The Global Automotive Sensor Fusion Market size is expected to reach $7.3 billion by 2028, rising at a market growth of 22.8% CAGR during the forecast period.
The ability to merge information from different radars, lidars, and cameras to produce a single model or image of the space around a vehicle is referred to as sensor fusion. The model created as a result of balancing the strengths of the various sensors is more accurate. Vehicle systems can then employ more sophisticated behaviors using the data gathered through sensor fusion. There are benefits and drawbacks to each sensor type, or 'modality,' separately.
Even in adverse weather, radars are quite effective at calculating distance and speed, but they are unable to 'see' the colour of a stoplight or read street signs. Cameras are excellent at interpreting signs or categorizing objects like humans, bicycles, and other vehicles. But they are quickly dazzled by debris, the light, the rain, the snow, or the night. Lidars are capable of precise object detection, but they lack the price or range of cameras or radar.
Utilizing software algorithms, sensor fusion combines the data from all of these different types of sensors to produce the most complete and accurate environmental model possible. Through a process called internal and external sensor fusion, it may also correlate data obtained from within the cabin. The information from numerous sensors of the same sort, such as radar, might also be combined by a vehicle via sensor fusion.
By taking advantage of slightly overlapping areas of view, this enhances perception. More than one sensor will pick up things simultaneously when more than one radar scans the area around a vehicle. The detection likelihood and reliability of things nearby the vehicle can be increased by fusing or overlapping the detections from those various sensors when interpreted by 360° perception software, which also produces a more accurate and trustworthy picture of the environment.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include NVIDIA Corporation, NXP Semiconductors N.V., Robert Bosch GmbH, TE Connectivity Ltd., Infineon Technologies AG, ZF Friedrichshafen AG, TDK Corporation, STMicroelectronics N.V., Aptiv PLC, and Texas Instruments, Inc.
The ability to merge information from different radars, lidars, and cameras to produce a single model or image of the space around a vehicle is referred to as sensor fusion. The model created as a result of balancing the strengths of the various sensors is more accurate. Vehicle systems can then employ more sophisticated behaviors using the data gathered through sensor fusion. There are benefits and drawbacks to each sensor type, or 'modality,' separately.
Even in adverse weather, radars are quite effective at calculating distance and speed, but they are unable to 'see' the colour of a stoplight or read street signs. Cameras are excellent at interpreting signs or categorizing objects like humans, bicycles, and other vehicles. But they are quickly dazzled by debris, the light, the rain, the snow, or the night. Lidars are capable of precise object detection, but they lack the price or range of cameras or radar.
Utilizing software algorithms, sensor fusion combines the data from all of these different types of sensors to produce the most complete and accurate environmental model possible. Through a process called internal and external sensor fusion, it may also correlate data obtained from within the cabin. The information from numerous sensors of the same sort, such as radar, might also be combined by a vehicle via sensor fusion.
By taking advantage of slightly overlapping areas of view, this enhances perception. More than one sensor will pick up things simultaneously when more than one radar scans the area around a vehicle. The detection likelihood and reliability of things nearby the vehicle can be increased by fusing or overlapping the detections from those various sensors when interpreted by 360° perception software, which also produces a more accurate and trustworthy picture of the environment.
