Global Computing Platform for Automated Driving Market Analysis and Forecast 2024-2030

Global Computing Platform for Automated Driving Market Analysis and Forecast 2024-2030


Summary

According to APO Research, The global Computing Platform for Automated Driving market is projected to grow from US$ million in 2024 to US$ million by 2030, at a Compound Annual Growth Rate (CAGR) of % during the forecast period.

The US & Canada market for Computing Platform for Automated Driving is estimated to increase from $ million in 2024 to reach $ million by 2030, at a CAGR of % during the forecast period of 2025 through 2030.

Asia-Pacific market for Computing Platform for Automated Driving is estimated to increase from $ million in 2024 to reach $ million by 2030, at a CAGR of % during the forecast period of 2025 through 2030.

The China market for Computing Platform for Automated Driving is estimated to increase from $ million in 2024 to reach $ million by 2030, at a CAGR of % during the forecast period of 2025 through 2030.

Europe market for Computing Platform for Automated Driving is estimated to increase from $ million in 2024 to reach $ million by 2030, at a CAGR of % during the forecast period of 2025 through 2030.

The major global companies of Computing Platform for Automated Driving include Baidu, Tesla, NVIDIA, Bosch, Continental, Huawei, Qualcomm and Horizon, etc. In 2023, the world's top three vendors accounted for approximately % of the revenue.

Report Includes

This report presents an overview of global market for Computing Platform for Automated Driving, market size. Analyses of the global market trends, with historic market revenue data for 2019 - 2023, estimates for 2024, and projections of CAGR through 2030.

This report researches the key producers of Computing Platform for Automated Driving, also provides the revenue of main regions and countries. Of the upcoming market potential for Computing Platform for Automated Driving, and key regions or countries of focus to forecast this market into various segments and sub-segments. Country specific data and market value analysis for the U.S., Canada, Mexico, Brazil, China, Japan, South Korea, Southeast Asia, India, Germany, the U.K., Italy, Middle East, Africa, and Other Countries.

This report focuses on the Computing Platform for Automated Driving revenue, market share and industry ranking of main manufacturers, data from 2019 to 2024. Identification of the major stakeholders in the global Computing Platform for Automated Driving market, and analysis of their competitive landscape and market positioning based on recent developments and segmental revenues. This report will help stakeholders to understand the competitive landscape and gain more insights and position their businesses and market strategies in a better way.

This report analyzes the segments data by Type and by Application, revenue, and growth rate, from 2019 to 2030. Evaluation and forecast the market size for Computing Platform for Automated Driving revenue, projected growth trends, production technology, application and end-user industry.

Computing Platform for Automated Driving segment by Company

Baidu
Tesla
NVIDIA
Bosch
Continental
Huawei
Qualcomm
Horizon

Computing Platform for Automated Driving segment by Type

Software
Hardware

Computing Platform for Automated Driving segment by Application

L1/L2 Automatic Driving
L3 Automatic Driving
Other

Computing Platform for Automated Driving segment by Region

North America
United States
Canada
Europe
Germany
France
U.K.
Italy
Netherlands
Asia-Pacific
China
Japan
South Korea
India
Australia
China Taiwan
Southeast Asia
Latin America
Mexico
Brazil
Argentina
Middle East & Africa
Turkey
Saudi Arabia
UAE

Study Objectives

1. To analyze and research the global status and future forecast, involving growth rate (CAGR), market share, historical and forecast.
2. To present the key players, revenue, market share, and Recent Developments.
3. To split the breakdown data by regions, type, manufacturers, and Application.
4. To analyze the global and key regions market potential and advantage, opportunity and challenge, restraints, and risks.
5. To identify significant trends, drivers, influence factors in global and regions.
6. To analyze competitive developments such as expansions, agreements, new product launches, and acquisitions in the market.

Reasons to Buy This Report

1. This report will help the readers to understand the competition within the industries and strategies for the competitive environment to enhance the potential profit. The report also focuses on the competitive landscape of the global Computing Platform for Automated Driving market, and introduces in detail the market share, industry ranking, competitor ecosystem, market performance, new product development, operation situation, expansion, and acquisition. etc. of the main players, which helps the readers to identify the main competitors and deeply understand the competition pattern of the market.
2. This report will help stakeholders to understand the global industry status and trends of Computing Platform for Automated Driving and provides them with information on key market drivers, restraints, challenges, and opportunities.
3. This report will help stakeholders to understand competitors better and gain more insights to strengthen their position in their businesses. The competitive landscape section includes the market share and rank (in market size), competitor ecosystem, new product development, expansion, and acquisition.
4. This report stays updated with novel technology integration, features, and the latest developments in the market.
5. This report helps stakeholders to gain insights into which regions to target globally.
6. This report helps stakeholders to gain insights into the end-user perception concerning the adoption of Computing Platform for Automated Driving.
7. This report helps stakeholders to identify some of the key players in the market and understand their valuable contribution.

