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HD Map for Autonomous Vehicles Market Research Report – Segmented By Services (Localization, Advertisement, Mapping, Update & Maintenance); By Level Of Automation (Semi-Autonomous (Level 2&3), Autonomous (Level 4&5)); By Solution (Embedded, Cloud-based); By Vehicle Type (Commercial Vehicles, Passenger Vehicles); and Region - Size, Share, Growth Analysis | Forecast (2023 – 2030)

HD Map for Autonomous Vehicles Market Size (2023 – 2030)

In 2023, the Global HD Map for Autonomous Vehicles Market was valued at $1.84 billion, and is projected to reach a market size of $12.85 billion by 2030. Over the forecast period of 2024-2030, market is projected to grow at a CAGR of 32%.

HD MAP FOR AUTONOMOUS

INDUSTRY OVERVIEW

Demand for autonomous cars is now being driven by a growing desire to boost mobility and minimize traffic accidents, and this trend is projected to continue in the future. Advances in next-generation high-accuracy and lifelike digital maps are assisting in the evolution of HD maps. The goal in developed and developing countries is to have safer, cleaner, and less crowded roads, which is leading to a greater focus on autonomous cars and innovative means of transportation.

HD maps, also known as high-definition maps, are utilized for self-driving assistance with exceptionally high precision of centimeter scale and may be described as the autonomous cars' eyes. To help autonomous cars drive safely, the HD map is a semantic layer that detects lane borders, road signals, crosswalks, traffic lights, and other objects. Autonomous cars' high-definition onboard maps give exact location data on adjacent infrastructure, routes, and habitats. Furthermore, these maps were created specifically for self-driving cars and include extraordinarily high resolution and centimeter-level precision. It also offers virtual support and is simple to update regularly. Furthermore, the map offers information to the vehicle such as height, curvature, lane slope, road geometry, and traffic, assisting the vehicle in planning a course along its trip. The map captures real-time data from its surroundings to avoid any unexpected events. In addition, the HD map will aid in boosting reaction time in the face of any blockage or tough scenario, enhancing safety in the event of sensor failure. As a result, the widespread use of HD maps in autonomous cars is likely to propel the market for HD maps for autonomous vehicles.

The growing trend of driverless vehicles, which incorporates next-generation high-definition maps into new automobiles, is fueling the expansion of the HD maps industry. HD maps are required for autonomous driving to be precise, secure, seamless, and efficient. The need for HD map software among autonomous car producers is growing as a result of this reason. Manufacturers of autonomous cars are working to increase their vehicles' awareness and enable them to recognise their specific position. HD map technology was created to allow for the detection of location on the road, surroundings, kind of road divider, position, and breadth. These are more advanced functions than GPS and GPRS technology and applications typically give. Major market companies are utilising powerful Artificial Intelligence algorithms to accelerate the manufacturing of HD map software and services for deployment in self-driving cars, which is boosting the market for HD maps for autonomous vehicles. The expensive expense of HD maps and software, on the other hand, is projected to limit demand for implementation in autonomous cars. Furthermore, privacy and regulatory concerns about HD maps are likely to limit the market for HD maps for autonomous cars to some extent.

COVID-19 IMPACT ON HD MAP FOR AUTONOMOUS VEHICLES MARKET

Manufacturing has been suspended, sales have plummeted, and major corporations in the worldwide car industry have had to adapt or change their strategies as a result of the COVID-19 outbreak. The production and sales of passenger and commercial cars throughout the world have been influenced by postponing model and project launches, stabilising dealer networks, handling cash outflow, and assessing investment portfolios. Autonomous vehicle development, testing, and deployment, as well as the expansion of the HD map space, are projected to decelerate. Most nations implemented total lockdowns for more than two months as a result of the COVID-19 epidemic, which had an impact on vehicle manufacturing. Vehicle sales were drastically impacted as manufacturing plants throughout the world were shut down.