COVID-19 Impact Analysis
Due to the adoption of lockdown following the COVID-19 pandemic, which decreased demand for automotive sensor fusion, the COVID-19 pandemic had a detrimental impact on the expansion of the automotive sensor fusion market. Import and export restrictions caused a disruption in the supply chain. Both labour and raw materials were in short supply for manufacturers. A fall in working capital, a reduction in new car sales, a shutdown of production facilities, and a limited supply of auto parts. Since the manufacturing of automobiles is reliant on the sensor fusion industry, the outbreak is anticipated to have an effect on this business. However, because the advanced driver assistance system (ADAS) is so widely used in cars, it is anticipated that there will be a rise in the need for automotive sensors.Market Growth Factors
Government safety regulations that are strict
In order to reduce accidents and boost traffic safety, automakers have hastened the implementation of technology. Additionally, the government takes action to reduce traffic fatalities by mandating the inclusion of these technologies in all new cars. The government is being urged to enact severe restrictions relating to safety measures in vehicles by the sharp rise in traffic accidents. The requirements include installing an advanced emergency braking system, logging accidents, installing seat belt sensors that have passed crash tests, reversing sensors, and speed assistance in vehicles. The use of sensors like RADAR, LiDAR, cameras, and others allows advanced safety features like accident avoidance and mitigation, speeding warning and alerts, and adaptive cruise control system to detect and identify objects as well as track their movement The benefits of automotive sensor fusion are predicted to support market growth during the projection period.Technical benefits offered by automotive sensor fusion
Sensor fusion is the technique of combining data from various sensors using software algorithms to produce an equally thorough and accurate picture of the environment. In an automated driving system, sensors are essential for the perception of the environment around the car, and the use and functionality of numerous integrated sensors directly affect the viability and safety of automated driving vehicles. One of the key processes in automated driving applications is sensor fusion, which combines data from various sensors to lower uncertainty compared to using each sensor separately. The benefits of automotive sensor fusion are predicted to support market growth during the projection period.Market Restraining Factors
A malfunctioning electronic sensor system in the vehicle
Sensor data is gathered by autonomous vehicle systems, which then compute driving choices and communicate control signals to the vehicles. To combine the sensor outputs and give a more accurate image of the environment while reducing the uncertainties offered by sensor outputs, these systems are combined with multi-sensor fusion (MSF). Multi-sensor fusion (MSF) lacks knowledge of which sensors provide the most accurate data and how to appropriately combine the data the sensors produce; hence it is unable to completely remove uncertainties. It is projected that this aspect will limit market expansion.Technology Outlook
On the basis of technology, the automotive sensor fusion market is segmented into radar sensor, IMU, image sensor, and others. In 2021, the IMU segment held the highest revenue share in the automotive sensor fusion market. An IMU is a sensor generally consisting of an accelerometer, gyroscope, and often a magnetometer. A device can get a complete picture of its orientation and motion state by looking at data from these sensors. The information provided by the sensors is used to hold a drone’s balance, enhance the heading of a home robot vacuum cleaner, change the orientation of a smartphone screen, and other motion-related applications.Vehicle Type Outlook
By vehicle type, the automotive sensor fusion market is classified into passenger car, light commercial vehicle, and heavy commercial vehicle. The heavy commercial vehicle segment garnered a substantial revenue share in the automotive sensor fusion market in 2021. Sensor fusion does not penetrate heavy commercial vehicles. The vehicle height, longer range, and distance do, however, necessitate more cameras and radar for sensor fusion. Due to fleet managers' growing desire to transition to cutting-edge safety technology, trucks are anticipated to embrace sensor fusion technology before buses.Propulsion Type Outlook
Based on propulsion type, the automotive sensor fusion market is divided into ICE, BEV, and HEV. The ICE segment witnessed the largest revenue share in the automotive sensor fusion market in 2021. A starter motor that will start the engine is installed in almost all cars. The starter battery feeds the alternator. The alternator, which the engine turns, recharges the battery. The electricity produced is used to power all auxiliary operations, including spark plugs, lights, and fans, as well as to recharge the starter battery. Alternator load adjustments may be possible in more sophisticated automobiles depending on the situation.Regional Outlook
Region wise, the automotive sensor fusion market is analyzed across North America, Europe, Asia, and LAMEA region. The North America region projected a prominent revenue share in the automotive sensor fusion market in 2021. The region's automotive sensor fusion market is expanding as a result of the growing use of advanced driver assistance systems (ADAS) and the development of autonomous vehicle technologies in commercial and passenger cars. The development of autonomous and semi-autonomous vehicles has been facilitated by strict governmental rules aimed at enhancing road safety. As a result, the market for automotive sensor fusion is anticipated to benefit greatly from the spike in the use of autonomous vehicles.Automotive Sensor Fusion Market Competition Analysis
The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Texas Instruments, Inc. and NVIDIA Corporation are the forerunners in the Automotive Sensor Fusion Market. Companies such as Infineon Technologies AG, NXP Semiconductors N.V., and Robert Bosch GmbH are some of the key innovators in Automotive Sensor Fusion Market.The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include NVIDIA Corporation, NXP Semiconductors N.V., Robert Bosch GmbH, TE Connectivity Ltd., Infineon Technologies AG, ZF Friedrichshafen AG, TDK Corporation, STMicroelectronics N.V., Aptiv PLC, and Texas Instruments, Inc.
