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Global Self-driving Cars Market to reach USD 6.36 billion by 2028.

Global Self-driving Cars Market Size study, By Component (Camera Unit, LiDAR, Radar Sensor, Ultrasonic Sensor, Infrared Sensor), By Mobility type (Shared Mobility, Personal Mobility), By Electric vehicle (Battery Electric Vehicles (BEV), Hybrid Electric Vehicles (HEV), Plug-in Hybrid Electric Vehicle (PHEV), Fuel Cell Electric Vehicle (FCEV)), By System (Adaptive Cruise Control (ACC), Adaptive Front Light (AFL), Automatic Emergency Braking (AEB), Blind Spot Detection (BSD), Cross Traffic Alert (CTA), Driver Monitoring System (DMS), Forward Collision Warning (FCW), Intelligent Park Assist (IPA), Lane Departure Warning (LDW), Night Vision System (NVS), Pedestrian Detection System (PDS), Road Sign Recognition (RSR), Tire Pressure Monitoring System (TPMS), Traffic Jam Assist (TJA)), By Vehicle type (Hatchback, Coupe & Sports Car, Sedan, SUV, Others), and Regional Forecasts 2022-2028

Product Code: ALTST-12818674
Publish Date: 22-04-2022
Page: 200

Global Self-driving Cars Market is valued approximately USD 1.74 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 20.3% over the forecast period 2022-2028. A self-driving car is also commonly known as a driverless car, an autonomous vehicle (AV), or a robotic car (robo-car). This car encompasses various types of sensors to perceive their environs, such as GPS, odometry, radar, LIDAR, sonar, thermographic cameras, and inertial measurement units. Self-driving cars are integrated with vehicular automation, which is a ground vehicle that is proficient to sense its environment and moving securely with no or little human participation. The implementation of stringent safety regulations, growing demand for luxury vehicles, safety and driving comfort features, as well as the introduction of AI-based camera systems for self-driving applications are the chief driving factors for the Global market growth. In addition, the emergence of novel technologies such as machine learning and artificial intelligence, coupled with the development of connected vehicle technology and dynamic mobile application are the factors which are expected to further fuel the market growth across the globe. For instance, in September 2021, Mercedes-Benz declared to incorporate the first brain-computer interface (BCI) approaches with the company’s new VISION AVTR notion vehicle. Similarly, in September 2021, Honda Motor Co., Ltd. declared the commencement of the company’s testing program that is initiated for autonomous vehicles. The objective of this program is the development of an autonomous vehicle mobility service (MaaS) business across Japan. The biometric integration with the vehicle is accompanied by a direct linking with the human brain, which facilitates a completely new interaction between man, machine, and nature in the autonomous-driving concept vehicle. Therefore, the incorporation of new technologies in self-driving cars is bolstering the market demand. However, the lack of required infrastructure in emerging countries and real-time image processing in multi-camera systems impedes the growth of the market over the forecast period of 2022-2028. Also, increasing demand for 5G technology for vehicle connectivity and rapid development of ADAS technology is anticipated to act as a catalyzing factor for the market demand during the forecast period.

The key regions considered for the Global Self-driving Cars Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. Asia-Pacific is the leading region across the world in terms of market share owing to the execution of stringent safety regulations, and rising demand for a safe, efficient, and convenient driving experience. Whereas, Asia-Pacific is also anticipated to exhibit the highest CAGR over the forecast period 2022-2028. Factors such as growing disposable income in emerging economies, as well as growing technological advancements, would create lucrative growth prospects for the self-driving cars market across the Asia-Pacific region.