Chapter Outline

Chapter 1: Introduces the report scope of the report, executive summary of different market segments (product type, application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Revenue of Computing Platform for Automated Driving in global and regional level. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 4: Detailed analysis of Computing Platform for Automated Driving company competitive landscape, revenue, market share and industry ranking, latest development plan, merger, and acquisition information, etc.
Chapter 5: Provides the analysis of various market segments by type, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 6: Provides the analysis of various market segments by application, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 7: Provides profiles of key companies, introducing the basic situation of the main companies in the market in detail, including product descriptions and specifications, Computing Platform for Automated Driving revenue, gross margin, and recent development, etc.
Chapter 8: North America (US & Canada) by type, by application and by country, revenue for each segment.
Chapter 9: Europe by type, by application and by country, revenue for each segment.
Chapter 10: China type, by application, revenue for each segment.
Chapter 11: Asia (excluding China) type, by application and by region, revenue for each segment.
Chapter 12: Middle East, Africa, and Latin America type, by application and by country, revenue for each segment.
Chapter 13: The main concluding insights of the report.


1 Market Overview
1.1 Product Definition
1.2 Computing Platform for Automated Driving Market by Type
1.2.1 Global Computing Platform for Automated Driving Market Size by Type, 2019 VS 2023 VS 2030
1.2.2 Software
1.2.3 Hardware
1.3 Computing Platform for Automated Driving Market by Application
1.3.1 Global Computing Platform for Automated Driving Market Size by Application, 2019 VS 2023 VS 2030
1.3.2 L1/L2 Automatic Driving
1.3.3 L3 Automatic Driving
1.3.4 Other
1.4 Assumptions and Limitations
1.5 Study Goals and Objectives
2 Computing Platform for Automated Driving Market Dynamics
2.1 Computing Platform for Automated Driving Industry Trends
2.2 Computing Platform for Automated Driving Industry Drivers
2.3 Computing Platform for Automated Driving Industry Opportunities and Challenges
2.4 Computing Platform for Automated Driving Industry Restraints
3 Global Growth Perspective
3.1 Global Computing Platform for Automated Driving Market Perspective (2019-2030)
3.2 Global Computing Platform for Automated Driving Growth Trends by Region
3.2.1 Global Computing Platform for Automated Driving Market Size by Region: 2019 VS 2023 VS 2030
3.2.2 Global Computing Platform for Automated Driving Market Size by Region (2019-2024)
3.2.3 Global Computing Platform for Automated Driving Market Size by Region (2025-2030)
4 Competitive Landscape by Players
4.1 Global Computing Platform for Automated Driving Revenue by Players
4.1.1 Global Computing Platform for Automated Driving Revenue by Players (2019-2024)
4.1.2 Global Computing Platform for Automated Driving Revenue Market Share by Players (2019-2024)
4.1.3 Global Computing Platform for Automated Driving Players Revenue Share Top 10 and Top 5 in 2023
4.2 Global Computing Platform for Automated Driving Key Players Ranking, 2022 VS 2023 VS 2024
4.3 Global Computing Platform for Automated Driving Key Players Headquarters & Area Served
4.4 Global Computing Platform for Automated Driving Players, Product Type & Application
4.5 Global Computing Platform for Automated Driving Players Commercialization Time
4.6 Market Competitive Analysis
4.6.1 Global Computing Platform for Automated Driving Market CR5 and HHI
4.6.2 Global Top 5 and 10 Computing Platform for Automated Driving Players Market Share by Revenue in 2023
4.6.3 2023 Computing Platform for Automated Driving Tier 1, Tier 2, and Tier 3
5 Computing Platform for Automated Driving Market Size by Type
5.1 Global Computing Platform for Automated Driving Revenue by Type (2019 VS 2023 VS 2030)
5.2 Global Computing Platform for Automated Driving Revenue by Type (2019-2030)
5.3 Global Computing Platform for Automated Driving Revenue Market Share by Type (2019-2030)