Strategies deployed in Automotive Sensor Fusion Market
Partnerships, Collaborations and Agreements:
- Jan-2023: NXP Semiconductors collaborated with VinFast, a leading Vietnamese electric car manufacturer. In this collaboration, both companies enable the early development period of the latest VinFast automotive projects and leveraged NXP’s suite of system solutions for advanced applications
- Nov-2022: Infineon Technologies AG teamed up with REE Automobile Ltd, an Israel-based technology company. Through this Collaboration, Infineon Technologies AG would aim to promote sustainable mobility
- May-2022: Bosch Sensortec GmbH came into collaboration with Qeexo, developer of the Qeexo AutoML. Under this collaboration, Qeexo's AutoML, an automated machine learning (ML) platform, would be deployed on Arduino Nicla Sense ME with Bosch BHI260AP and BME688 sensors. Moreover, this would allow application developers to generate and deploy machine learning algorithms on Bosch's AI-integrated sensors
- Oct-2021: Infineon Technologies collaborated with TTTech Auto, a company engaged in the engineering and development of safety-critical software. In this collaboration, both companies developed critical components for a fail-operational electronic architecture planned for highly automated driving at SAE Levels 3 and 4
- Jun-2021: STMicroelectronics collaborated with Eyeris, a company engaged in vision-based Artificial Intelligence (AI) software. This collaboration focuses on broadening ST’s Global-Shutter sensor to in-cabin sensing applications with Eyeris' developed suite of Deep Neural Networks for a complete visuospatial understanding of the complete vehicle interior
- May-2021: ZF teamed up with Toyota Motor corp., a Japanese multinational automotive manufacturer, and Mobileye, an Intel company. With this collaboration, companies would innovate advanced driver-assistance systems (ADAS) that would be used in various vehicle platforms
- Feb-2021: NXP Semiconductors collaborated with Airbiquity®, Cloudera, Teraki™, and Wind River to announce The Fusion Project, an automotive industry collaboration to deal in the streamlined data lifecycle platform to make developments in intelligent connected vehicles. The pre-integrated hardware and software solution would consolidate advanced technologies from major companies, enabling automakers to gather, analyze and manage connected vehicle data for making advancement, and deployment in features
- Jan-2021: NXP Semiconductors unveiled BlueBox 3.0, an extended version of NXP’s flagship safe Automotive High-Performance Compute (AHPC) development platform. Consolidating centralized compute module, safely integrated high-performance NXP processors, expanded I/O connectivity and extensions with Kalray’s MPPA processor-based PCIe cards would allow in the enhancement heterogeneously; BlueBox 3.0 would enable designers to boost system development speed time and cycles to market
Product Launches and Product Expansions:
- Nov-2022: ST launched LSM6DSV16X, the 6-axis inertial measurement unit (IMU) entrenching ST’s Sensor Fusion Low Power (SFLP) technology, adaptive-self-configuration (ASC), and Artificial Intelligence (AI) for better power management
- Nov-2022: Infineon Technologies AG launched the XENSIV™ TLE4971 series to its current sensor offerings for automotive applications. The products provide accurate magnetic current sensing based on owned temperature and stress compensation, without the negative effects of magnetic cores caused by saturation or hysteresis effects
- Oct-2022: XP Semiconductors N.V. unveils OrangeBox, a platform to enable automotive engineers to accommodate wired and wireless information and security against safety susceptibilities during a rising automated vehicle design evolution. The product integrates current and developing external wireless interfaces into a single connectivity domain controller, which would connect to the secure vehicle gateway through NXP’s high-speed Ethernet
