Sensor fusion is the process of combining data from multiple sensors to reduce the uncertainty associated with task execution. It is a technology that combines sensor data obtained from various sources to produce less uncertain information than using those sources individually. These sensors include cameras, radar, LiDAR, time-of-flight (ToF), microphones, inertial measurement unit (IMU) sensors, and collaborative sensors. The implementation of stringent government regulations to include safety features in vehicles is expected to further impact the automotive sensor fusion market.
In addition, the growing trend of autonomous vehicles, integration of advanced technologies, and rise in demand for environmentally friendly vehicles are anticipated to drive the growth of the automotive sensor fusion market. Self-driving cars use a combination of forward-facing cameras and radar systems to collect and further process relevant information about road conditions. Sensor fusion is a building block in the development of semi-autonomous and fully autonomous vehicles designed to maintain lane position and adapt to traffic environments. Therefore, the rise in the development of sophisticated sensor fusion technologies to enable efficient semi-automated and fully automated driving is expected to drive the growth of the market.
An image sensor is an electronic device that converts an optical image into an electrical signal. It is used in digital cameras and imaging devices to convert the light received by the lens of the camera or imaging device into a digital image. Image sensors are used for sensing and providing information in the form of an image. These sensors convert light waves and sound waves into signals, which are then used for providing a pictorial representation of the environment in the form of an image. Image sensors are mainly used for the applications such as park assist, lane departure warning, collision avoidance system, and blind spot detection.
Image sensors for automotive applications are important feature for vehicle safety. These sensors have witnessed impressive growth in advanced driver assistance systems. Image sensors are used in various applications such as park assist, lane departure warning, and collision avoidance systems for projecting the outside picture to the driver. The development of NCAP car ratings in developed nations, such as Japan, U. S., and European countries has led to the remarkable commercial opportunity for image sensors. Surge in development of image sensors to enhance driver monitoring system in autonomous vehicles is expected to drive the growth of the segment in the market. For instance, in May 2022, STMicroelectronics introduced advanced global shutter image sensor for affordable and reliable driver monitoring safety systems. Sensor fusion combines input from image sensors and other sensors to create a more complete, accurate, and reliable picture of the environment, especially in dynamic setting. Therefore, increase in adoption of image sensors in vehicles is expected to boost the growth of the segment in the market.
The automotive sensor fusion market is segmented on the basis of technology, vehicle type, propulsion type, and region. By technology, it is fragmented into radar sensors, image sensors, IMU, and others. On the basis of vehicle type, it is classified into passenger car and commercial vehicle. By propulsion type, it is categorized into ICE, BEV, and HEV. By region, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Some major companies operating in the market include Aptiv, Elmos Semiconductor SE, Infineon Technologies AG, Mobileye, NVIDIA Corporation, NXP Semiconductors, Robert Bosch GmbH, STMicroelectronics, TDK Corporation, TE Connectivity, Texas Instruments, and ZF Friedrichshafen AG.
In addition, the growing trend of autonomous vehicles, integration of advanced technologies, and rise in demand for environmentally friendly vehicles are anticipated to drive the growth of the automotive sensor fusion market. Self-driving cars use a combination of forward-facing cameras and radar systems to collect and further process relevant information about road conditions. Sensor fusion is a building block in the development of semi-autonomous and fully autonomous vehicles designed to maintain lane position and adapt to traffic environments. Therefore, the rise in the development of sophisticated sensor fusion technologies to enable efficient semi-automated and fully automated driving is expected to drive the growth of the market.
An image sensor is an electronic device that converts an optical image into an electrical signal. It is used in digital cameras and imaging devices to convert the light received by the lens of the camera or imaging device into a digital image. Image sensors are used for sensing and providing information in the form of an image. These sensors convert light waves and sound waves into signals, which are then used for providing a pictorial representation of the environment in the form of an image. Image sensors are mainly used for the applications such as park assist, lane departure warning, collision avoidance system, and blind spot detection.
