Software-Defined Vehicles Market (By Propulsion: ICE Vehicles, Electric Vehicles; By Application: ADAS & Safety, Connected Vehicle Services, Autonomous Driving, Body Control & Comfort System, Powertrain System; By Vehicle Type: Passenger Car, Commercial Vehicles; By Level of Autonomy: Level 1, Level 2, Level 3, Level 4, Level 5) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2023-2032
The global software-defined vehicles market size was estimated at USD 35.6 billion in 2022 and it is expected to hit around USD 210.88 billion by 2032, growing at a CAGR of 19.47% during the forecast period from 2023 to 2032.
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The Software-Defined Vehicles Market refers to the use of software-defined networking (SDN) and software-defined architecture (SDA) technologies to enhance the functionality, safety, and efficiency of vehicles. This technology is becoming increasingly popular in the automotive industry as it allows vehicles to be more connected, customizable, and secure. It also allows for more efficient communication between the various systems within the car, such as the engine, braking, and safety systems. Some of the key drivers of the software-defined vehicles market include the increasing demand for connected and autonomous vehicles, the growing need for improved safety features, and the rising demand for more efficient and environmentally friendly vehicles.
SDVs enable customers to receive firmware patches, enhancements to infotainment, tuning, and monitoring of key functional capabilities like vehicle and powertrain dynamics, and feature-on-demand comfort services via over-the-air (OTA) updates.
Report Coverage | Details |
Market Size in 2023 | USD 42.53 Billion |
Market Size by 2032 | USD 210.88 Billion |
Growth Rate from 2023 to 2032 | CAGR of 19.47% |
Largest Market | North America |
Base Year | 2022 |
Forecast Period | 2023 to 2032 |
Segments Covered | By Propulsion, By Application, By Vehicle Type and By Level of Autonomy |
Regions Covered | North America, Europe, Asia-Pacific, Latin America and Middle East & Africa |
Drivers
Increase safety and upgradation
Software-defined vehicles are easier to upgrade and have enhanced features by utilizing over-the-air software as per the need of the driver. SDVs have the potential to significantly reduce the number of accidents caused by human error. The vehicle also has an anti-collision and driver assistance feature for enhanced safety. The updates are independent of the model of the vehicle as well as the speed and agility of the vehicle.
Greater accessibility
SDVs have the potential to provide greater mobility for people who are unable to drive due to physical disabilities or other reasons. With the help of advanced software and technology, SDVs are programmed to safely transport passengers with different mobility needs.
Restraints:
Increase cost as well as rising infrastructure
Software-defined vehicles are generally more expensive than traditional cars due to the different technology and components required, making them less accessible to some consumers. For software-defined vehicles to function properly, there needs to be a robust infrastructure in place to support them. This includes high-speed internet, 5G networks, and other technologies that may not be widely available in some areas.
Opportunities:
During the transition to software-defined vehicles, conventional automobile manufacturers will face difficulties and challenges, as well as chances for new automotive industry players such as chip suppliers, software suppliers, and Internet companies. The transformation to software-defined vehicles will be an unstoppable trend driving the growth of the automotive business over the next 5-10 years. All businesses in the industrial chain must conduct comprehensive evaluations and forward planning in order to maintain initiative during the new industrial transformation.
Impact of COVID-19:
The COVID-19 pandemic had a significant impact on various industries, including the automotive industry, which includes the software-defined vehicles market. The pandemic has resulted in a decline in demand for new vehicles due to economic uncertainty as well as decreased consumer spending. This has affected the sales of software-defined vehicles, as manufacturers have reduced production due to reduced demand. However, the pandemic had also accelerated the adoption of remote work and online shopping, leading to increased demand for delivery vehicles, which had a positive impact on the market for software-defined commercial vehicles.
However, these vehicles also offer greater flexibility and customization, allowing manufacturers to adapt to changing market demands. As the world continues to recover from the pandemic, the software-defined vehicles market is expected to grow as manufacturers continue to invest in research and development to improve vehicle technology and meet evolving customer needs. In particular, the market for autonomous vehicles, which rely heavily on advanced software systems, is expected to see significant growth in the coming years.
Electric Vehicles (EVs) sector is anticipated to grow at the highest CAGR from 2023 to 2032. EVs use electric motors and batteries to power the vehicle. Software-defined EVs optimize battery usage, improve charging times, and provide more accurate range estimates. Electric vehicles are powered by electricity and have a battery that stores energy, while software-defined vehicles are equipped with advanced software that controls various aspects of the vehicle, such as performance, safety, and entertainment.