- Jun-2022: Infineon Technologies AG released Smart Alarm System (SAS), the technology platform that performs a very low-power operation and high accuracy using sensor fusion based on artificial intelligence/machine learning (AI/ML). Additionally, the company would allow a different approach to bring AI/ML abilities to cost-efficient battery-powered home security sensor systems
- Mar-2022: NVIDIA unveiled NVIDIA DRIVE Orin an autonomous vehicle computer, showcased new automakers assuming the NVIDIA DRIVE platform. NVIDIA DRIVE Orin enable very successful with companies making this future and is operating as the ideal AV and AI engine for the new generation of shuttles, robot axis, EVs, and trucks
- Sep-2021: ZF announced the launch of mid-range radar, a solution that adds a fourth elevation measurement angle enabling the production of an advanced 3D image of the traffic solution with speed information. This launch would support ADAS safety functions and improve the available ZF assist semi-automated system on the Dongfeng Aeolus Yixuan Max across China
- Jan-2021: TDK Corporation announced the launch of InvenSense ICM-40627 and ICM-42688-V high-performance MEMS motion tracking solutions to serve consumers. ICM-40627 is a high-precision ultra-low-power 6-axis MEMS MotionTracking™ device that would integrate a 3-axis gyroscope and a 3-axis accelerometer in a 2.5mm x 3mm x 0.9mm package. With this launch, TDK extended the portfolio of SmartMotion™ sensor solutions to offer services to a wide range of consumers and IOT applications
- Jan-2021: TDK Corp. launched various sensor, laser, and microphone products. Out of all, the most advanced products were TCE-11101 MEMS-based carbon dioxide (CO2) gas sensor platform, the InWheelSense energy harvesting and sensing module, and an ultra-small, full-color laser module. TDK produced InvenSense TCE-11101, a miniaturized, ultra-low-power MEMS gas sensor platform that would directly detect CO2 in the home, automotive, IoT, and health-care, as well as in other applications
- Jan-2021: Aptiv PLC launched Level 1-3 capable ADAS platform, a next-generation advanced driver-assistance system. The launch would enhance comfort, vehicle safety, and convenience. The product would span all vehicle segments and manage software complexities and support features ranging from entry-level safety compliance to developed highway pilot and parking assist
Acquisitions and Mergers:
- Dec-2022: Aptiv PLC acquired Wind River, a leader in providing software for the intelligent edge. Under this acquisition, Aptive would offer notable value to its customers through the complementary offerings of both companies
- Apr-2022: Robert Bosch completed the acquisition of Five, a leading UK startup in the field of automated driving. Through this acquisition, Robert Bosch would work in the area of software development to make automated driving safe. Moreover, with this acquisition Bosch would deliver European-made technology to customers
Scope of the Study
Market Segments Covered in the Report:
By Propulsion Type
- ICE
- BEV
- HEV
By Vehicle Type
- Passenger Cars
- Light Commercial Vehicles
- Heavy Commercial Vehicles
By Technology
- IMU
- Image Sensors
- Radar Sensors
- Others
By Geography
North America
- US
- Canada
- Mexico
- Rest of North America
Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Key Market Players
List of Companies Profiled in the Report:
- NVIDIA Corporation
- NXP Semiconductors N.V
- Robert Bosch GmbH
- TE Connectivity Ltd
- Infineon Technologies AG
- ZF Friedrichshafen AG
- TDK Corporation
- STMicroelectronics N.V
- Aptiv PLC
- Texas Instruments, Inc
Unique Offerings
- Exhaustive coverage
- The highest number of Market tables and figures
- Subscription-based model available
- Guaranteed best price
- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Automotive Sensor Fusion Market, by Propulsion Type
1.4.2 Global Automotive Sensor Fusion Market, by Vehicle Type
1.4.3 Global Automotive Sensor Fusion Market, by Technology
1.4.4 Global Automotive Sensor Fusion Market, by Geography
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition & Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 KBV Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Top Winning Strategies