Image sensors for automotive applications are important feature for vehicle safety. These sensors have witnessed impressive growth in advanced driver assistance systems. Image sensors are used in various applications such as park assist, lane departure warning, and collision avoidance systems for projecting the outside picture to the driver. The development of NCAP car ratings in developed nations, such as Japan, U. S., and European countries has led to the remarkable commercial opportunity for image sensors. Surge in development of image sensors to enhance driver monitoring system in autonomous vehicles is expected to drive the growth of the segment in the market. For instance, in May 2022, STMicroelectronics introduced advanced global shutter image sensor for affordable and reliable driver monitoring safety systems. Sensor fusion combines input from image sensors and other sensors to create a more complete, accurate, and reliable picture of the environment, especially in dynamic setting. Therefore, increase in adoption of image sensors in vehicles is expected to boost the growth of the segment in the market.
The automotive sensor fusion market is segmented on the basis of technology, vehicle type, propulsion type, and region. By technology, it is fragmented into radar sensors, image sensors, IMU, and others. On the basis of vehicle type, it is classified into passenger car and commercial vehicle. By propulsion type, it is categorized into ICE, BEV, and HEV. By region, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Some major companies operating in the market include Aptiv, Elmos Semiconductor SE, Infineon Technologies AG, Mobileye, NVIDIA Corporation, NXP Semiconductors, Robert Bosch GmbH, STMicroelectronics, TDK Corporation, TE Connectivity, Texas Instruments, and ZF Friedrichshafen AG.
KEY BENEFITS FOR STAKEHOLDERS
- This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the automotive sensor fusion market analysis from 2021 to 2031 to identify the prevailing automotive sensor fusion market opportunities.
- The market research is offered along with information related to key drivers, restraints, and opportunities.
- Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders make profit-oriented business decisions and strengthen their supplier-buyer network.
- In-depth analysis of the automotive sensor fusion market segmentation assists to determine the prevailing market opportunities.
- Major countries in each region are mapped according to their revenue contribution to the global market.
- Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
- The report includes the analysis of the regional as well as global automotive sensor fusion market trends, key players, market segments, application areas, and market growth strategies.
Key Market Segments
By Technology
- Radar Sensors
- Image Sensors
- IMU
- Others
By Vehicle Type
- Passenger car
- Light Commercial vehicle
- Heavy Commercial vehicle
By Propulsion Type
- ICE
- BEV
- HEV
By Region
- North America
- U. S.
- Canada
- Mexico
- Europe
- Germany
- France
- UK
- Italy
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- South Korea
- Rest of Asia-Pacific
- LAMEA
- Latin America
- Middle East
- Africa
Key Market Players
- Robert Bosch GmbH
- TE Connectivity
- Texas Instruments Inc.
- ZF Friedrichshafen AG
- NXP Semiconductors
- Infineon Technologies AG
- NVIDIA Corporation
- TDK Corporation
- Aptiv
- Elmos Semiconductor SE
- STMicroelectronics
- Mobileye
Table of Contents
CHAPTER 1: INTRODUCTION1.1. Report description
1.2. Key market segments
1.3. Key benefits to the stakeholders
1.4. Research Methodology
1.4.1. Secondary research
1.4.2. Primary research
1.4.3. Analyst tools and models
CHAPTER 2: EXECUTIVE SUMMARY
2.1. Key findings of the study
2.2. CXO Perspective
CHAPTER 3: MARKET OVERVIEW
