Sensor Fusion Market for Automotive by Level of Autonomy (L2, L3, L4), Vehicle Type (Passenger Cars, LCV, HCV), Electric Vehicle Type (BEV, PHEV, FCEV), Sensor Platform, Fusion Level (Data, Feature), Sensor Type, Algorithm, Region - Global Forecast 2030
[387 Pages Report] The global sensor fusion market for automotive is projected to grow from USD 0.3 billion in 2023 to USD 3.3 billion by 2030, registering a CAGR of 42.4%. With technological advancements, increasing safety demand, and supportive government regulations, vehicles with sensor fusion have gained significant traction as a viable and sustainable transportation option. Government and regulatory bodies globally have intensified their focus on enhancing road safety, prompting the enforcement of stringent safety standards and vehicle mandates. As a result, the sensor fusion market for automotive is experiencing robust growth, given its integral role in making vehicles safer and aligning with worldwide safety regulations.
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Market Dynamics:
Driver: Increasing advancements in ADAS technology
The continuous advancement of ADAS technology is driving the demand for comprehensive sensor fusion solutions within the automotive industry. While ADAS already encompasses a wide range of safety and automation features, such as adaptive cruise control and lane-keeping assistance, the ongoing evolution of this technology has given rise to new and exciting applications that leverage advanced sensors and AI capabilities. One of the most notable advancements is in automatic parking systems. These systems go beyond simple parking assistance by enabling vehicles to navigate parking lots and tight spaces autonomously. They utilize a combination of sensors, including cameras and ultrasonic sensors, to detect obstacles, assess parking spaces, and execute precise parking maneuvers. Another significant development is in active lane keep assist. This technology alerts the driver when they're drifting out of their lane and actively steers the vehicle to keep it within the lane. Automated driving systems are becoming more sophisticated, enabling traffic jam assist and highway pilot features. These systems use a combination of sensors, including cameras and LiDAR, to provide semi-autonomous driving capabilities. They can handle tasks like maintaining a safe following distance, navigating stop-and-go traffic, and changing lanes under certain conditions. Pedestrian avoidance systems use a mix of sensors, including cameras and radar, to detect pedestrians near the vehicle and take action to avoid collisions. This includes both visual and audible alerts to the driver, as well as automated braking if necessary. As consumers and regulators demand higher safety standards and vehicles transition toward higher levels of automation and autonomy, the need for sensor fusion has increased. Ensuring the accuracy and redundancy of sensor data is essential in realizing the safety and reliability expected from ADAS and autonomous driving systems.
Restraint: Data privacy concerns
The increasing use of sensors for data collection offers valuable insights and enhances the efficiency of vehicles. However, this rapid proliferation of sensors gives rise to significant data privacy concerns, which can potentially restrain the growth of the sensor fusion market. Sensor fusion involves integrating data from multiple sensors to provide a more comprehensive and accurate view of the environment. While this can be highly beneficial, it necessitates collecting a vast amount of data, often including sensitive information. These sensors can be found in various applications, from smart cities and autonomous vehicles to wearable devices. They collect data that may include personal, location, or behavioral information. As a result, the increased use of sensors raises issues such as accessibility to data, storage, security, and the potential for misuse or breaches of personal privacy. Considering these concerns, regulators, businesses, and consumers increasingly demand robust data protection measures and transparency, which can challenge the growth of the sensor fusion market for automotive. Adhering to strong data privacy standards and ensuring that users have control over their data will be crucial to overcoming these constraints and fostering trust in sensor-based technologies.
Opportunity: Rising demand for safer and sustainable transportation solutions
The use of sensor fusion as an integral component of ADAS has enhanced vehicle safety and led to more fuel-efficient and eco-friendly vehicles, making a substantial contribution to sustainability. ADAS relies on LiDAR, radar, cameras, and ultrasonic sensors to gather real-time data about the vehicle's surroundings, enabling it to make informed decisions to improve safety and driving efficiency. This data-driven approach has significant implications for sustainability. Sensor fusion aids in optimizing driving behavior by providing critical information to ADAS systems, such as adaptive cruise control and lane-keeping assistance. These features can reduce aggressive driving patterns, leading to smoother acceleration and deceleration, reducing fuel consumption, and lower emissions. The enhanced situational awareness offered by sensor fusion allows ADAS systems to make precise decisions on route planning and traffic management, minimizing fuel waste and reducing the carbon footprint. For example, vehicles can take more efficient routes, avoiding traffic congestion and idling, leading to fuel savings and emission reduction. Sensor fusion contributes to developing autonomous and electric vehicles, key elements in sustainability efforts. Sensor fusion is fundamental to the safe operation of autonomous vehicles by providing a comprehensive view of the vehicle's surroundings, reducing the potential for accidents.
