Sensor Fusion Market for Automotive by Technology, Data Fusion Type & Level, Software Layer, Vehicle Type and Region - Global Forecast to 2030 - ResearchAndMarkets.com

The "Global Sensor Fusion Market for Automotive by Technology (Camera, LIDAR & RADAR), Data Fusion Type & Level (Homogeneous, Heterogeneous, Data, Decision, Feature), Software Layer, Vehicle Type (ICE, Autonomous & Electric) and Region - Forecast to 2030" report has been added to ResearchAndMarkets.com's offering.

The ICE sensor fusion market for automotive is projected to reach USD 22.2 billion by 2030 from an estimated USD 2.9 billion in 2021, at a CAGR of 25.4% during the forecast period.

Various governments globally are implementing safety standards by making safety features such as automated emergency brake, adaptive cruise control, lane departure warning a mandatory feature in vehicles, driving adoption of cameras, radars and LiDARs in automobiles.

This is expected to strongly drive the adoption of sensor fusion in developed as well developing countries. Also, growing popularity of high-end and luxury cars is boosting sensor fusion market for automotive. Countries such as India, China, Brazil, Mexico, Argentina, European Union, US are focusing on enhanced automotive safety standards. Thus, the demand is expected to gain momentum globally.

Heterogeneous fusion type is expected to be the largest market by data fusion type

The key benefits of heterogenous sensor fusion are enhanced system performance and robustness. Examples of multi-modal fusion systems or heterogeneous sensors are visible cameras, Far IR cameras, visual cameras LASER scanner radar, GPS localizer CAN bus Gyroscope, etc. Various modern sensor networks are heterogenous - a combination of a variety of wired and wireless sensors/actuators.

For instance, in a driver assistance system, the system collects data from internal and external sensors installed in the car. This includes various types of sensors such as GPS localizers, a CAN bus, a gyroscope, radar, and cameras. Thus, the multiple benefits offered by heterogeneous sensor data fusion are driving its popularity in vehicles.

Decision fusion market segment is expected to be the fastest

In decision level sensors, each sensor makes an individual decision before forming a combination of decisions to arrive at a more informed final decision, i.e., target decision fusion. Decision fusion is less complex than data fusion. Decision-making algorithms, as a key technology for uncertain data fusion, is the core to obtain reasonable multisensory information fusion results.

Thus, there is a broad application of decision-making algorithms on target attributes, characteristics, and types through detailed processing of information obtained through various sensors. A multitude of theorems and algorithms are emerging in decision sensor fusions. Decision fusion is expected to gain popularity globally in the coming years, owing to its advantages and less complex architecture.

One of the many practical benefits offered by decision fusion is that it allows combining individual results, even if it was not expected in the testing of the algorithm. Consequently, different sources of information can be easily exchanged, and the fusion strategy is readily adapted to unknown future changes of input sources.

Asia Pacific market is expected to register the highest growth during the forecast period

The Asia Pacific sensor fusion market for automotive is estimated to be the fastest-growing regional market. The growing adoption of advanced ADAS technologies in China, Japan, South Korea, and India is expected to drive market growth in the region. China's passenger car production is expected to reach 24 million units by 2026, presenting a huge opportunity for sensor fusion hardware manufacturers and software/algorithm developers globally as well as domestically.

Not only passenger cars but trucks are also set to reach 2 million units by 2026. The South Korean transport ministry announced that it requires all new large passenger vehicles and trucks to be fitted with AEB and LDW systems from January 2019. Thus, the implementation of government mandates is expected to drive the adoption of sensors- cameras, radars and LiDARs. Such factors would in turn, drive the growth of sensor fusion technology during the forecast period.

Market Dynamics

Drivers

• Technical advantages offered by sensor fusion
• Stringent emission standards regarding NOx and particulate matter

Restraints

• Lack of standardization in software architecture/hardware platforms

Opportunities

• Development of autonomous vehicles

Challenges

• Security and safety concerns

Companies Mentioned

• Allegro Microsystems
• Analog Devices
• Aptiv Plc
• Baselabs GmbH
• CTS Corporation
• Continental AG
• Denso Corporation
• Elmos Semiconductor Se
• Ibeo Automotive Systems GmbH
• Infineon Technologies
• Kionix, Inc.
• Leddartech Inc.
• Magna International
• Maxim Integrated
• Memsic Semiconductor (Tianjin) Co., Ltd.
• Microchip Technology Inc.
• Mobileye
• Monolithic Power Systems, Inc.
• NXP Semiconductors N.V.
• Renesas Electronics Corporation
• Robert Bosch GmbH
• STMicroelectronics
• Sensata Technologies, Inc.
• TDK Corporation
• TE Connectivity Ltd.
• Velodyne LiDAR, Inc.
• ZF Friedrichshafen AG

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