3.3.1 Key Leading Strategies: Percentage Distribution (2018-2022)
3.3.2 Key Strategic Move: (Product Launches and Product Expansions : 2019, Oct - 2022, Nov) Leading Players
Chapter 4. Global Automotive Sensor Fusion Market by Propulsion Type
4.1 Global ICE Market by Region
4.2 Global BEV Market by Region
4.3 Global HEV Market by Region
Chapter 5. Global Automotive Sensor Fusion Market by Vehicle Type
5.1 Global Passenger Cars Market by Region
5.2 Global Light Commercial Vehicles Market by Region
5.3 Global Heavy Commercial Vehicles Market by Region
Chapter 6. Global Automotive Sensor Fusion Market by Technology
6.1 Global IMU Market by Region
6.2 Global Image Sensors Market by Region
6.3 Global Radar Sensors Market by Region
6.4 Global Others Market by Region
Chapter 7. Global Automotive Sensor Fusion Market by Region
7.1 North America Automotive Sensor Fusion Market
7.1.1 North America Automotive Sensor Fusion Market by Propulsion Type
7.1.1.1 North America ICE Market by Country
7.1.1.2 North America BEV Market by Country
7.1.1.3 North America HEV Market by Country
7.1.2 North America Automotive Sensor Fusion Market by Vehicle Type
7.1.2.1 North America Passenger Cars Market by Country
7.1.2.2 North America Light Commercial Vehicles Market by Country
7.1.2.3 North America Heavy Commercial Vehicles Market by Country
7.1.3 North America Automotive Sensor Fusion Market by Technology
7.1.3.1 North America IMU Market by Country
7.1.3.2 North America Image Sensors Market by Country
7.1.3.3 North America Radar Sensors Market by Country
7.1.3.4 North America Others Market by Country
7.1.4 North America Automotive Sensor Fusion Market by Country
7.1.4.1 US Automotive Sensor Fusion Market
7.1.4.1.1 US Automotive Sensor Fusion Market by Propulsion Type
7.1.4.1.2 US Automotive Sensor Fusion Market by Vehicle Type
7.1.4.1.3 US Automotive Sensor Fusion Market by Technology
7.1.4.2 Canada Automotive Sensor Fusion Market
7.1.4.2.1 Canada Automotive Sensor Fusion Market by Propulsion Type
7.1.4.2.2 Canada Automotive Sensor Fusion Market by Vehicle Type
7.1.4.2.3 Canada Automotive Sensor Fusion Market by Technology
7.1.4.3 Mexico Automotive Sensor Fusion Market
7.1.4.3.1 Mexico Automotive Sensor Fusion Market by Propulsion Type
7.1.4.3.2 Mexico Automotive Sensor Fusion Market by Vehicle Type
7.1.4.3.3 Mexico Automotive Sensor Fusion Market by Technology
7.1.4.4 Rest of North America Automotive Sensor Fusion Market
7.1.4.4.1 Rest of North America Automotive Sensor Fusion Market by Propulsion Type
7.1.4.4.2 Rest of North America Automotive Sensor Fusion Market by Vehicle Type
7.1.4.4.3 Rest of North America Automotive Sensor Fusion Market by Technology
7.2 Europe Automotive Sensor Fusion Market
7.2.1 Europe Automotive Sensor Fusion Market by Propulsion Type
7.2.1.1 Europe ICE Market by Country
7.2.1.2 Europe BEV Market by Country
7.2.1.3 Europe HEV Market by Country
7.2.2 Europe Automotive Sensor Fusion Market by Vehicle Type
7.2.2.1 Europe Passenger Cars Market by Country
7.2.2.2 Europe Light Commercial Vehicles Market by Country
7.2.2.3 Europe Heavy Commercial Vehicles Market by Country
7.2.3 Europe Automotive Sensor Fusion Market by Technology
7.2.3.1 Europe IMU Market by Country
7.2.3.2 Europe Image Sensors Market by Country
7.2.3.3 Europe Radar Sensors Market by Country
7.2.3.4 Europe Others Market by Country