Moreover, electric vehicles benefit from sensor fusion by optimizing energy usage and improving regenerative braking systems. As global efforts to reduce carbon emissions and combat climate change intensify, the automotive industry is under pressure to develop more sustainable transportation solutions. The role of sensor fusion in making vehicles safer and more fuel-efficient aligns with these objectives, offering an opportunity for the sensor fusion market for automotive. As a result, continued growth is anticipated in adopting sensor fusion technology, both in developing existing vehicles and in shaping the future of sustainable mobility.
Challenge: Management of high volume of sensor data
Processing a large volume of data in real-time requires advanced computing capabilities, which can be expensive. The need for high-performance processors, specialized hardware, and efficient software algorithms to handle the data efficiently adds significant cost to developing and implementing sensor fusion systems. This data must be processed and analyzed with minimal latency to ensure the timely response of safety and automation features. Delays in data processing can compromise the effectiveness of systems like collision avoidance and adaptive cruise control, potentially leading to safety risks. The increasing complexity and sophistication of sensor fusion systems result in software development, testing, and maintenance. As the number of sensors and data sources grows, the challenge of developing and maintaining reliable and robust software adds to the overall cost and complexity of sensor fusion solutions.
Market Ecosystem
HCVs to be the fastest growing segment during forecast period
Heavy commercial vehicles include trucks, trailers, buses, and others, contributing to a large part of the economies in countries such as US, China, European countries, and India. Heavy-duty trucks tend to travel longer distances; therefore, road accidents can occur due to driver fatigue. MAN, IVECO, and Mercedes-Benz focus on offering features in heavy-duty trucks for a safer driving experience, which will be enabled by sensor fusion technology. Bosch and Continental already offer various ADAS solutions specially targeted at L2 commercial vehicles. Various truck OEMs, including Daimler and Volvo, had revealed plans back in 2020 to develop L4 autonomy-based trucks directly, bypassing L3. For instance, in 2022, Daimler Trucks announced a collaboration with Waymo LLC to develop L4 autonomous technology on a Freightliner Cascadia. Daimler’s Class 8 truck will get Waymo Driver technology, and production could begin in 2024.
L3 to be the fastest growing segment during the forecast period
Level 3 vehicles are considered to be partially autonomous with highway auto-driving features. Often referred to as eyes-off vehicles, these vehicles can allow the driver to sit back and relax as they can take care of everything while driving along the road. The L3 autonomous vehicles offer features such as autonomous emergency braking, connected vehicle technology, and automated valet parking. These vehicles are equipped with sensors such as LiDAR, radars, ultrasonic, and GPS, which use sensor fusion technology to increase the accuracy and efficiency of the sensors. All these technologies cater to the rising demands of road safety, which will, in turn, drive the sensor fusion market for automobiles. Multiple L3 autonomous vehicle models have been or will be launched in the short term. In March 2021, Honda Motors (Japan) unveiled a limited batch of its flagship Legend sedan, becoming the world’s first carmaker to sell a vehicle equipped with certified level 3 self-driving technology. Mercedes-Benz (Germany) and GAC (China) also launched their passenger cars with level 3 automation in 2020 and 2021. In July 2022, Hyundai Motor Group announced its plan to launch its most advanced level 3 autonomous cars by 2023. The company has decided to launch its flagship luxury Genesis G90 sedan and Kia’s electric SUV, the EV9. Mercedes-Benz also launched its L3 S-Class and EQS autonomous passenger cars in 2023. Further, Stellantis will be launching its L3 vans in 2024.