Major market players included in this report are:
General Motors Company
Ford Motors Company
Daimler AG
Volkswagen Group
Toyota Motors Corporation
Waymo LLC
BYD Co. Ltd.
Aurora Innovation, Inc.
Tesla, Inc.
Denso Corporation

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 eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Component offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Component:
Camera Unit
Radar Sensor
Ultrasonic Sensor
Infrared Sensor
By Mobility type:
Shared Mobility
Personal Mobility
By Electric vehicle:
Battery Electric Vehicles (BEV)
Hybrid Electric Vehicles (HEV)
Plug-in Hybrid Electric Vehicle (PHEV)
Fuel Cell Electric Vehicle (FCEV)
By System:
Adaptive Cruise Control (ACC)
Adaptive Front Light (AFL)
Automatic Emergency Braking (AEB)
Blind Spot Detection (BSD)
Cross Traffic Alert (CTA)
Driver Monitoring System (DMS)
Forward Collision Warning (FCW)
Intelligent Park Assist (IPA)
Lane Departure Warning (LDW)
Night Vision System (NVS)
Pedestrian Detection System (PDS)
Road Sign Recognition (RSR)
Tire Pressure Monitoring System (TPMS)
Traffic Jam Assist (TJA)
By Vehicle type:
Coupe & Sports Car
By Region:
North America

