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Global Autonomous Cars Market to reach USD 37.36 billion by the end of 2030.

Global Autonomous Cars Market Size study & Forecast, by Type (Fully Autonomous, Semi-Autonomous), by Vehicle Type (Passenger Cars, Commercial Vehicles), and Regional Analysis, 2023-2030

Product Code: ALTPCV-49802843
Publish Date: 27-06-2023
Page: 200

Global Autonomous Cars Market is valued at approximately USD 2.14 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 42.97% over the forecast period 2023-2030. Autonomous cars, also known as self-driving cars or driverless cars, are vehicles capable of operating without human intervention or assistance. These cars use a combination of advanced sensors, artificial intelligence (AI), and complex algorithms to perceive their environment, make decisions, and navigate safely. The goal of autonomous cars is to enhance road safety, improve traffic efficiency, and provide greater convenience for passengers. The Autonomous Cars Market is expanding because of factors such as rising increasing adoption of advanced driver assistance systems (ADAS) and increasing demand for automated Energy-efficient Vehicles.

The automotive industry has been driving research and development in recent years to enhance ADAS systems. As a result, lane departure warning systems, cameras, RADAR, and other sensors are in high demand and are being integrated into vehicles at a rapid rate. Companies, therefore, keep focusing on developing products utilizing these technologies to increase demand in the industry which is driving the market growth. As an example, in the year 2020, Hyundai unveiled its upgraded Santafee model. Along with safety features, the car is loaded with numerous features. The Hyundai Santafee comes with SmartSense safety systems, which include a variety of cameras, radars, and motion detection technologies such as Forward Collision-Avoidance Assist (FCA), meant to identify cars, pedestrians, or cyclists who are directly in front of the car. In April 2021, In Japan, Toyota Motor Corp. presented revised versions of the Lexus LS and Toyota Mirai. Both vehicles have Level 2 autonomous Advanced Drive, which supports lane keeping, maintaining a safe distance from other vehicles, lane changes, and advanced driver assistance. Furthermore, many governments across the world have put rigorous car emission standards into place to lower the quantity of greenhouse gas emissions in the environment which is promoting the adoption of autonomous cars. The European Union has established a policy to cut the CO2 emissions of light and medium commercial vehicles by 15% before 2025. Along with these, the government of Japan also set a target to reduce CO2 emissions and other greenhouse gasses by about 80% per vehicle by 2050. Thus, the rising government focus on reducing emissions through vehicles is driving market growth. In addition, increasingly stringent government regulations focusing on increasing road safety, and rising demand for advanced automotive safety are creating lucrative growth in the market. However, the high cost of autonomous cars and cybersecurity and safety concerns stifle market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Autonomous Cars Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the presence of key market players and rising technological advancement and development of advanced driving assistant systems. Europe is expected to grow significantly during the forecast period, owing to factors such as rising government initiatives for limiting carbon emission, rising adoption of advanced technologies, and geographic expansion of key players in the region.

Major market player included in this report are:
Uber Technologies Inc.
Daimler AG
Waymo LLC (Google Inc.)
Toyota Motor Corp.
Nissan Motor Corporation
Volvo Car Group
General Motors Company
Volkswagen AG
Tesla Inc.
Bayerische Motoren Werke AG

Recent Developments in the Market:
Ø In May 2022, Volkswagen’s software division CARIAD announced a partnership with Qualcomm for level 4 self-driving technology. Through the collaboration, Volkswagen would be able to employ Qualcomm’s system on a chip (SOC), which was created especially for driverless vehicles, across all its brands. Cariad has created a level 4 autonomous driving capability based on Qualcomm’s Snapdragon Ride Platform.
Ø In January 2022, Volvo announced the launch of the autonomous driving feature Ride Pilot. This software was created by the autonomous driving software startup Zeneact with assistance from the Volvo Cars development team and the Luminar team of programmers. The system is made up of sensors, including the cutting-edge Iris LiDAR sensor from Luminar, having integrated functions software.