7.2.4 Europe Automotive Sensor Fusion Market by Country
7.2.4.1 Germany Automotive Sensor Fusion Market
7.2.4.1.1 Germany Automotive Sensor Fusion Market by Propulsion Type
7.2.4.1.2 Germany Automotive Sensor Fusion Market by Vehicle Type
7.2.4.1.3 Germany Automotive Sensor Fusion Market by Technology
7.2.4.2 UK Automotive Sensor Fusion Market
7.2.4.2.1 UK Automotive Sensor Fusion Market by Propulsion Type
7.2.4.2.2 UK Automotive Sensor Fusion Market by Vehicle Type
7.2.4.2.3 UK Automotive Sensor Fusion Market by Technology
7.2.4.3 France Automotive Sensor Fusion Market
7.2.4.3.1 France Automotive Sensor Fusion Market by Propulsion Type
7.2.4.3.2 France Automotive Sensor Fusion Market by Vehicle Type
7.2.4.3.3 France Automotive Sensor Fusion Market by Technology
7.2.4.4 Russia Automotive Sensor Fusion Market
7.2.4.4.1 Russia Automotive Sensor Fusion Market by Propulsion Type
7.2.4.4.2 Russia Automotive Sensor Fusion Market by Vehicle Type
7.2.4.4.3 Russia Automotive Sensor Fusion Market by Technology
7.2.4.5 Spain Automotive Sensor Fusion Market
7.2.4.5.1 Spain Automotive Sensor Fusion Market by Propulsion Type
7.2.4.5.2 Spain Automotive Sensor Fusion Market by Vehicle Type
7.2.4.5.3 Spain Automotive Sensor Fusion Market by Technology
7.2.4.6 Italy Automotive Sensor Fusion Market
7.2.4.6.1 Italy Automotive Sensor Fusion Market by Propulsion Type
7.2.4.6.2 Italy Automotive Sensor Fusion Market by Vehicle Type
7.2.4.6.3 Italy Automotive Sensor Fusion Market by Technology
7.2.4.7 Rest of Europe Automotive Sensor Fusion Market
7.2.4.7.1 Rest of Europe Automotive Sensor Fusion Market by Propulsion Type
7.2.4.7.2 Rest of Europe Automotive Sensor Fusion Market by Vehicle Type
7.2.4.7.3 Rest of Europe Automotive Sensor Fusion Market by Technology
7.3 Asia Pacific Automotive Sensor Fusion Market
7.3.1 Asia Pacific Automotive Sensor Fusion Market by Propulsion Type
7.3.1.1 Asia Pacific ICE Market by Country
7.3.1.2 Asia Pacific BEV Market by Country
7.3.1.3 Asia Pacific HEV Market by Country
7.3.2 Asia Pacific Automotive Sensor Fusion Market by Vehicle Type
7.3.2.1 Asia Pacific Passenger Cars Market by Country
7.3.2.2 Asia Pacific Light Commercial Vehicles Market by Country
7.3.2.3 Asia Pacific Heavy Commercial Vehicles Market by Country
7.3.3 Asia Pacific Automotive Sensor Fusion Market by Technology
7.3.3.1 Asia Pacific IMU Market by Country
7.3.3.2 Asia Pacific Image Sensors Market by Country
7.3.3.3 Asia Pacific Radar Sensors Market by Country
7.3.3.4 Asia Pacific Others Market by Country
7.3.4 Asia Pacific Automotive Sensor Fusion Market by Country
7.3.4.1 China Automotive Sensor Fusion Market
7.3.4.1.1 China Automotive Sensor Fusion Market by Propulsion Type
7.3.4.1.2 China Automotive Sensor Fusion Market by Vehicle Type
7.3.4.1.3 China Automotive Sensor Fusion Market by Technology
7.3.4.2 Japan Automotive Sensor Fusion Market
7.3.4.2.1 Japan Automotive Sensor Fusion Market by Propulsion Type
7.3.4.2.2 Japan Automotive Sensor Fusion Market by Vehicle Type
7.3.4.2.3 Japan Automotive Sensor Fusion Market by Technology
7.3.4.3 India Automotive Sensor Fusion Market
7.3.4.3.1 India Automotive Sensor Fusion Market by Propulsion Type
7.3.4.3.2 India Automotive Sensor Fusion Market by Vehicle Type
7.3.4.3.3 India Automotive Sensor Fusion Market by Technology
7.3.4.4 South Korea Automotive Sensor Fusion Market