3.1. Market definition and scope
3.2. Key findings
3.2.1. Top investment pockets
3.3. Porter’s five forces analysis
3.4. Top player positioning
3.5. Market dynamics
3.5.1. Drivers
3.5.2. Restraints
3.5.3. Opportunities
3.6. COVID-19 Impact Analysis on the market
CHAPTER 4: AUTOMOTIVE SENSOR FUSION MARKET, BY TECHNOLOGY
4.1 Overview
4.1.1 Market size and forecast
4.2 Radar Sensors
4.2.1 Key market trends, growth factors and opportunities
4.2.2 Market size and forecast, by region
4.2.3 Market share analysis by country
4.3 Image Sensors
4.3.1 Key market trends, growth factors and opportunities
4.3.2 Market size and forecast, by region
4.3.3 Market share analysis by country
4.4 IMU
4.4.1 Key market trends, growth factors and opportunities
4.4.2 Market size and forecast, by region
4.4.3 Market share analysis by country
4.5 Others
4.5.1 Key market trends, growth factors and opportunities
4.5.2 Market size and forecast, by region
4.5.3 Market share analysis by country
CHAPTER 5: AUTOMOTIVE SENSOR FUSION MARKET, BY VEHICLE TYPE
5.1 Overview
5.1.1 Market size and forecast
5.2 Passenger car
5.2.1 Key market trends, growth factors and opportunities
5.2.2 Market size and forecast, by region
5.2.3 Market share analysis by country
5.3 Light Commercial vehicle
5.3.1 Key market trends, growth factors and opportunities
5.3.2 Market size and forecast, by region
5.3.3 Market share analysis by country
5.4 Heavy Commercial vehicle
5.4.1 Key market trends, growth factors and opportunities
5.4.2 Market size and forecast, by region
5.4.3 Market share analysis by country
CHAPTER 6: AUTOMOTIVE SENSOR FUSION MARKET, BY PROPULSION TYPE
6.1 Overview
6.1.1 Market size and forecast
6.2 ICE
6.2.1 Key market trends, growth factors and opportunities
6.2.2 Market size and forecast, by region
6.2.3 Market share analysis by country
6.3 BEV
6.3.1 Key market trends, growth factors and opportunities
6.3.2 Market size and forecast, by region
6.3.3 Market share analysis by country
6.4 HEV
6.4.1 Key market trends, growth factors and opportunities
6.4.2 Market size and forecast, by region
6.4.3 Market share analysis by country
CHAPTER 7: AUTOMOTIVE SENSOR FUSION MARKET, BY REGION
7.1 Overview
7.1.1 Market size and forecast
7.2 North America
7.2.1 Key trends and opportunities
7.2.2 North America Market size and forecast, by Technology
7.2.3 North America Market size and forecast, by Vehicle Type
7.2.4 North America Market size and forecast, by Propulsion Type
7.2.5 North America Market size and forecast, by country
7.2.5.1 U. S.
7.2.5.1.1 Key market trends, growth factors and opportunities
7.2.5.1.2 Market size and forecast, by Technology
7.2.5.1.3 Market size and forecast, by Vehicle Type
7.2.5.1.4 Market size and forecast, by Propulsion Type
7.2.5.2 Canada
7.2.5.2.1 Key market trends, growth factors and opportunities
7.2.5.2.2 Market size and forecast, by Technology
7.2.5.2.3 Market size and forecast, by Vehicle Type
7.2.5.2.4 Market size and forecast, by Propulsion Type
7.2.5.3 Mexico
7.2.5.3.1 Key market trends, growth factors and opportunities
7.2.5.3.2 Market size and forecast, by Technology
7.2.5.3.3 Market size and forecast, by Vehicle Type
7.2.5.3.4 Market size and forecast, by Propulsion Type
7.3 Europe
7.3.1 Key trends and opportunities
7.3.2 Europe Market size and forecast, by Technology
7.3.3 Europe Market size and forecast, by Vehicle Type
7.3.4 Europe Market size and forecast, by Propulsion Type
7.3.5 Europe Market size and forecast, by country
7.3.5.1 Germany
7.3.5.1.1 Key market trends, growth factors and opportunities
7.3.5.1.2 Market size and forecast, by Technology
7.3.5.1.3 Market size and forecast, by Vehicle Type
7.3.5.1.4 Market size and forecast, by Propulsion Type
7.3.5.2 France
7.3.5.2.1 Key market trends, growth factors and opportunities