Global Autonomous Cars Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Type, Vehicle Type, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Typeofferings of key players. The detailed segments and sub-segment of the market are explained below:

By Type:
Fully Autonomous
Semi-Autonomous

By Vehicle Type:
Passenger Cars
Commercial Vehicles

By Region:

North America
U.S.
Canada

Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC

Latin America
Brazil
Mexico

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Autonomous Cars Market, by Region, 2020-2030 (USD Billion)
1.2.2. Autonomous Cars Market, by Type, 2020-2030 (USD Billion)
1.2.3. Autonomous Cars Market, by Vehicle Type, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Autonomous Cars Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Autonomous Cars Market Dynamics
3.1. Autonomous Cars Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Increasing Adoption of Advanced Driver Assistance System (ADAS)
3.1.1.2. Increasing Demand for Automated Energy-efficient Vehicles
3.1.2. Market Challenges
3.1.2.1. High Cost of Autonomous Cars
3.1.2.2. Cybersecurity and safety concerns
3.1.3. Market Opportunities
3.1.3.1. Increasingly stringent government regulations focusing on increasing road safety.
3.1.3.2. Rising Demand for Advanced Automotive Safety
Chapter 4. Global Autonomous Cars Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Autonomous Cars Market, by Type
5.1. Market Snapshot
5.2. Global Autonomous Cars Market by Type, Performance – Potential Analysis
5.3. Global Autonomous Cars Market Estimates & Forecasts by Type 2020-2030 (USD Billion)
5.4. Autonomous Cars Market, Sub Segment Analysis
5.4.1. Fully Autonomous
5.4.2. Semi-Autonomous
Chapter 6. Global Autonomous Cars Market, by Vehicle Type
6.1. Market Snapshot
6.2. Global Autonomous Cars Market by Vehicle Type, Performance – Potential Analysis
6.3. Global Autonomous Cars Market Estimates & Forecasts by Vehicle Type 2020-2030 (USD Billion)
6.4. Autonomous Cars Market, Sub Segment Analysis
6.4.1. Passenger Cars
6.4.2. Commercial Vehicles
Chapter 7. Global Autonomous Cars Market, Regional Analysis
7.1. Top Leading Countries
7.2. Top Emerging Countries
7.3. Autonomous Cars Market, Regional Market Snapshot
7.4. North America Autonomous Cars Market
7.4.1. U.S. Autonomous Cars Market
7.4.1.1. Type breakdown estimates & forecasts, 2020-2030
7.4.1.2. Vehicle Type breakdown estimates & forecasts, 2020-2030
7.4.2. Canada Autonomous Cars Market
7.5. Europe Autonomous Cars Market Snapshot
7.5.1. U.K. Autonomous Cars Market
7.5.2. Germany Autonomous Cars Market
7.5.3. France Autonomous Cars Market
7.5.4. Spain Autonomous Cars Market
7.5.5. Italy Autonomous Cars Market
7.5.6. Rest of Europe Autonomous Cars Market
7.6. Asia-Pacific Autonomous Cars Market Snapshot
7.6.1. China Autonomous Cars Market
7.6.2. India Autonomous Cars Market
7.6.3. Japan Autonomous Cars Market
7.6.4. Australia Autonomous Cars Market
7.6.5. South Korea Autonomous Cars Market
7.6.6. Rest of Asia Pacific Autonomous Cars Market
7.7. Latin America Autonomous Cars Market Snapshot
7.7.1. Brazil Autonomous Cars Market
7.7.2. Mexico Autonomous Cars Market
7.8. Middle East & Africa Autonomous Cars Market
7.8.1. Saudi Arabia Autonomous Cars Market
7.8.2. South Africa Autonomous Cars Market
7.8.3. Rest of Middle East & Africa Autonomous Cars Market

Chapter 8. Competitive Intelligence
8.1. Key Company SWOT Analysis
8.1.1. Company 1
8.1.2. Company 2
8.1.3. Company 3
8.2. Top Market Strategies
8.3. Company Profiles
8.3.1. Uber Technologies Inc.
8.3.1.1. Key Information
8.3.1.2. Overview
8.3.1.3. Financial (Subject to Data Availability)
8.3.1.4. Product Summary
8.3.1.5. Recent Developments
8.3.2. Daimler AG
8.3.3. Waymo LLC (Google Inc.)
8.3.4. Toyota Motor Corp.
8.3.5. Nissan Motor Corporation
8.3.6. Volvo Car Group
8.3.7. General Motors Company
8.3.8. Volkswagen AG
8.3.9. Tesla Inc.
8.3.10. Bayerische Motoren Werke AG
Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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