Asia Pacific to be the largest market by value during the forecast period
China, Japan, and South Korea account for the largest share of the sensor fusion market for automotive in the Asia Pacific region. The market growth in this region can be attributed to the high vehicle production and increased use of advanced electronics in Japan, South Korea, and China. These countries' governments have recognized the automotive industry's growth potential and have consequently taken different initiatives to encourage major OEMs to enter their domestic markets. Several European and American automobile manufacturers, such as Volkswagen (Germany), Mercedes-Benz (Germany), and General Motors (US), have shifted their production plants to developing countries. Major sensor component providers such as Robert Bosch (Germany), Continental (Germany), and DENSO Corporation (Japan) have production facilities across the region. China is one of the fastest-growing econosmies in Asia Pacific. It has experienced exceptional growth in the last few decades and has become the world’s second-largest economy. China is the largest vehicle manufacturer in the world and is expected to retain its leading position during the forecast period. The rising demand for vehicles in the country, coupled with favorable investment regulations and economical labor costs, has raised domestic vehicle production levels. Vehicle safety norms drive the sensor fusion market for automotive in the country. Several advanced safety features are mandated in the country to prevent accidents. Many car manufacturers have also established production facilities in China to cater to global demand.
Key Market Players
The Sensor Fusion Market for Automotive is dominated by Mobileye Global Inc. (Israel), NVIDIA Corporation (US), Qualcomm Incorporated (US), Tesla Inc. (US), and Huawei Technologies, Co., Ltd. (China), among others. These companies have worked with other players in the automotive sensor fusion ecosystem and developed best in class sensor fusion technology.
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Scope of the Report
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Report Metric |
Details |
Market size available for years |
2019–2030 |
Base year considered |
2022 |
Forecast period |
2023-2030 |
Forecast units |
Volume (Thousand Units), Value(USD Million/Billion) |
Segments covered |
Level of Autonomy, Vehicle Type, Electric Vehicle Type, Sensor Platform, Fusion Level, Sensor Type, Algorithm, Data Fusion Type, Technology, Region. |
Geographies covered |
Asia Pacific, Europe, and North America |
Companies Covered |
Mobileye Global Inc. (Israel), NVIDIA Corporation (US), Qualcomm Incorporated (US), Tesla Inc. (US), and Huawei Technologies, Co., Ltd. (China) and more. |
This research report categorizes the sensor fusion market for automotive based on Level of Autonomy, Vehicle Type, Electric Vehicle Type, Sensor Platform, Fusion Level, Sensor Type, Algorithm, Data Fusion Type, Technology, Region.
Based on Level of Autonomy:
- L2
- L3
- L4
Based on Vehicle Type:
- Passenger Cars
- Light Commercial Vehicles
- Heavy Commercial Vehicles
Based on Electric Vehicle Type:
- Battery Electric Vehicle (BEV)
- Plug-In Hybrid Electric Vehicle (PHEV)
- Fuel Cell Electric Vehicle (FECV)
Based on Sensor Platform:
- High-Level Fusion
- Mid-Level Fusion
- Low-Level Fusion
Based on Fusion Level:
- Data Fusion
- Feature Fusion
- Decision Fusion
Based on Sensor Type:
- Camera
- Radar
- Lidar
- Ultrasonic Sensor
- Infrared Sensor
Based on Algorithm:
- Kalman Filter
- Bayesian Filter
- Centeral Limit Theorem
- Convolution Neural Network
Based on Data Fusion Type:
- Homogeneous
- Heterogeneous
Based on Technology:
- ADAS
- Autonomous Driving
Based on the region:
-
Asia Pacific
- China
- Japan
- India
- South Korea
-
Europe
- France
- Germany
- Italy
- Spain
- UK
-
North America
- US
- Canada
Recent Developments
- In September 2023, Mobileye Global Inc. and FAW Group unveiled a strategic collaboration, capitalizing on their software, hardware, and technology product strengths. Their joint efforts will focus on developing innovative products utilizing Mobileye SuperVision and Mobileye Chauffeur platforms.
- In September 2023, Qualcomm partners with Mercedes-Benz to power vehicles using Snapdragon Digital Chassis Solutions. The collaboration aims to enable high-bandwidth, always-on, and always-connected in-vehicle experiences, starting with Mercedes-Benz E-Class sedans.
- In September 2023, JMC Group partnered with Baidu, Inc. for intelligent driving, combining AI expertise with advanced automotive technologies to promote and develop high-level intelligent driving and urban transportation solutions.
- In July 2023, Samsung Electronics Co. is designated to produce Tesla Inc.'s forthcoming Full Self-Driving (FSD) chips intended for application in Level-5 autonomous driving vehicles. These chips will be manufactured using Samsung's cutting-edge 4-nanometer node technology and will be integrated into Tesla's Hardware 5 (HW 5.0) computers.