7.3.5.2.2 Market size and forecast, by Technology
7.3.5.2.3 Market size and forecast, by Vehicle Type
7.3.5.2.4 Market size and forecast, by Propulsion Type
7.3.5.3 UK
7.3.5.3.1 Key market trends, growth factors and opportunities
7.3.5.3.2 Market size and forecast, by Technology
7.3.5.3.3 Market size and forecast, by Vehicle Type
7.3.5.3.4 Market size and forecast, by Propulsion Type
7.3.5.4 Italy
7.3.5.4.1 Key market trends, growth factors and opportunities
7.3.5.4.2 Market size and forecast, by Technology
7.3.5.4.3 Market size and forecast, by Vehicle Type
7.3.5.4.4 Market size and forecast, by Propulsion Type
7.3.5.5 Rest of Europe
7.3.5.5.1 Key market trends, growth factors and opportunities
7.3.5.5.2 Market size and forecast, by Technology
7.3.5.5.3 Market size and forecast, by Vehicle Type
7.3.5.5.4 Market size and forecast, by Propulsion Type
7.4 Asia-Pacific
7.4.1 Key trends and opportunities
7.4.2 Asia-Pacific Market size and forecast, by Technology
7.4.3 Asia-Pacific Market size and forecast, by Vehicle Type
7.4.4 Asia-Pacific Market size and forecast, by Propulsion Type
7.4.5 Asia-Pacific Market size and forecast, by country
7.4.5.1 China
7.4.5.1.1 Key market trends, growth factors and opportunities
7.4.5.1.2 Market size and forecast, by Technology
7.4.5.1.3 Market size and forecast, by Vehicle Type
7.4.5.1.4 Market size and forecast, by Propulsion Type
7.4.5.2 Japan
7.4.5.2.1 Key market trends, growth factors and opportunities
7.4.5.2.2 Market size and forecast, by Technology
7.4.5.2.3 Market size and forecast, by Vehicle Type
7.4.5.2.4 Market size and forecast, by Propulsion Type
7.4.5.3 India
7.4.5.3.1 Key market trends, growth factors and opportunities
7.4.5.3.2 Market size and forecast, by Technology
7.4.5.3.3 Market size and forecast, by Vehicle Type
7.4.5.3.4 Market size and forecast, by Propulsion Type
7.4.5.4 South Korea
7.4.5.4.1 Key market trends, growth factors and opportunities
7.4.5.4.2 Market size and forecast, by Technology
7.4.5.4.3 Market size and forecast, by Vehicle Type
7.4.5.4.4 Market size and forecast, by Propulsion Type
7.4.5.5 Rest of Asia-Pacific
7.4.5.5.1 Key market trends, growth factors and opportunities
7.4.5.5.2 Market size and forecast, by Technology
7.4.5.5.3 Market size and forecast, by Vehicle Type
7.4.5.5.4 Market size and forecast, by Propulsion Type
7.5 LAMEA
7.5.1 Key trends and opportunities
7.5.2 LAMEA Market size and forecast, by Technology
7.5.3 LAMEA Market size and forecast, by Vehicle Type
7.5.4 LAMEA Market size and forecast, by Propulsion Type
7.5.5 LAMEA Market size and forecast, by country
7.5.5.1 Latin America
7.5.5.1.1 Key market trends, growth factors and opportunities
7.5.5.1.2 Market size and forecast, by Technology
7.5.5.1.3 Market size and forecast, by Vehicle Type
7.5.5.1.4 Market size and forecast, by Propulsion Type
7.5.5.2 Middle East
7.5.5.2.1 Key market trends, growth factors and opportunities
7.5.5.2.2 Market size and forecast, by Technology
7.5.5.2.3 Market size and forecast, by Vehicle Type
7.5.5.2.4 Market size and forecast, by Propulsion Type
7.5.5.3 Africa
7.5.5.3.1 Key market trends, growth factors and opportunities
7.5.5.3.2 Market size and forecast, by Technology
7.5.5.3.3 Market size and forecast, by Vehicle Type
7.5.5.3.4 Market size and forecast, by Propulsion Type
CHAPTER 8: COMPANY LANDSCAPE
8.1. Introduction
8.2. Top winning strategies
8.3. Product Mapping of Top 10 Players
8.4. Competitive Dashboard
8.5. Competitive Heatmap
8.6. Key developments
CHAPTER 9: COMPANY PROFILES
9.1 Aptiv
9.1.1 Company overview
9.1.2 Company snapshot
9.1.3 Operating business segments
9.1.4 Product portfolio
9.1.5 Business performance
9.1.6 Key strategic moves and developments
9.2 Elmos Semiconductor SE
9.2.1 Company overview
9.2.2 Company snapshot
9.2.3 Operating business segments