7.3.4.4.1 South Korea Automotive Sensor Fusion Market by Propulsion Type
7.3.4.4.2 South Korea Automotive Sensor Fusion Market by Vehicle Type
7.3.4.4.3 South Korea Automotive Sensor Fusion Market by Technology
7.3.4.5 Singapore Automotive Sensor Fusion Market
7.3.4.5.1 Singapore Automotive Sensor Fusion Market by Propulsion Type
7.3.4.5.2 Singapore Automotive Sensor Fusion Market by Vehicle Type
7.3.4.5.3 Singapore Automotive Sensor Fusion Market by Technology
7.3.4.6 Malaysia Automotive Sensor Fusion Market
7.3.4.6.1 Malaysia Automotive Sensor Fusion Market by Propulsion Type
7.3.4.6.2 Malaysia Automotive Sensor Fusion Market by Vehicle Type
7.3.4.6.3 Malaysia Automotive Sensor Fusion Market by Technology
7.3.4.7 Rest of Asia Pacific Automotive Sensor Fusion Market
7.3.4.7.1 Rest of Asia Pacific Automotive Sensor Fusion Market by Propulsion Type
7.3.4.7.2 Rest of Asia Pacific Automotive Sensor Fusion Market by Vehicle Type
7.3.4.7.3 Rest of Asia Pacific Automotive Sensor Fusion Market by Technology
7.4 LAMEA Automotive Sensor Fusion Market
7.4.1 LAMEA Automotive Sensor Fusion Market by Propulsion Type
7.4.1.1 LAMEA ICE Market by Country
7.4.1.2 LAMEA BEV Market by Country
7.4.1.3 LAMEA HEV Market by Country
7.4.2 LAMEA Automotive Sensor Fusion Market by Vehicle Type
7.4.2.1 LAMEA Passenger Cars Market by Country
7.4.2.2 LAMEA Light Commercial Vehicles Market by Country
7.4.2.3 LAMEA Heavy Commercial Vehicles Market by Country
7.4.3 LAMEA Automotive Sensor Fusion Market by Technology
7.4.3.1 LAMEA IMU Market by Country
7.4.3.2 LAMEA Image Sensors Market by Country
7.4.3.3 LAMEA Radar Sensors Market by Country
7.4.3.4 LAMEA Others Market by Country
7.4.4 LAMEA Automotive Sensor Fusion Market by Country
7.4.4.1 Brazil Automotive Sensor Fusion Market
7.4.4.1.1 Brazil Automotive Sensor Fusion Market by Propulsion Type
7.4.4.1.2 Brazil Automotive Sensor Fusion Market by Vehicle Type
7.4.4.1.3 Brazil Automotive Sensor Fusion Market by Technology
7.4.4.2 Argentina Automotive Sensor Fusion Market
7.4.4.2.1 Argentina Automotive Sensor Fusion Market by Propulsion Type
7.4.4.2.2 Argentina Automotive Sensor Fusion Market by Vehicle Type
7.4.4.2.3 Argentina Automotive Sensor Fusion Market by Technology
7.4.4.3 UAE Automotive Sensor Fusion Market
7.4.4.3.1 UAE Automotive Sensor Fusion Market by Propulsion Type
7.4.4.3.2 UAE Automotive Sensor Fusion Market by Vehicle Type
7.4.4.3.3 UAE Automotive Sensor Fusion Market by Technology
7.4.4.4 Saudi Arabia Automotive Sensor Fusion Market
7.4.4.4.1 Saudi Arabia Automotive Sensor Fusion Market by Propulsion Type
7.4.4.4.2 Saudi Arabia Automotive Sensor Fusion Market by Vehicle Type
7.4.4.4.3 Saudi Arabia Automotive Sensor Fusion Market by Technology
7.4.4.5 South Africa Automotive Sensor Fusion Market
7.4.4.5.1 South Africa Automotive Sensor Fusion Market by Propulsion Type
7.4.4.5.2 South Africa Automotive Sensor Fusion Market by Vehicle Type
7.4.4.5.3 South Africa Automotive Sensor Fusion Market by Technology
7.4.4.6 Nigeria Automotive Sensor Fusion Market
7.4.4.6.1 Nigeria Automotive Sensor Fusion Market by Propulsion Type
7.4.4.6.2 Nigeria Automotive Sensor Fusion Market by Vehicle Type
7.4.4.6.3 Nigeria Automotive Sensor Fusion Market by Technology
7.4.4.7 Rest of LAMEA Automotive Sensor Fusion Market
7.4.4.7.1 Rest of LAMEA Automotive Sensor Fusion Market by Propulsion Type