Asia Pacific
South Korea
Latin America
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Self-driving Cars Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Billion)
1.2.1. Global Self-driving Cars Market, by region, 2020-2028 (USD Billion)
1.2.2. Global Self-driving Cars Market, by Component, 2020-2028 (USD Billion)
1.2.3. Global Self-driving Cars Market, by Mobility type, 2020-2028 (USD Billion)
1.2.4. Global Self-driving Cars Market, by Electric vehicle, 2020-2028 (USD Billion)
1.2.5. Global Self-driving Cars Market, by System, 2020-2028 (USD Billion)
1.2.6. Global Self-driving Cars Market, by Vehicle type, 2020-2028 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Self-driving Cars Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Self-driving Cars Market Dynamics
3.1. Self-driving Cars Market Impact Analysis (2020-2028)
3.1.1. Market Drivers Growing demand for safety and driving comfort features Emergence of the AI-based camera systems for self-driving applications
3.1.2. Market Challenges Lack of required infrastructure in emerging countries Real-time image processing in multi-camera systems
3.1.3. Market Opportunities Increasing demand for 5G technology for vehicle connectivity Rapid development of ADAS technology
Chapter 4. Global Self-driving 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
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2019-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economic
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 market scenario
Chapter 6. Global Self-driving Cars Market, by Component
6.1. Market Snapshot
6.2. Global Self-driving Cars Market by Component, Performance – Potential Analysis
6.3. Global Self-driving Cars Market Estimates & Forecasts by Component 2019-2028 (USD Billion)
6.4. Self-driving Cars Market, Sub Segment Analysis
6.4.1. Camera Unit
6.4.2. LiDAR
6.4.3. Radar Sensor
6.4.4. Ultrasonic Sensor
6.4.5. Infrared Sensor
Chapter 7. Global Self-driving Cars Market, by Mobility type
7.1. Market Snapshot
7.2. Global Self-driving Cars Market by Mobility type, Performance – Potential Analysis
7.3. Global Self-driving Cars Market Estimates & Forecasts by Mobility type 2019-2028 (USD Billion)
7.4. Self-driving Cars Market, Sub Segment Analysis
7.4.1. Shared Mobility
7.4.2. Personal Mobility
Chapter 8. Global Self-driving Cars Market, by Electric vehicle
8.1. Market Snapshot
8.2. Global Self-driving Cars Market by Electric vehicle, Performance – Potential Analysis
8.3. Global Self-driving Cars Market Estimates & Forecasts by Electric vehicle 2019-2028 (USD Billion)
8.4. Self-driving Cars Market, Sub Segment Analysis
8.4.1. Battery Electric Vehicles (BEV)
8.4.2. Hybrid Electric Vehicles (HEV)
8.4.3. Plug-in Hybrid Electric Vehicle (PHEV)
8.4.4. Fuel Cell Electric Vehicle (FCEV)
Chapter 9. Global Self-driving Cars Market, by System
9.1. Market Snapshot
9.2. Global Self-driving Cars Market by System, Performance – Potential Analysis
9.3. Global Self-driving Cars Market Estimates & Forecasts by System 2019-2028 (USD Billion)
9.4. Self-driving Cars Market, Sub Segment Analysis
9.4.1. Adaptive Cruise Control (ACC)
9.4.2. Adaptive Front Light (AFL)
9.4.3. Automatic Emergency Braking (AEB)
9.4.4. Blind Spot Detection (BSD)
9.4.5. Cross Traffic Alert (CTA)
9.4.6. Driver Monitoring System (DMS)
9.4.7. Forward Collision Warning (FCW)
9.4.8. Intelligent Park Assist (IPA)
9.4.9. Lane Departure Warning (LDW)
9.4.10. Night Vision System (NVS)
9.4.11. Pedestrian Detection System (PDS)
9.4.12. Road Sign Recognition (RSR)
9.4.13. Tire Pressure Monitoring System (TPMS)
9.4.14. Traffic Jam Assist (TJA)
Chapter 10. Global Self-driving Cars Market, by Vehicle type
10.1. Market Snapshot
10.2. Global Self-driving Cars Market by Vehicle type, Performance – Potential Analysis
10.3. Global Self-driving Cars Market Estimates & Forecasts by Vehicle type 2019-2028 (USD Billion)
10.4. Self-driving Cars Market, Sub Segment Analysis
10.4.1. Hatchback
10.4.2. Coupe & Sports Car
10.4.3. Sedan
10.4.4. SUV
10.4.5. Others
Chapter 11. Global Self-driving Cars Market, Regional Analysis
11.1. Self-driving Cars Market, Regional Market Snapshot
11.2. North America Self-driving Cars Market
11.2.1. U.S. Self-driving Cars Market Component estimates & forecasts, 2019-2028 Mobility type estimates & forecasts, 2019-2028 Electric vehicle estimates & forecasts, 2019-2028 System estimates & forecasts, 2019-2028 Vehicle type estimates & forecasts, 2019-2028
11.2.2. Canada Self-driving Cars Market
11.3. Europe Self-driving Cars Market Snapshot
11.3.1. U.K. Self-driving Cars Market
11.3.2. Germany Self-driving Cars Market
11.3.3. France Self-driving Cars Market
11.3.4. Spain Self-driving Cars Market
11.3.5. Italy Self-driving Cars Market
11.3.6. Rest of Europe Self-driving Cars Market
11.4. Asia-Pacific Self-driving Cars Market Snapshot
11.4.1. China Self-driving Cars Market
11.4.2. India Self-driving Cars Market
11.4.3. Japan Self-driving Cars Market
11.4.4. Australia Self-driving Cars Market
11.4.5. South Korea Self-driving Cars Market
11.4.6. Rest of Asia Pacific Self-driving Cars Market
11.5. Latin America Self-driving Cars Market Snapshot
11.5.1. Brazil Self-driving Cars Market
11.5.2. Mexico Self-driving Cars Market
11.6. Rest of The World Self-driving Cars Market
Chapter 12. Competitive Intelligence
12.1. Top Market Strategies
12.2. Company Profiles
12.2.1. General Motors Company Key Information Overview Financial (Subject to Data Availability) Component Summary Recent Developments
12.2.2. Ford Motors Company
12.2.3. Daimler AG
12.2.4. Volkswagen Group
12.2.5. Toyota Motors Corporation
12.2.6. Waymo LLC
12.2.7. BYD Co. Ltd.
12.2.8. Aurora Innovation, Inc.
12.2.9. Tesla, Inc.
12.2.10. Denso Corporation
Chapter 13. Research Process
13.1. Research Process
13.1.1. Data Mining
13.1.2. Analysis
13.1.3. Market Estimation
13.1.4. Validation
13.1.5. Publishing
13.2. Research Attributes
13.3. 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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