MARKET DRIVERS: 

The growing trend of autonomous driving is likely to fuel the growth of the HD maps for the autonomous vehicles market

Autonomous vehicles are becoming increasingly popular across the world. The study and development of autonomous driving technology are a priority for major participants in the autonomous driving sector. Leading automakers including Ford, Volkswagen, Mercedes-Benz, Toyota, Audi, General Motors, Honda, and Tesla have already announced projects to create self-driving cars. The expansion of autonomous cars is being driven by major benefits such as enhanced efficiency, elimination of human mistakes in driving, environmentally friendly operation, and so on. With the growing population of cities, transportation congestion has become a serious issue. When compared to human-driven cars, autonomous vehicles can maintain shorter minimum distances between two vehicles, resulting in improved traffic flow, fewer emissions, and reduced congestion. The expansion of the autonomous vehicle market is strongly related to the demand for HD maps. The usage of HD maps in autonomous vehicles will provide accurate navigation and safe travel, which would eventually generate demand for HD maps.

The rollout of 5g technology is acting as a major proponent to the market growth

The 5G network provides new application opportunities for the development of autonomous automobiles by providing quicker connections across transportation systems. For navigation, this vehicle requires regular data updates, including precise route maps, traffic congestion statistics, and real-time weather updates like rain or black ice. Such challenges are addressed by 5G and associated modern technology. Furthermore, the 5G Automotive Association (5GAA) claims that in the future, this technology will provide even better quality for numerous digital in-car services. As a result, all of these considerations will accelerate the adoption of HD mapping for autonomous cars shortly.

MARKET RESTRAINTS:

The lack of a single standardization in HD maps is restraining the market growth

The growth of HD maps technology is dependent on the standardisation of HD maps. There is no one reliable source or database of HD mapping data at the moment. The amount of map data is continually growing as a result of technological advancements. The standardisation and preservation of this information have become critical issues. Despite existing standards like ADASIS, NDS, SENSORIS, and TISA, the database lacks compatibility among mapping vendors. One of the major roadblocks to self-driving vehicle commercial readiness and safety is the lack of a unified automotive-grade navigation platform.

High Costs linked with Technology Building, Data Processing, and Use of Components May Restrain Growth

HD map creation is a difficult process that entails several steps, including data collection, map creation, and integration of advanced tool/technology ecosystems such as AI, Machine Learning, and others. These features allow for real-time road data. Higher production costs result from the total expense of manual verification and the demand for new map sources. Furthermore, due to the enormous complexity of roads and environmental circumstances, producing error-free maps is difficult. Furthermore, creating automation maps with manual verification based on local knowledge has become a time-consuming effort. The majority of newcomers sell commercial maps based on satellite imaginary and car sensor information, which are insufficient for creating very accurate HD maps. Furthermore, these maps rely on information gathered from the many components employed, such as cameras, sensors, GPS devices, high-speed networks, Lidar, and so on. The adoption of such higher-priced components ensures that the system cost is high. As a result, the market's expansion is hampered by high costs and a lack of uniformity.

HD MAP FOR AUTONOMOUS VEHICLES MARKET REPORT COVERAGE:

REPORT METRIC

DETAILS

Market Size Available

2022 - 2030

Base Year

2022

Forecast Period

2023 - 2030

CAGR

26.5%

Segments Covered

By Services, Level of Automation, Solution,  Vehicle Type, and Region

Various Analyses Covered

Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities

Regional Scope

North America, Europe, APAC, Latin America, Middle East & Africa

Key Companies Profiled

NVIDIA, Tomtom, DeepMap, Here Technologies, Navinfo, Civil Maps, Mapmyindia, Sanborn Map Company, Navmii, Autonavi

This research report on the HD Map for Autonomous Vehicles Market has been segmented and sub-segmented based on By Services, By Level of Automation, By Solution, By Vehicle Type and By Region.

HD MAP FOR AUTONOMOUS VEHICLES MARKET - BY SERVICES

  • Localization

  • Advertisement

  • Mapping

  • Update & Maintenance

Based on services, the HD map for the autonomous vehicles market is segmented into Localization, Advertisement, Mapping and Update & Maintenance. In 2021, the localization sector of the HD maps for autonomous cars market had the highest revenue share. During the projection period, the revenue growth rate for the localization segment is anticipated to grow at a significant rate. New HD maps provide high-precision optical positioning, which is leading to its increased adoption in autonomous cars. HD maps boost sensor reception and localisation to centimetre-level precision, which improves safety and leads to better course planning by autonomous driving systems. These are some of the technical aspects that are driving the growing demand for high-resolution maps for autonomous vehicles. HD maps allow a vehicle to place itself on the road precisely and properly, assisting in the resolution of the localization problem. The driver's safety and comfort are considerably improved by automation, and the high efficiency of HD map solutions gives the driver even more assurance in the vehicle's ability to safely navigate highways in a variety of circumstances and conditions.

