIC OUTLOOK
  • 12.2.2 CHINA
    • 12.2.2.1 High production of vehicles and favourable investment norms to drive growth
  • 12.2.3 INDIA
    • 12.2.3.1 Increased focus on emission-friendly vehicles and vehicle safety regulations to drive market
  • 12.2.4 JAPAN
    • 12.2.4.1 Increased sales of mid-range cars to drive market
  • 12.2.5 SOUTH KOREA
    • 12.2.5.1 Rapid integration of HD maps into autonomous vehicle technologies to boost growth
• 12.3 EUROPE
  • 12.3.1 MACROECONOMIC OUTLOOK
  • 12.3.2 GERMANY
    • 12.3.2.1 Increased production of passenger cars to drive market
  • 12.3.3 FRANCE
    • 12.3.3.1 Need for improving road safety through advanced ADAS features to drive market
  • 12.3.4 ITALY
    • 12.3.4.1 Presence of major OEMs to drive advancements in HD map technology
  • 12.3.5 SPAIN
    • 12.3.5.1 Rise in government initiatives for advanced automotive systems to drive market
  • 12.3.6 UK
    • 12.3.6.1 Rising automotive output in country to spur demand for HD maps
• 12.4 NORTH AMERICA
  • 12.4.1 MACROECONOMIC OUTLOOK
  • 12.4.2 US
    • 12.4.2.1 Rising investments by OEMs in emerging megatrends to drive market
  • 12.4.3 CANADA
    • 12.4.3.1 Heightened awareness of consumers regarding vehicle safety to drive adoption of HD maps
• 12.5 REST OF THE WORLD (ROW)
  • 12.5.1 MACROECONOMIC OUTLOOK
  • 12.5.2 BRAZIL
    • 12.5.2.1 Collaboration between autonomous driving companies and other tech companies to boost growth
  • 12.5.3 SOUTH AFRICA
    • 12.5.3.1 Rapid growth of automotive sector and rising number of vehicle manufacturers to drive demand
  • 12.5.4 RUSSIA
    • 12.5.4.1 Changing market dynamics aligned with rising production of autonomous vehicles to drive growth
  • 12.5.5 SAUDI ARABIA
    • 12.5.5.1 Rising domestic demand for vehicles and support of government-backed initiatives to boost growth
  • 12.5.6 UAE
    • 12.5.6.1 Rapid investments in electric and autonomous vehicle infrastructure to boost growth

13 COMPETITIVE LANDSCAPE

• 13.1 OVERVIEW
• 13.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
• 13.3 MARKET SHARE ANALYSIS, 2024
• 13.4 REVENUE ANALYSIS OF TOP FIVE PLAYERS, 2020-2024
• 13.5 COMPANY VALUATION AND FINANCIAL METRICS
  • 13.5.1 COMPANY VALUATION
  • 13.5.2 FINANCIAL METRICS
• 13.6 BRAND/PRODUCT COMPARISON
• 13.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
  • 13.7.1 STARS
  • 13.7.2 EMERGING LEADERS
  • 13.7.3 PERVASIVE PLAYERS
  • 13.7.4 PARTICIPANTS
  • 13.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
    • 13.7.5.1 Company footprint
    • 13.7.5.2 Region footprint
    • 13.7.5.3 Usage type footprint
    • 13.7.5.4 Vehicle type footprint
    • 13.7.5.5 Level of automation footprint
• 13.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
  • 13.8.1 PROGRESSIVE COMPANIES
  • 13.8.2 RESPONSIVE COMPANIES
  • 13.8.3 DYNAMIC COMPANIES
  • 13.8.4 STARTING BLOCKS
  • 13.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
    • 13.8.5.1 Detailed list of startups/SMEs
    • 13.8.5.2 Competitive benchmarking of startups/SMEs
• 13.9 COMPETITIVE SCENARIO
  • 13.9.1 PRODUCT/SERVICE LAUNCHES/DEVELOPMENTS
  • 13.9.2 DEALS
  • 13.9.3 EXPANSION
  • 13.9.4 OTHER DEVELOPMENTS