The internal Combustion Engine (ICE) Vehicles segment is anticipated to grow at the fastest CAGR from 2023 to 2032. These are vehicles that use a traditional gasoline or diesel engine to power the vehicle. In the case of internal combustion engines, software-defined vehicles are equipped with electronic control units (ECUs) that use various sensors to monitor engine performance and make adjustments to the fuel injection, ignition timing, and other engine parameters to optimize performance and fuel efficiency.
These adjustments are made in real-time, providing drivers with a smooth and efficient driving experience. ECUs are also used to diagnose engine problems and alert the driver when maintenance is required. This help prevents severe damage to the engine and saves the driver money on costly repairs. Overall, software-defined vehicles equipped with internal combustion engines provide drivers with greater control, performance, and efficiency while also helping to reduce emissions and improve the longevity of the engine.
ADAS sector is expected to grow at the highest CAGR during the projected period. ADAS technologies are designed to help drivers avoid accidents by providing warnings, alerts, and automated responses to potential hazards on the road. Some of the most common advanced driver assistance systems (ADAS) features include lane departure warnings, adaptive cruise control, automatic emergency braking, and blind-spot monitoring. Overall, the ADAS and safety segment of the software-defined vehicles market is expected to experience significant growth in the coming years as more automakers and consumers seek out advanced safety features to improve the driving experience and reduce the risk of accidents.
Body Control & Comfort Systems is the fastest-growing sector from 2023 to 2032. This segment encompasses all the systems that control various aspects of the vehicle's body and interior, including lighting, climate control, infotainment, and more. This growth is likely to be supported by ongoing advancements in software and technology, as well as increasing regulatory support for autonomous driving and other advanced vehicle features.
On the basis of vehicle type, the passenger car sector is anticipated to grow at the highest CAGR from 2023 to 2032. The growth of the segment is due to the cost-effective alternative being introduced, like natural ventilation as well as increasing passengers’ comfort. The car producers have increased recently, which is further anticipated to boost the growth of the passenger car industry. Along with this, the rising concern regarding fossil fuel emissions, energy security, as well as increasing competitiveness between sectors is anticipated to encourage the government to make investments and generate incentives in the automotive sector, thus expanding the market of the software-defined vehicle market.
On the other hand, the commercial vehicle sector is anticipated to grow at the fastest CAGR during the projected period. The expansion is due to the rising implementation of sports utility vehicles, mainly in emerging countries. The growth is also attributed due to development in the supply chain and logistics industries. Manufacturers of light industrial vehicles are moving toward an electric, sustainable, and clean world. Several OEMs are developing novel paradigms to transform conventional commercial vehicle base approaches.
The Level 3 sector is anticipated to grow at the highest CAGR from 2023 to 2032. In level 3, the vehicle is able to drive itself in certain situations, but the driver must be ready to take control when prompted. These are automated and are mainly used to avoid accidents.
Level 1 is anticipated to grow at the fastest CAGR during the projected period. This is also known as the driver assistance level; in this, the vehicle is able to assist with steering, braking, or accelerating, but the driver remains in control.
The North American region, which includes the United States and Canada, is expected to be a significant player in the software-defined vehicles market. The presence of major automotive manufacturers and technology companies in this region, along with the increasing demand for electric and autonomous vehicles, is expected to drive growth.
Europe is also expected to be a significant software-defined vehicle market player. The region has a strong automotive industry and is home to several major automotive manufacturers, making it a hub for innovation.
Segments Covered in the Report:
By Propulsion
By Application
By Vehicle Type
By Level of Autonomy
By Geography
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Software-Defined Vehicles Market
5.1. COVID-19 Landscape: Software-Defined Vehicles Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Software-Defined Vehicles Market, By Propulsion
8.1. Software-Defined Vehicles Market, by Propulsion, 2023-2032
8.1.1. ICE Vehicles
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Electric Vehicles
8.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Software-Defined Vehicles Market, By Application
9.1. Software-Defined Vehicles Market, by Application, 2023-2032
9.1.1. ADAS & Safety
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Connected Vehicle Services
9.1.2.1. Market Revenue and Forecast (2020-2032)
9.1.3. Autonomous Driving
9.1.3.1. Market Revenue and Forecast (2020-2032)
9.1.4. Body Control & Comfort System
9.1.4.1. Market Revenue and Forecast (2020-2032)
9.1.5. Powertrain System
9.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Software-Defined Vehicles Market, By Vehicle Type
10.1. Software-Defined Vehicles Market, by Vehicle Type, 2023-2032
10.1.1. Passenger Car
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. Commercial Vehicles
10.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Software-Defined Vehicles Market, By Level of Autonomy
11.1. Software-Defined Vehicles Market, by Level of Autonomy, 2023-2032
11.1.1. Level 1
11.1.1.1. Market Revenue and Forecast (2020-2032)
11.1.2. Level 2
11.1.2.1. Market Revenue and Forecast (2020-2032)
11.1.3. Level 3
11.1.3.1. Market Revenue and Forecast (2020-2032)
11.1.4. Level 4
11.1.4.1. Market Revenue and Forecast (2020-2032)
11.1.5. Level 5
11.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 12. Global Software-Defined Vehicles Market, Regional Estimates and Trend Forecast
12.1. North America
12.1.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.1.2. Market Revenue and Forecast, by Application (2020-2032)
12.1.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.1.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.1.5. U.S.