HD MAP FOR AUTONOMOUS VEHICLES MARKET – BY LEVEL OF AUTOMATION

  • Semi-Autonomous (Level 2&3)

  • Autonomous (Level 4&5)

Based on the level of automation, the HD map for the autonomous vehicles market is segmented into Semi-Autonomous (Level 2&3) and Autonomous (Level 4&5), Among these, the Semi-Autonomous (Level 2&3) accounted for the maximum market share of over 60% in 2021. During the projection period, revenue growth in the semi-autonomous (Level 2&3) category is expected to grow significantly. Demand for increasingly advanced and creative technology in vehicle design and functionality is driving demand for semi-autonomous cars, which is fueling the market for HD maps for autonomous vehicles. Rigorous rules governing autonomous cars have boosted demand for semi-autonomous vehicles, boosting market growth, and this trend is projected to continue during the forecast period. Consumer scepticism about autonomous vehicles' overall safety is a major reason hampering their demand. Another significant aspect projected to contribute to increased demand for semi-autonomous cars and the use of HD maps and solutions in such vehicles is the desire to reduce traffic congestion.

HD MAP FOR AUTONOMOUS VEHICLES MARKET – BY SOLUTION

  • Embedded

  • Cloud-based  

Based on the solution, the HD map for the autonomous vehicles market is segmented into Embedded and Cloud-based. Among these, the Cloud-based segment dominated the market in 2021. The segment is anticipated to expand at a healthy CAGR of 35% over the forecast period. The use of cloud-based technologies is being driven by the need for an effective cloud infrastructure to handle raw sensor data produced by self-driving cars. The raw data saved on cloud platforms may be used to conduct distributed stimulation testing for a new method or technique deployment, offline deep learning model training, and the creation and updating of HD maps. Cloud-based services are rapidly being used by major participants in the sector, such as TomTom, NVIDIA, and HERE Technologies since they provide greater accuracy and ease of map updating. Another element driving revenue growth in the cloud-based category is the cost-effectiveness of cloud-based services when compared to embedded systems.

HD MAP FOR AUTONOMOUS VEHICLES MARKET - BY VEHICLE TYPE

  • Commercial Vehicles

  • Passenger Vehicles

Based on the vehicle type, the HD map for the autonomous vehicles market is segmented into Commercial Vehicles and Passenger Vehicles. The passenger vehicle segment dominated the market in 2021, capturing over 75% of the global market share. During the projection period, the revenue growth rate for passenger cars is expected to accelerate significantly. A factor driving stronger demand for autonomous passenger vehicles is the existence of more rigorous restrictions for autonomous commercial vehicles compared to passenger vehicles. Increasing demand for autonomous passenger vehicles is being driven by rising automobile sales and growing consumer preferences for more sophisticated technology.

HD MAP FOR AUTONOMOUS VEHICLES MARKET - BY REGION

  • North America

  • Europe

  • The Asia Pacific

  • Latin America

  • The Middle East and Africa

Based on region, the HD map for the autonomous vehicles market is grouped into North America, Europe, Asia Pacific, Latin America, The Middle East, and Africa. In 2020, North America contributed the most revenue to the global HD maps for autonomous cars market. During the forecast period, revenue from the HD maps for autonomous cars market in North America is predicted to grow at a quick pace. The rising emphasis in developed economies on making roads safer, cleaner, and less crowded is a significant element driving demand for autonomous cars, which is directly contributing to the growth of the HD maps for the autonomous vehicles market. Consumers in the area have more discretionary income, which is leading to an increase in the use of high-end safety automobiles in North America. Manufacturers of autonomous cars in the region are focused on implementing extremely precise and realistic digital map software in their vehicles, which is boosting demand for HD maps for autonomous vehicles. During the projected period, Asia Pacific is predicted to generate revenue at a much quicker rate than other regional markets. Companies with a strong presence in the region, including Baidu, Xiaoma Zhixing, Auto X, and Didi Chuxing, are pushing the advancement of autonomous driving technology. Due to the novelty of this type of technology, a growing number of customers in several countries in the area are supporting the expansion of HD maps for autonomous vehicles to some level. Furthermore, the rising use of AI and 5G in the automotive industry is pushing the manufacture of autonomous cars and the use of HD maps and software.