14 COMPANY PROFILES

• 14.1 KEY PLAYERS
  • 14.1.1 HERE
    • 14.1.1.1 Business overview
    • 14.1.1.2 Products/Solutions/Services offered
    • 14.1.1.3 Recent developments
      • 14.1.1.3.1 Deals
      • 14.1.1.3.2 Other developments
    • 14.1.1.4 MnM view
      • 14.1.1.4.1 Key strengths
      • 14.1.1.4.2 Strategic choices
      • 14.1.1.4.3 Weaknesses and competitive threats
  • 14.1.2 BAIDU INC.
    • 14.1.2.1 Business overview
    • 14.1.2.2 Products/Solutions/Services offered
    • 14.1.2.3 Recent developments
      • 14.1.2.3.1 Deals
    • 14.1.2.4 MnM view
      • 14.1.2.4.1 Key strengths
      • 14.1.2.4.2 Strategic choices
      • 14.1.2.4.3 Weaknesses and competitive threats
  • 14.1.3 TOMTOM INTERNATIONAL BV
    • 14.1.3.1 Business overview
    • 14.1.3.2 Products/Solutions/Services offered
    • 14.1.3.3 Recent developments
      • 14.1.3.3.1 Product/Service launches/developments
      • 14.1.3.3.2 Deals
    • 14.1.3.4 MnM view
      • 14.1.3.4.1 Key strengths
      • 14.1.3.4.2 Strategic choices
      • 14.1.3.4.3 Weaknesses and competitive threats
  • 14.1.4 NVIDIA CORPORATION
    • 14.1.4.1 Business overview
    • 14.1.4.2 Products/Solutions/Services offered
    • 14.1.4.3 MnM view
      • 14.1.4.3.1 Key strengths
      • 14.1.4.3.2 Strategic choices
      • 14.1.4.3.3 Weaknesses and competitive threats
  • 14.1.5 MOBILEYE
    • 14.1.5.1 Business overview
    • 14.1.5.2 Products/Solutions/Services offered
    • 14.1.5.3 Recent developments
      • 14.1.5.3.1 Deals
      • 14.1.5.3.2 Other developments
    • 14.1.5.4 MnM view
      • 14.1.5.4.1 Key strengths
      • 14.1.5.4.2 Strategic choices
      • 14.1.5.4.3 Weaknesses and competitive threats
  • 14.1.6 WAYMO LLC
    • 14.1.6.1 Business overview
    • 14.1.6.2 Products/Solutions/Services offered
    • 14.1.6.3 Recent developments
      • 14.1.6.3.1 Deals
  • 14.1.7 DYNAMIC MAP PLATFORM CO., LTD.
    • 14.1.7.1 Business overview
    • 14.1.7.2 Products/Solutions/Services offered
    • 14.1.7.3 Recent developments
      • 14.1.7.3.1 Product/Service launches/developments
      • 14.1.7.3.2 Deals
      • 14.1.7.3.3 Expansion
      • 14.1.7.3.4 Other developments
  • 14.1.8 NAVINFO CO., LTD.
    • 14.1.8.1 Business overview
    • 14.1.8.2 Products/Solutions/Services offered
    • 14.1.8.3 Recent developments
      • 14.1.8.3.1 Deals
      • 14.1.8.3.2 Other developments
  • 14.1.9 LUMINAR TECHNOLOGIES, INC.
    • 14.1.9.1 Business overview
    • 14.1.9.2 Products/Solutions/Services offered
  • 14.1.10 THE SANBORN MAP COMPANY, INC.
    • 14.1.10.1 Business overview
    • 14.1.10.2 Products/Solutions/Services offered
  • 14.1.11 MOMENTA
    • 14.1.11.1 Business overview
    • 14.1.11.2 Products/Solutions/Services offered
  • 14.1.12 MAPBOX
    • 14.1.12.1 Business overview
    • 14.1.12.2 Products/Solutions/Services offered
    • 14.1.12.3 Recent developments
      • 14.1.12.3.1 Product/Service launches/developments
      • 14.1.12.3.2 Deals
• 14.2 OTHER PLAYERS
  • 14.2.1 CE INFO SYSTEMS LTD.
  • 14.2.2 NAVMII
  • 14.2.3 RMSI
  • 14.2.4 ZENRIN CO., LTD.
  • 14.2.5 WOVEN BY TOYOTA, INC.
  • 14.2.6 SWIFT NAVIGATION, INC.
  • 14.2.7 IMERIT
  • 14.2.8 VOXELMAPS
  • 14.2.9 HYUNDAI AUTOEVER CORP.
  • 14.2.10 GENESYS INTERNATIONAL CORPORATION LTD
  • 14.2.11 GEOMATE
  • 14.2.12 INTELLIAS
  • 14.2.13 MORAI INC.

15 APPENDIX

• 15.1 DISCUSSION GUIDE
• 15.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 15.3 CUSTOMIZATION OPTIONS
  • 15.3.1 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY VEHICLE TYPE, AT COUNTRY LEVEL
  • 15.3.2 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY SOLUTION TYPE, AT COUNTRY LEVEL
  • 15.3.3 HD MAPS FOR AUTONOMOUS DRIVING MARKET, BY SERVICE TYPE, AT COUNTRY LEVEL
  • 15.3.4 COMPANY INFORMATION
    • 15.3.4.1 Profiling of additional market players (up to five)
• 15.4 RELATED REPORTS
• 15.5 AUTHOR DETAILS