6 Computing Platform for Automated Driving Market Size by Application
6.1 Global Computing Platform for Automated Driving Revenue by Application (2019 VS 2023 VS 2030)
6.2 Global Computing Platform for Automated Driving Revenue by Application (2019-2030)
6.3 Global Computing Platform for Automated Driving Revenue Market Share by Application (2019-2030)
7 Company Profiles
7.1 Baidu
7.1.1 Baidu Comapny Information
7.1.2 Baidu Business Overview
7.1.3 Baidu Computing Platform for Automated Driving Revenue and Gross Margin (2019-2024)
7.1.4 Baidu Computing Platform for Automated Driving Product Portfolio
7.1.5 Baidu Recent Developments
7.2 Tesla
7.2.1 Tesla Comapny Information
7.2.2 Tesla Business Overview
7.2.3 Tesla Computing Platform for Automated Driving Revenue and Gross Margin (2019-2024)
7.2.4 Tesla Computing Platform for Automated Driving Product Portfolio
7.2.5 Tesla Recent Developments
7.3 NVIDIA
7.3.1 NVIDIA Comapny Information
7.3.2 NVIDIA Business Overview
7.3.3 NVIDIA Computing Platform for Automated Driving Revenue and Gross Margin (2019-2024)
7.3.4 NVIDIA Computing Platform for Automated Driving Product Portfolio
7.3.5 NVIDIA Recent Developments
7.4 Bosch
7.4.1 Bosch Comapny Information
7.4.2 Bosch Business Overview
7.4.3 Bosch Computing Platform for Automated Driving Revenue and Gross Margin (2019-2024)
7.4.4 Bosch Computing Platform for Automated Driving Product Portfolio
7.4.5 Bosch Recent Developments
7.5 Continental
7.5.1 Continental Comapny Information
7.5.2 Continental Business Overview
7.5.3 Continental Computing Platform for Automated Driving Revenue and Gross Margin (2019-2024)
7.5.4 Continental Computing Platform for Automated Driving Product Portfolio
7.5.5 Continental Recent Developments
7.6 Huawei
7.6.1 Huawei Comapny Information
7.6.2 Huawei Business Overview
7.6.3 Huawei Computing Platform for Automated Driving Revenue and Gross Margin (2019-2024)
7.6.4 Huawei Computing Platform for Automated Driving Product Portfolio
7.6.5 Huawei Recent Developments
7.7 Qualcomm
7.7.1 Qualcomm Comapny Information
7.7.2 Qualcomm Business Overview
7.7.3 Qualcomm Computing Platform for Automated Driving Revenue and Gross Margin (2019-2024)
7.7.4 Qualcomm Computing Platform for Automated Driving Product Portfolio
7.7.5 Qualcomm Recent Developments
7.8 Horizon
7.8.1 Horizon Comapny Information
7.8.2 Horizon Business Overview
7.8.3 Horizon Computing Platform for Automated Driving Revenue and Gross Margin (2019-2024)
7.8.4 Horizon Computing Platform for Automated Driving Product Portfolio
7.8.5 Horizon Recent Developments
8 North America
8.1 North America Computing Platform for Automated Driving Revenue (2019-2030)
8.2 North America Computing Platform for Automated Driving Revenue by Type (2019-2030)
8.2.1 North America Computing Platform for Automated Driving Revenue by Type (2019-2024)
8.2.2 North America Computing Platform for Automated Driving Revenue by Type (2025-2030)
8.3 North America Computing Platform for Automated Driving Revenue Share by Type (2019-2030)
8.4 North America Computing Platform for Automated Driving Revenue by Application (2019-2030)
8.4.1 North America Computing Platform for Automated Driving Revenue by Application (2019-2024)
8.4.2 North America Computing Platform for Automated Driving Revenue by Application (2025-2030)
8.5 North America Computing Platform for Automated Driving Revenue Share by Application (2019-2030)
8.6 North America Computing Platform for Automated Driving Revenue by Country
8.6.1 North America Computing Platform for Automated Driving Revenue by Country (2019 VS 2023 VS 2030)
8.6.2 North America Computing Platform for Automated Driving Revenue by Country (2019-2024)
8.6.3 North America Computing Platform for Automated Driving Revenue by Country (2025-2030)
8.6.4 United States
8.6.5 Canada
9 Europe
9.1 Europe Computing Platform for Automated Driving Revenue (2019-2030)
9.2 Europe Computing Platform for Automated Driving Revenue by Type (2019-2030)
9.2.1 Europe Computing Platform for Automated Driving Revenue by Type (2019-2024)
9.2.2 Europe Computing Platform for Automated Driving Revenue by Type (2025-2030)
9.3 Europe Computing Platform for Automated Driving Revenue Share by Type (2019-2030)