HD MAP FOR AUTONOMOUS VEHICLES MARKET - BY COMPANIES

The global market for high-definition maps for autonomous cars is mostly fragmented, with a significant number of small and medium-sized companies responsible for the majority of revenue. Organizations in the HD maps for autonomous cars market have well-equipped production facilities and engage in various research and development activities and efforts to create and deliver new and more efficient technologies. Some of the prominent players operating in the HD map for the autonomous vehicles market are:

  1. NVIDIA

  2. Tomtom

  3. DeepMap

  4. Here Technologies

  5. Navinfo

  6. Civil Maps

  7. Mapmyindia

  8. Sanborn Map Company

  9. Navmii

  10. Autonavi

NOTABLE HAPPENING IN HD MAP FOR AUTONOMOUS VEHICLES MARKET

  • COLLABORATION- HERE and INCREMENT P established their partnership in May 2021, intending to expand access to high-quality location information and data sets.

  • COLLABORATION- Dynamic Map Platform and Valeo announced a collaboration in February 2021 to create technology and commercial structures for accurate localization and map updates to aid the growth of autonomous driving systems. Both companies have agreed to hold conversations and conduct technical and business research on high-precision localization and map update technologies required for ADAS and autonomous driving quality, with the goal of cooperatively delivering services on a worldwide scale and on a non-exclusive basis.

  • PRODUCT LAUNCH- In September 2020, TomTom announced the release of new technology named RoadCheck, for autonomous cars that will help them better handle traffic and weather. In bad weather and regions with inadequate signals, such as tunnels, the new RoadCheck solution directly tackles customer and partner pain points to enable safer autonomous driving experiences.

  • COLLABORATION- GeoJunxion formed a strategic agreement with NavInfo Europe in December 2020 to provide AI solutions to our clients.

Chapter 1. AI in Genomics Market – Scope & Methodology

1.1. Market Segmentation

1.2. Assumptions

1.3. Research Methodology

1.4. Primary Sources

1.5. Secondary Sources

Chapter 2. AI in Genomics Market – Executive Summary

2.1. Market Size & Forecast – (2023 – 2030) ($M/$Bn)

2.2. Key Trends & Insights

2.3. COVID-19 Impact Analysis

       2.3.1. Impact during 2023 - 2030

       2.3.2. Impact on Supply – Demand

Chapter 3. AI in Genomics Market – Competition Scenario

3.1. Market Share Analysis

3.2. Product Benchmarking

3.3. Competitive Strategy & Development Scenario

3.4. Competitive Pricing Analysis

3.5. Supplier - Distributor Analysis

Chapter 4. AI in Genomics Market Entry Scenario

4.1. Case Studies – Start-up/Thriving Companies

4.2. Regulatory Scenario - By Region

4.3 Customer Analysis

4.4. Porter's Five Force Model

       4.4.1. Bargaining Power of Suppliers

       4.4.2. Bargaining Powers of Customers

       4.4.3. Threat of New Entrants

       4.4.4. Rivalry among Existing Players

       4.4.5. Threat of Substitutes

Chapter 5. AI in Genomics Market - Landscape

5.1. Value Chain Analysis – Key Stakeholders Impact Analysis

5.2. Market Drivers

5.3. Market Restraints/Challenges

5.4. Market Opportunities

Chapter 6. AI in Genomics Market – By Services

6.1. Localization

6.2. Advertisement

6.3. Mapping

6.4. Update & Maintenance

Chapter 7. AI in Genomics Market – By Level of Automation

7.1. Semi-Autonomous (Level 2&3)

7.2. Autonomous (Level 4&5)

Chapter 8. AI in Genomics Market – By Solution

8.1. Embedded

8.2. Cloud-based  

Chapter 9. AI in Genomics Market – By Vehicle type

9.1. Commercial Vehicles

9.2. Passenger Vehicles

Chapter10. AI in Genomics Market- By Region

10.1. North America

10.2. Europe

10.3. Asia-Pacific

10.4. Latin America

10.5. The Middle East

10.6. Africa

Chapter 11. AI in Genomics Market – key players

 

11.1 NVIDIA

11.2 Tomtom

11.3 DeepMap

11.4 Here Technologies

11.5 Navinfo

11.6 Civil Maps

11.7 Mapmyindia

11.8 Sanborn Map Company

11.9 Navmii

11.10 Autonavi

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