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Global Software-Defined Vehicles Market to reach USD 137.53 billion by the end of 2030

Global Software-Defined Vehicles Market Size study & Forecast, by Application (ADAS & Safety, Connected Vehicle Services, Autonomous Driving, Body Control & Comfort System, Powertrain System), by Vehicle Type, by Propulsion Type (ICE Vehicles, Electric Vehicles), by Level of Autonomy (Level 1, Level 2, Level 3, Level 4, Level 5), and Regional Analysis, 2023-2030

Product Code: ALTST-41509437
Publish Date: 20-07-2023
Page: 200

Global Software-Defined Vehicles Market is valued at approximately USD 34.2 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 19% over the forecast period 2023-2030. A Software Defined Vehicle is a vehicle that relies heavily on software to enable its functionalities and operations. This progressive transformation of automobiles involves shifting from a predominantly hardware-oriented product to a software-focused device on wheels, leading to the emergence and expansion of this specific category. The increasing adoption of software-defined vehicles is primarily attributed to their semi-autonomous and autonomous capabilities, particularly in scenarios such as monotonous highway driving, navigating through traffic jams, and challenging parking situations. These vehicles incorporate features such as highway pilot, traffic jam assist, and parking assist, where the vehicle’s computer assumes situational control, partially or entirely. The growing demand for higher levels of autonomy in vehicles is a significant driver for the expansion of the software-defined vehicles market.

The market demand for software-defined vehicles is primarily fueled by their ability to significantly mitigate accidents resulting from human error. These vehicles are equipped with advanced safety features such as anti-collision systems and driver assistance technology, which further enhance their safety capabilities. Based on the findings from the U.S. General Services Administration’s Office of Motor Vehicle Management, human error is responsible for 98% of car crashes. Additionally, car crashes take place approximately every 5 seconds. Based on the statistics provided by the Centers for Disease Control and Prevention, global roadways witness approximately 1.35 million fatalities annually. This translates to nearly 3,700 deaths every day, resulting from various types of accidents involving cars, buses, motorcycles, bicycles, trucks, or pedestrians. Additionally, the software-defined vehicles market is propelled by several significant factors, including the escalating demand for connected and autonomous vehicles, the increasing emphasis on enhanced safety features, and the growing need for vehicles that are both environmentally friendly and efficient. However, the cost of software-defined vehicles is typically higher compared to traditional cars, which can limit their accessibility to certain consumers. Software-defined vehicles must have a robust infrastructure that may not be universally accessible in all regions, these are the two factors that may stifle market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Software-Defined Vehicles Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022. The growth of the region can be attributed to the concentration of prominent automotive manufacturers and technology companies, coupled with the rising market demand for electric and autonomous vehicles. This convergence of factors is anticipated to drive the expansion and development of the region. Europe is expected to grow significantly during the forecast period, as this region serves as a thriving hub for innovation due to its robust automotive industry and the presence of numerous prominent automotive manufacturers. Its strong foundation in the automotive sector positions it as a center for pioneering advancements in the industry.

Major market player included in this report are:
Tesla, Inc.
Toyota Motor Corporation
Volkswagen Ag
General Motors Company
BYD Company Limited
Hyundai Motor Company
Ford Motor Company
Honda Motor Co., Ltd.
Mercedes Benz Group AG
BMW Group

Recent Developments in the Market:
Ø In October 2022, Hyundai Motor Group (South Korea) revealed its strategic entry into the Software-Defined vehicle market, taking a significant leap forward by introducing Software-Defined vehicles in both gasoline and electric variants. The company aims to have 20 million connected vehicles equipped with its internally developed Integrated Modular Architecture (IMA) and Connected Car Operating System (CCOS) on the road by 2025. This ambitious plan demonstrates Hyundai Motor Group’s commitment to advanced vehicle technology and connectivity in the automotive industry.
Ø In October 2022, NVIDIA and Qualcomm have recently unveiled their latest System on Chip (SoC) portfolios for Software-Defined vehicles, namely Drive Thor and Ride Flex SoC. These new offerings are positioned as the “industry’s first super-compute class SoC portfolio” and are aimed at capturing a significant share of the semiconductor segment within the Software-Defined vehicle market. With their advanced capabilities, these SoCs are designed to power the next generation of intelligent and connected vehicles.

Global Software-Defined Vehicles 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 – Application, Vehicle Type, Propulsion Type, Level of Autonomy, 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 product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Application:
ADAS & Safety
Connected Vehicle Services
Autonomous Driving
Body Control & Comfort System
Powertrain System