9.4 Europe Computing Platform for Automated Driving Revenue by Application (2019-2030)
9.4.1 Europe Computing Platform for Automated Driving Revenue by Application (2019-2024)
9.4.2 Europe Computing Platform for Automated Driving Revenue by Application (2025-2030)
9.5 Europe Computing Platform for Automated Driving Revenue Share by Application (2019-2030)
9.6 Europe Computing Platform for Automated Driving Revenue by Country
9.6.1 Europe Computing Platform for Automated Driving Revenue by Country (2019 VS 2023 VS 2030)
9.6.2 Europe Computing Platform for Automated Driving Revenue by Country (2019-2024)
9.6.3 Europe Computing Platform for Automated Driving Revenue by Country (2025-2030)
9.6.4 Germany
9.6.5 France
9.6.6 U.K.
9.6.7 Italy
9.6.8 Netherlands
10 China
10.1 China Computing Platform for Automated Driving Revenue (2019-2030)
10.2 China Computing Platform for Automated Driving Revenue by Type (2019-2030)
10.2.1 China Computing Platform for Automated Driving Revenue by Type (2019-2024)
10.2.2 China Computing Platform for Automated Driving Revenue by Type (2025-2030)
10.3 China Computing Platform for Automated Driving Revenue Share by Type (2019-2030)
10.4 China Computing Platform for Automated Driving Revenue by Application (2019-2030)
10.4.1 China Computing Platform for Automated Driving Revenue by Application (2019-2024)
10.4.2 China Computing Platform for Automated Driving Revenue by Application (2025-2030)
10.5 China Computing Platform for Automated Driving Revenue Share by Application (2019-2030)
11 Asia (Excluding China)
11.1 Asia Computing Platform for Automated Driving Revenue (2019-2030)
11.2 Asia Computing Platform for Automated Driving Revenue by Type (2019-2030)
11.2.1 Asia Computing Platform for Automated Driving Revenue by Type (2019-2024)
11.2.2 Asia Computing Platform for Automated Driving Revenue by Type (2025-2030)
11.3 Asia Computing Platform for Automated Driving Revenue Share by Type (2019-2030)
11.4 Asia Computing Platform for Automated Driving Revenue by Application (2019-2030)
11.4.1 Asia Computing Platform for Automated Driving Revenue by Application (2019-2024)
11.4.2 Asia Computing Platform for Automated Driving Revenue by Application (2025-2030)
11.5 Asia Computing Platform for Automated Driving Revenue Share by Application (2019-2030)
11.6 Asia Computing Platform for Automated Driving Revenue by Country
11.6.1 Asia Computing Platform for Automated Driving Revenue by Country (2019 VS 2023 VS 2030)
11.6.2 Asia Computing Platform for Automated Driving Revenue by Country (2019-2024)
11.6.3 Asia Computing Platform for Automated Driving Revenue by Country (2025-2030)
11.6.4 Japan
11.6.5 South Korea
11.6.6 India
11.6.7 Australia
11.6.8 China Taiwan
11.6.9 Southeast Asia
12 Middle East, Africa, Latin America
12.1 MEALA Computing Platform for Automated Driving Revenue (2019-2030)
12.2 MEALA Computing Platform for Automated Driving Revenue by Type (2019-2030)
12.2.1 MEALA Computing Platform for Automated Driving Revenue by Type (2019-2024)
12.2.2 MEALA Computing Platform for Automated Driving Revenue by Type (2025-2030)
12.3 MEALA Computing Platform for Automated Driving Revenue Share by Type (2019-2030)
12.4 MEALA Computing Platform for Automated Driving Revenue by Application (2019-2030)
12.4.1 MEALA Computing Platform for Automated Driving Revenue by Application (2019-2024)
12.4.2 MEALA Computing Platform for Automated Driving Revenue by Application (2025-2030)
12.5 MEALA Computing Platform for Automated Driving Revenue Share by Application (2019-2030)
12.6 MEALA Computing Platform for Automated Driving Revenue by Country
12.6.1 MEALA Computing Platform for Automated Driving Revenue by Country (2019 VS 2023 VS 2030)
12.6.2 MEALA Computing Platform for Automated Driving Revenue by Country (2019-2024)
12.6.3 MEALA Computing Platform for Automated Driving Revenue by Country (2025-2030)
12.6.4 Mexico
12.6.5 Brazil
12.6.6 Israel
12.6.7 Argentina
12.6.8 Colombia
12.6.9 Turkey
12.6.10 Saudi Arabia
12.6.11 UAE
13 Concluding Insights
14 Appendix
14.1 Reasons for Doing This Study
14.2 Research Methodology
14.3 Research Process
14.4 Authors List of This Report
14.5 Data Source
14.5.1 Secondary Sources
14.5.2 Primary Sources
14.6 Disclaimer

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