12.1.5.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.1.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.1.5.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.1.5.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.1.6. Rest of North America
12.1.6.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.1.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.1.6.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.1.6.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.2. Europe
12.2.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.2.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.2.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.2.5. UK
12.2.5.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.2.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.5.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.2.5.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.2.6. Germany
12.2.6.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.2.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.6.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.2.6.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.2.7. France
12.2.7.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.2.7.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.7.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.2.7.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.2.8. Rest of Europe
12.2.8.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.2.8.2. Market Revenue and Forecast, by Application (2020-2032)
12.2.8.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.2.8.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.3. APAC
12.3.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.3.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.3.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.3.5. India
12.3.5.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.3.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.5.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.3.5.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.3.6. China
12.3.6.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.3.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.6.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.3.6.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.3.7. Japan
12.3.7.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.3.7.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.7.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.3.7.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.3.8. Rest of APAC
12.3.8.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.3.8.2. Market Revenue and Forecast, by Application (2020-2032)
12.3.8.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.3.8.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.4. MEA
12.4.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.4.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.4.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.4.5. GCC
12.4.5.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.4.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.5.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.4.5.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.4.6. North Africa
12.4.6.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.4.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.6.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.4.6.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.4.7. South Africa
12.4.7.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.4.7.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.7.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.4.7.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.4.8. Rest of MEA
12.4.8.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.4.8.2. Market Revenue and Forecast, by Application (2020-2032)
12.4.8.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.4.8.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.5. Latin America
12.5.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.5.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.5.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.5.5. Brazil
12.5.5.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.5.5.2. Market Revenue and Forecast, by Application (2020-2032)
12.5.5.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.5.5.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
12.5.6. Rest of LATAM
12.5.6.1. Market Revenue and Forecast, by Propulsion (2020-2032)
12.5.6.2. Market Revenue and Forecast, by Application (2020-2032)
12.5.6.3. Market Revenue and Forecast, by Vehicle Type (2020-2032)
12.5.6.4. Market Revenue and Forecast, by Level of Autonomy (2020-2032)
Chapter 13. Company Profiles
13.1. Tesla, Inc.
13.1.1. Company Overview
13.1.2. Product Offerings
13.1.3. Financial Performance
13.1.4. Recent Initiatives
13.2. Toyota Motor Corporation
13.2.1. Company Overview
13.2.2. Product Offerings
13.2.3. Financial Performance
13.2.4. Recent Initiatives
13.3. Volkswagen Ag
13.3.1. Company Overview
13.3.2. Product Offerings
13.3.3. Financial Performance
13.3.4. Recent Initiatives
13.4. General Motors Company
13.4.1. Company Overview
13.4.2. Product Offerings
13.4.3. Financial Performance
13.4.4. Recent Initiatives
13.5. Stellantis NV
13.5.1. Company Overview
13.5.2. Product Offerings
13.5.3. Financial Performance
13.5.4. Recent Initiatives
13.6. BYD Company Limited
13.6.1. Company Overview
13.6.2. Product Offerings
13.6.3. Financial Performance
13.6.4. Recent Initiatives
13.7. Hyundai Motor Company
13.7.1. Company Overview
13.7.2. Product Offerings
13.7.3. Financial Performance
13.7.4. Recent Initiatives
13.8. Ford Motor Company
13.8.1. Company Overview
13.8.2. Product Offerings
13.8.3. Financial Performance
13.8.4. Recent Initiatives
13.9. Honda Motor Co., Ltd.
13.9.1. Company Overview
13.9.2. Product Offerings
13.9.3. Financial Performance
13.9.4. Recent Initiatives
13.10. Mercedes Benz Group AG
13.10.1. Company Overview
13.10.2. Product Offerings
13.10.3. Financial Performance
13.10.4. Recent Initiatives
Chapter 14. Research Methodology
14.1. Primary Research
14.2. Secondary Research
14.3. Assumptions
Chapter 15. Appendix
15.1. About Us
15.2. Glossary of Terms
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