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Global Robotaxi Market to reach USD XX billion by 2027

Global Robotaxi Market to reach USD XX billion by 2027

Product Code: ALTST-37260619
Publish Date: 11-07-2021
Page: 200

Global Robotaxi Market is valued at approximately USD XX billion in 2020 and is anticipated to grow with a healthy growth rate of more than XX % over the forecast period 2021-2027. The market has grown as a result of mounting worries about road safety, pollutants, and increased demand for ride-hailing services. Autonomous vehicles also assist fleet operators in reducing costs. Newer business models, such as mobility as a service, could provide a future revenue source that is both sustainable and profitable. Every day, nearly 94 percent of car accidents are caused by human error, according to the NHTSA. According to Waymo, roughly 1.4 million people die each year in traffic accidents around the world by the year 2020. According to the Mobility of the Future research published by the MIT Energy Initiative in 2020, around 40,000 people died in traffic accidents in the United States in 2019. These faults in behavior can be reduced if technology manages human activities including driving. This is predicted to result in fewer owned automobiles on the road, reducing the number of cars in cities around the world. As a result, traffic congestion should be reduced, and traffic control efficiency should improve. The rush to deploy autonomous vehicles has piqued the interest of public policymakers in autonomous mobility and its potential implications, particularly in industrialized countries. Various governments have already eased legal restrictions in order to conduct self-driving vehicle testing. Finland’s Ministry of Transport and Communications has taken a step forward by preparing a legal framework for autonomous vehicle testing. Many other countries, including Austria, France, the Netherlands, the United Kingdom, and the United States, are following suit. For example, The California Public Utilities Commission (CPUC) announced two new commercial initiatives in 2020. However, human jobs being jeopardized by machines is expected to reduce wide acceptance which may impede market growth over the forecast period of 2021-2027.

The regional analysis of the global Robo-taxi Market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America, and Rest of the World (ROW). Europe is the leading region across the world in terms of market share due to technological advancements and developed & supportive infrastructure in the region. Whereas Asia Pacific is also anticipated to exhibit the highest growth rate over the forecast period 2021-2027 due to growing technological trends for autonomous vehicles will greatly impact the market.

Major market player included in this report are:

Cruise Automation
Uber Technologies Inc.
Daimler AG
Ford Motor Company
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 product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Application Type:
Goods Transportation
Passenger Transportation
By Level of Autonomy:
Level 4
Level 5
By Vehicle Type:
By Propulsion:
Fuel Cell

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
Base year –2020
Forecast period – 2021 to 2027.

Target Audience of the Global Robotaxi 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, 2019-2027 (USD Billion)
1.2.1. Robo-taxi Market , by Region, 2019-2027 (USD Billion)
1.2.2. Robo-taxi Market , by Application Type, 2019-2027 (USD Billion)
1.2.3. Robo-taxi Market , by Level of Autonomy, 2019-2027 (USD Billion)
1.2.4. Robo-taxi Market , by Vehicle Type, 2019-2027 (USD Billion)
1.2.5. Robo-taxi Market , by Propulsion, 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Robo-taxi 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 Robo-taxi Market Dynamics
3.1. Robo-taxi Market Impact Analysis (2019-2027)
3.1.1. Market Drivers Need for enhanced road safety and traffic control. Reduced overall operating costs.
3.1.2. Market Restraint Human jobs being jeopardized by machines expected to reduce wide acceptance
3.1.3. Market Opportunities Government support
Chapter 4. Global Robo-taxi 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 (2018-2027)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
Chapter 5. Global Robo-taxi Market , by Application Type
5.1. Market Snapshot
5.2. Global Robo-taxi Market by Application Type , Performance – Potential Analysis
5.3. Global Robo-taxi Market Estimates & Forecasts by Application Type 2018-2027 (USD Billion)
5.4. Robo-taxi Market , Sub Segment Analysis
5.4.1. Goods Transportation
5.4.2. Passenger Transportation
Chapter 6. Global Robo-taxi Market , by Level of Autonomy
6.1. Market Snapshot
6.2. Global Robo-taxi Market by Level of Autonomy, Performance – Potential Analysis
6.3. Global Robo-taxi Market Estimates & Forecasts by Level of Autonomy 2018-2027 (USD Billion)
6.4. Robo-taxi Market , Sub Segment Analysis
6.4.1. Level 4
6.4.2. Level 5
Chapter 7. Global Robo-taxi Market , by Vehicle Type
7.1. Market Snapshot
7.2. Global Robo-taxi Market by Vehicle Type, Performance – Potential Analysis
7.3. Global Robo-taxi Market Estimates & Forecasts by Vehicle Type 2018-2027 (USD Billion)
7.4. Robo-taxi Market , Sub Segment Analysis
7.4.1. Car
7.4.2. Shuttle/Van
Chapter 8. Global Robo-taxi Market , by Propulsion
8.1. Market Snapshot
8.2. Global Robo-taxi Market by Propulsion, Performance – Potential Analysis
8.3. Global Robo-taxi Market Estimates & Forecasts by Propulsion 2018-2027 (USD Billion)
8.4. Robo-taxi Market , Sub Segment Analysis
8.4.1. Electric
8.4.2. Hybrid
8.4.3. Fuel Cell
Chapter 9. Global Robo-taxi Market , Regional Analysis
9.1. Robo-taxi Market , Regional Market Snapshot
9.2. North America Robo-taxi Market
9.2.1. U.S. Robo-taxi Market Application Type breakdown estimates & forecasts, 2018-2027 Level of Autonomy breakdown estimates & forecasts, 2018-2027 Vehicle Type breakdown estimates & forecasts, 2018-2027 Propulsion breakdown estimates & forecasts, 2018-2027
9.2.2. Canada Robo-taxi Market
9.3. Europe Robo-taxi Market Snapshot
9.3.1. U.K. Robo-taxi Market
9.3.2. Germany Robo-taxi Market
9.3.3. France Robo-taxi Market
9.3.4. Spain Robo-taxi Market
9.3.5. Italy Robo-taxi Market
9.3.6. Rest of Europe Robo-taxi Market
9.4. Asia-Pacific Robo-taxi Market Snapshot
9.4.1. China Robo-taxi Market
9.4.2. India Robo-taxi Market
9.4.3. Japan Robo-taxi Market
9.4.4. Australia Robo-taxi Market
9.4.5. South Korea Robo-taxi Market
9.4.6. Rest of Asia Pacific Robo-taxi Market
9.5. Latin America Robo-taxi Market Snapshot
9.5.1. Brazil Robo-taxi Market
9.5.2. Mexico Robo-taxi Market
9.6. Rest of The World Robo-taxi Market
Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Waymo Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
10.2.2. Cruise Automation
10.2.3. Baidu
10.2.4. AutoX
10.2.5. Tesla
10.2.6. Uber Technologies Inc.
10.2.7. NAVYA
10.2.8. EasyMile
10.2.9. Daimler AG
10.2.10. Ford Motor Company
Chapter 11. Research Level of Autonomy
11.1. Research Level of Autonomy
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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Data Collection:
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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.
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