By Vehicle Type:
Passenger Car
Commercial Vehicles

By Propulsion Type:
ICE Vehicles
Electric Vehicles

By Level Of Autonomy:
Level 1
Level 2
Level 3
Level 4
Level 5

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. Software-Defined Vehicles Market, by Region, 2020-2030 (USD Billion)
1.2.2. Software-Defined Vehicles Market, by Application, 2020-2030 (USD Billion)
1.2.3. Software-Defined Vehicles Market, by Vehicle Type, 2020-2030 (USD Billion)
1.2.4. Software-Defined Vehicles Market, by Propulsion Type, 2020-2030 (USD Billion)
1.2.5. Software-Defined Vehicles Market, by Level of Autonomy, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Software-Defined Vehicles 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 Software-Defined Vehicles Market Dynamics
3.1. Software-Defined Vehicles Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Increasing semi-autonomous and autonomous capabilities
3.1.1.2. Growing demand for higher levels of autonomy in vehicles
3.1.2. Market Challenges
3.1.2.1. High Cost of Software-Defined Vehicles
3.1.2.2. Lack Of Infrastructural Facilities
3.1.3. Market Opportunities
3.1.3.1. Growing need for environmentally friendly and efficient vehicles
3.1.3.2. Escalating demand for connected and autonomous vehicles
3.1.3.3. Increasing emphasis on enhanced safety features
Chapter 4. Global Software-Defined Vehicles 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 Software-Defined Vehicles Market, by Application
5.1. Market Snapshot
5.2. Global Software-Defined Vehicles Market by Application, Performance – Potential Analysis
5.3. Global Software-Defined Vehicles Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
5.4. Software-Defined Vehicles Market, Sub Segment Analysis
5.4.1. ADAS & Safety
5.4.2. Connected Vehicle Services
5.4.3. Autonomous Driving
5.4.4. Body Control & Comfort System
5.4.5. Powertrain System
Chapter 6. Global Software-Defined Vehicles Market, by Vehicle Type
6.1. Market Snapshot
6.2. Global Software-Defined Vehicles Market by Vehicle Type, Performance – Potential Analysis
6.3. Global Software-Defined Vehicles Market Estimates & Forecasts by Vehicle Type 2020-2030 (USD Billion)
6.4. Software-Defined Vehicles Market, Sub Segment Analysis
6.4.1. Passenger Car
6.4.2. Commercial Vehicles
Chapter 7. Global Software-Defined Vehicles Market, by Propulsion Type
7.1. Market Snapshot
7.2. Global Software-Defined Vehicles Market by Propulsion Type, Performance – Potential Analysis
7.3. Global Software-Defined Vehicles Market Estimates & Forecasts by Propulsion Type 2020-2030 (USD Billion)
7.4. Software-Defined Vehicles Market, Sub Segment Analysis
7.4.1. ICE Vehicles
7.4.2. Electric Vehicles
Chapter 8. Global Software-Defined Vehicles Market, by Level of Autonomy
8.1. Market Snapshot
8.2. Global Software-Defined Vehicles Market by Level of Autonomy, Performance – Potential Analysis
8.3. Global Software-Defined Vehicles Market Estimates & Forecasts by Level of Autonomy 2020-2030 (USD Billion)
8.4. Software-Defined Vehicles Market, Sub Segment Analysis
8.4.1. Level 1
8.4.2. Level 2
8.4.3. Level 3
8.4.4. Level 4
8.4.5. Level 5
Chapter 9. Global Software-Defined Vehicles Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Software-Defined Vehicles Market, Regional Market Snapshot
9.4. North America Software-Defined Vehicles Market
9.4.1. U.S. Software-Defined Vehicles Market
9.4.1.1. Application breakdown estimates & forecasts, 2020-2030
9.4.1.2. Vehicle Type breakdown estimates & forecasts, 2020-2030
9.4.1.3. Propulsion Type breakdown estimates & forecasts, 2020-2030
9.4.1.4. Level of Autonomy breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Software-Defined Vehicles Market
9.5. Europe Software-Defined Vehicles Market Snapshot
9.5.1. U.K. Software-Defined Vehicles Market
9.5.2. Germany Software-Defined Vehicles Market
9.5.3. France Software-Defined Vehicles Market
9.5.4. Spain Software-Defined Vehicles Market
9.5.5. Italy Software-Defined Vehicles Market
9.5.6. Rest of Europe Software-Defined Vehicles Market
9.6. Asia-Pacific Software-Defined Vehicles Market Snapshot
9.6.1. China Software-Defined Vehicles Market
9.6.2. India Software-Defined Vehicles Market
9.6.3. Japan Software-Defined Vehicles Market
9.6.4. Australia Software-Defined Vehicles Market
9.6.5. South Korea Software-Defined Vehicles Market
9.6.6. Rest of Asia Pacific Software-Defined Vehicles Market
9.7. Latin America Software-Defined Vehicles Market Snapshot
9.7.1. Brazil Software-Defined Vehicles Market
9.7.2. Mexico Software-Defined Vehicles Market
9.8. Middle East & Africa Software-Defined Vehicles Market
9.8.1. Saudi Arabia Software-Defined Vehicles Market
9.8.2. South Africa Software-Defined Vehicles Market
9.8.3. Rest of Middle East & Africa Software-Defined Vehicles Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. Tesla, Inc
10.3.1.1. Key Information
10.3.1.2. Overview
10.3.1.3. Financial (Subject to Data Availability)
10.3.1.4. Product Summary
10.3.1.5. Recent Developments
10.3.2. Toyota Motor Corporation
10.3.3. Volkswagen Ag
10.3.4. General Motors Company
10.3.5. BYD Company Limited
10.3.6. Hyundai Motor Company
10.3.7. Ford Motor Company
10.3.8. Honda Motor Co., Ltd.
10.3.9. Mercedes Benz Group AG
10.3.10. BMW Group
Chapter 11. Research Process
11.1. Research Process
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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