9.2.4 Product portfolio
9.2.5 Business performance
9.2.6 Key strategic moves and developments
9.3 Infineon Technologies AG
9.3.1 Company overview
9.3.2 Company snapshot
9.3.3 Operating business segments
9.3.4 Product portfolio
9.3.5 Business performance
9.3.6 Key strategic moves and developments
9.4 Mobileye
9.4.1 Company overview
9.4.2 Company snapshot
9.4.3 Operating business segments
9.4.4 Product portfolio
9.4.5 Business performance
9.4.6 Key strategic moves and developments
9.5 NVIDIA Corporation
9.5.1 Company overview
9.5.2 Company snapshot
9.5.3 Operating business segments
9.5.4 Product portfolio
9.5.5 Business performance
9.5.6 Key strategic moves and developments
9.6 NXP Semiconductors
9.6.1 Company overview
9.6.2 Company snapshot
9.6.3 Operating business segments
9.6.4 Product portfolio
9.6.5 Business performance
9.6.6 Key strategic moves and developments
9.7 Robert Bosch GmbH
9.7.1 Company overview
9.7.2 Company snapshot
9.7.3 Operating business segments
9.7.4 Product portfolio
9.7.5 Business performance
9.7.6 Key strategic moves and developments
9.8 STMicroelectronics
9.8.1 Company overview
9.8.2 Company snapshot
9.8.3 Operating business segments
9.8.4 Product portfolio
9.8.5 Business performance
9.8.6 Key strategic moves and developments
9.9 TDK Corporation
9.9.1 Company overview
9.9.2 Company snapshot
9.9.3 Operating business segments
9.9.4 Product portfolio
9.9.5 Business performance
9.9.6 Key strategic moves and developments
9.10 TE Connectivity
9.10.1 Company overview
9.10.2 Company snapshot
9.10.3 Operating business segments
9.10.4 Product portfolio
9.10.5 Business performance
9.10.6 Key strategic moves and developments
9.11 Texas Instruments Inc.
9.11.1 Company overview
9.11.2 Company snapshot
9.11.3 Operating business segments
9.11.4 Product portfolio
9.11.5 Business performance
9.11.6 Key strategic moves and developments
9.12 ZF Friedrichshafen AG
9.12.1 Company overview
9.12.2 Company snapshot
9.12.3 Operating business segments
9.12.4 Product portfolio
9.12.5 Business performance
9.12.6 Key strategic moves and developments
Executive Summary
The Automotive Sensor Fusion Market is likely to experience a significant growth rate of 5.6% from 2022-2031 owing to increase in market demand from automotive sector.The method of combining data from RADAR, LiDAR, cameras, and ultrasonic sensors to evaluate ambient conditions for detection confidence is known as sensor fusion. Each sensor cannot function independently and provide all the data required for an autonomous car to operate in the safest possible manner. Autonomous driving systems can profit from the strengths of each individual sensor while balancing out the aggregate advantages of using a variety of them. Sensor fusion data is processed by autonomous cars using preprogrammed algorithms. This enables autonomous cars to make decisions and choose the appropriate course of action.
Key factors driving the growth of the automotive sensor fusion market include stringent safety rules and regulations, technical benefits offered by sensor fusion, increase in the adoption of safety features such as advanced driving assistance (ADAS). Advanced driver assistance system provides various advantages such as a reduction in loss of property & life, a decrease in the rate of accidents, and others. ADAS consists of safety functions that are designed to improve pedestrian and passenger safety by minimizing both motor vehicle accidents and severity. The deployment of ADAS in vehicles to enhance comfort and ensure safety on road is anticipated to be one of the major trends being witnessed in the automotive industry. The rise in the need for safer driving conditions increases the demand for assistive driving systems among customers, which in turn propels the growth of the automotive sensor fusion market.