7.4.4.7.2 Rest of LAMEA Automotive Sensor Fusion Market by Vehicle Type
7.4.4.7.3 Rest of LAMEA Automotive Sensor Fusion Market by Technology
Chapter 8. Company Profiles
8.1 NVIDIA Corporation
8.1.1 Company Overview
8.1.2 Financial Analysis
8.1.3 Segmental and Regional Analysis
8.1.4 Research & Development Expense
8.1.5 Recent strategies and developments:
8.1.5.1 Product Launches and Product Expansions:
8.1.6 SWOT Analysis
8.2 NXP Semiconductors N.V.
8.2.1 Company Overview
8.2.2 Financial Analysis
8.2.3 Regional Analysis
8.2.4 Research & Development Expense
8.2.5 Recent strategies and developments:
8.2.5.1 Partnerships, Collaborations, and Agreements:
8.2.5.2 Product Launches and Product Expansions:
8.2.6 SWOT Analysis
8.3 Robert Bosch GmbH
8.3.1 Company Overview
8.3.2 Financial Analysis
8.3.3 Segmental and Regional Analysis
8.3.4 Research & Development Expense
8.3.5 Recent strategies and developments:
8.3.5.1 Partnerships, Collaborations, and Agreements:
8.3.5.2 Acquisition and Mergers:
8.3.6 SWOT Analysis
8.4 TE Connectivity Ltd.
8.4.1 Company Overview
8.4.2 Financial Analysis
8.4.3 Segmental and Regional Analysis
8.4.4 Research & Development Expense
8.4.5 SWOT Analysis
8.5 Infineon Technologies AG
8.5.1 Company Overview
8.5.2 Financial Analysis
8.5.3 Segmental and Regional Analysis
8.5.4 Research & Development Expense
8.5.5 Recent strategies and developments:
8.5.5.1 Partnerships, Collaborations, and Agreements:
8.5.5.2 Product Launches and Product Expansions:
8.6 ZF Friedrichshafen AG
8.6.1 Company Overview
8.6.2 Financial Analysis
8.6.3 Regional Analysis
8.6.4 Research & Development Expenses
8.6.5 Recent strategies and developments:
8.6.5.1 Partnerships, Collaborations, and Agreements:
8.6.5.2 Product Launches and Product Expansions:
8.7 TDK Corporation
8.7.1 Company Overview
8.7.2 Financial Analysis
8.7.3 Regional & Segmental Analysis
8.7.4 Research & Development Expenses
8.7.5 Recent strategies and developments:
8.7.5.1 Product Launches and Product Expansions:
8.8 STMicroelectronics N.V.
8.8.1 Company Overview
8.8.2 Financial Analysis
8.8.3 Segmental and Regional Analysis
8.8.4 Research & Development Expense
8.8.5 Recent strategies and developments:
8.8.5.1 Partnerships, Collaborations, and Agreements:
8.8.5.2 Product Launches and Product Expansions:
8.9 Aptiv PLC
8.9.1 Company Overview
8.9.2 Financial Analysis
8.9.3 Segmental and Regional Analysis
8.9.4 Research & Development Expense
8.9.5 Recent strategies and developments:
8.9.5.1 Product Launches and Product Expansions:
8.9.5.2 Acquisition and Mergers:
8.10. Texas Instruments, Inc.
8.10.1 Company Overview
8.10.2 Financial Analysis
8.10.3 Segmental and Regional Analysis
8.10.4 Research & Development Expense
Companies Mentioned
- NVIDIA Corporation
- NXP Semiconductors N.V.
- Robert Bosch GmbH
- TE Connectivity Ltd.
- Infineon Technologies AG
- ZF Friedrichshafen AG
- TDK Corporation
- STMicroelectronics N.V.
- Aptiv PLC
- Texas Instruments, Inc.
Methodology
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Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 235 |
| Published | January 2023 |
| Forecast Period | 2021 - 2028 |
| Estimated Market Value ( USD | $ 1774.2 Million |
| Forecasted Market Value ( USD | $ 7288.6 Million |
| Compound Annual Growth Rate | 22.8% |
| Regions Covered | Global |
| No. of Companies Mentioned | 10 |