The market also offers growth opportunities to the key players in the market. An autonomous vehicle that can drive itself in 'autopilot' mode from a starting point to a given destination or able to perform necessary operations without any human intervention using various in-vehicle technologies such as adaptive cruise control, anti-lock braking systems (brake by wire), active steering (steer by wire), lasers, GPS navigation technology, and radar. These systems which make vehicles autonomous are integrated with sensors such as RADAR, LiDAR, ultrasonic sensors, and cameras, based on these sensors located throughout the vehicle, autonomous vehicles develop and maintain a map of their surroundings. the rising investment in the development of autonomous vehicles and related systems by vehicle manufacturers such as Ford, BMW, General Motors, Volvo, and others is anticipated to create demand for sensor fusion. For instance, in April 2019, BMW entered into a partnership with DXC Technology, a global end-to-end IT services company, for the development of autonomous driving research and development. In addition, growing research and development of sensor fusion systems for autonomous vehicles are expected to boost the growth of the automotive sensor fusion market during the forecast period.
The automotive sensor fusion market is segmented into technology, vehicle type, propulsion type, and region. On the basis of technology, the market is categorized into radar sensors, image sensors, IMU, and others. On the basis of vehicle type, it is categorized into passenger car, light commercial vehicle, and heavy commercial vehicle. On the basis of propulsion type, it is fragmented into ICE, BEV, and HEV. Region wise, it is analyzed across North America (the U.S., Canada, and Mexico), Europe (Germany, France, UK, Italy, and rest of Europe), Asia-Pacific (China, Japan, India, South Korea, and rest of Asia-Pacific), and LAMEA (Latin America, Middle East, and Africa).
The key players profiled in the study include Aptiv, Elmos Semiconductor SE, Infineon Technologies AG, Mobileye, NVIDIA Corporation, NXP Semiconductors, Robert Bosch GmbH, STMicroelectronics, TDK Corporation, TE Connectivity, Texas Instruments, and ZF Friedrichshafen AG. The players in the market have been actively engaged in the adoption various strategies such as agreement, contract, collaboration, expansion, product development, and partnership to remain competitive and gain advantage over the competitors in the market. For instance, in November 2021, NVIDIA Corporation entered into a collaboration with Luminar Technologies for developing the platform with the aim of providing it to car manufacturers to install in their consumer vehicles. The in-car solution is set to include sensors and software tools necessary for self-driving and intelligent cockpit capabilities. .
Key Market Insights
By technology, the IMU segment was the highest revenue contributor to the market, and is estimated to reach $2,232.6 million by 2031, with a CAGR of 20.3%. However, the image sensors segment is estimated to be the fastest growing segment with the CAGR of 22.3% during the forecast period.By vehicle type, the passenger car segment dominated the global market, and is estimated to reach $5,372.2 million by 2031, with a CAGR of 21.5%.
Based on propulsion type, the ICE segment was the highest revenue contributor to the market, with $871.7 million in 2021, and is estimated to reach $5,076.2 million by 2031, with a CAGR of 20.2%.
Based on region, North America was the highest revenue contributor, accounting for $384.8 million in 2021, and is estimated to reach $2,221.0 million by 2031, with a CAGR of 20.1%.
Companies Mentioned
- Robert Bosch GmbH
- Te Connectivity
- Texas Instruments Inc.
- Zf Friedrichshafen AG
- Nxp Semiconductors
- Infineon Technologies AG
- Nvidia Corporation
- Tdk Corporation
- Aptiv
- Elmos Semiconductor SE
- Stmicroelectronics
- Mobileye
Methodology
The analyst offers exhaustive research and analysis based on a wide variety of factual inputs, which largely include interviews with industry participants, reliable statistics, and regional intelligence. The in-house industry experts play an instrumental role in designing analytic tools and models, tailored to the requirements of a particular industry segment. The primary research efforts include reaching out participants through mail, tele-conversations, referrals, professional networks, and face-to-face interactions.
They are also in professional corporate relations with various companies that allow them greater flexibility for reaching out to industry participants and commentators for interviews and discussions.
They also refer to a broad array of industry sources for their secondary research, which typically include; however, not limited to:
- Company SEC filings, annual reports, company websites, broker & financial reports, and investor presentations for competitive scenario and shape of the industry
- Scientific and technical writings for product information and related preemptions
- Regional government and statistical databases for macro analysis
- Authentic news articles and other related releases for market evaluation
- Internal and external proprietary databases, key market indicators, and relevant press releases for market estimates and forecast
Furthermore, the accuracy of the data will be analyzed and validated by conducting additional primaries with various industry experts and KOLs. They also provide robust post-sales support to clients.
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