- In May, 2023, Waymo LLC and Uber partnered to integrate Waymo's cutting-edge autonomous driving technology with the extensive reach and scale of Uber's ridesharing and delivery networks.
- In May 2023, Vector Informatik GmbH acquired BASELABS GmbH a specialist in sensor fusion for automated driving. The company aims to focus on software-defined vehicles throught this strategic investment.
- In March 2023, Renesas Electronics Corporation partnered with Tata Consultancy Services to inaugurate an Innovation Center dedicated to crafting semiconductor designs and software solutions for various sectors, including IoT, infrastructure, industrial, and automotive segments.
- In February 2023, Mercedes-Benz collaborated with NVIDIA Corporation to leverage its software, data, and AI proficiency alongside its Orin system-on-chip. This collaboration aims to augment SAE Level 2 functionalities within urban contexts and ultimately achieve SAE Level 3 capabilities, specifically targeting speeds up to 80 mph (130 km/h).
Frequently Asked Questions (FAQ):
What is the current size of the Sensor Fusion Market for Automotive by volume?
The current size of the Sensor Fusion Market for Automotive is estimated at 12,802 thousand units by volume in 2023.
Who are the winners in the Sensor Fusion Market for Automotive?
The Sensor Fusion Market for Automotive is dominated by Mobileye Global Inc. (Israel), NVIDIA Corporation (US), Qualcomm Incorporated (US), Tesla Inc. (US), and Huawei Technologies, Co., Ltd. (China), among others.
Which region will have the fastest-growing market for Sensor Fusion Market for Automotive?
Asia-Pacific will be the fastest-growing region in the Sensor Fusion Market for Automotive due to the increasing emphasis on safety, supportive government regulations, and technological advancements.
What are the key technologies affecting the Sensor Fusion Market for Automotive?
The key technologies affecting the Sensor Fusion Market for Automotive are Deep Learning, Artificial Intelligence, Edge Computing, Blockchain Technology, and Sensor fsusion with Kalman filer.
What algorithms are mainly used in sensor fusion marke for automotive?
The Kalman filter, Bayesian filter, Central Limit Theorem, and Convolutional Neural Network are algorithms mainly used in sensor fusion market for automotive.
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The study involved four major activities in estimating the current size of the sensor fusion market for automotive. Exhaustive secondary research was done to collect information on the market, the peer market, and the child markets. The next step was to validate these findings, assumptions, and sizing with the industry experts across value chains through primary research. The top-down and bottom-up approaches were employed to estimate the complete market size. Thereafter, market breakdown and data triangulation processes were used to estimate the market size of segments and subsegments.
Secondary Research
In the secondary research process, various secondary sources were used to identify and collect information for this study on the sensor fusion market for automotive. The secondary sources included annual reports, press releases, and investor presentations of companies; whitepapers, certified publications, and articles from recognized authors, directories, and databases; and articles from recognized associations and government publishing sources.
Primary Research
Extensive primary research was conducted after acquiring an understanding of the scenario of the sensor fusion market for automotive through secondary research. Several primary interviews were conducted with market experts from both the demand (OEMs) and supply (hardware providers, SOC providers, sensor fusion providers, and other component manufacturers) sides across three major regions, namely, North America, Europe and Asia Pacific. Approximately 52% and 48% of primary interviews were conducted from the demand and supply sides, respectively. Primary data was collected through questionnaires, emails, and telephonic interviews. In the canvassing of primaries, various departments within organizations were covered, such as sales, operations, and administration, to provide a holistic viewpoint in this report.
After interacting with industry experts, brief sessions with highly experienced independent consultants were also conducted to reinforce the findings from primaries. This, along with the in-house subject-matter experts’ opinions, led to the findings described in the remainder of this report.
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Market Size Estimation
The bottom-up approach was used to estimate and validate the size of the sensor fusion market for automotive. This method was also used extensively to estimate the size of various subsegments in the market. The research methodology used to estimate the market size includes the following:
- The key players in the industry and markets have been identified through extensive secondary research
- The industry’s supply chain and market size, in terms of volume, have been determined through primary and secondary research processes
- All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources
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Market Size Validation
The top-down approach was used to determine the size of the sensor fusion market for automotive for the component, software, propulsion, vehicle type, sensor platform approach, and sensor fusion process. The total market size in value (USD million) was derived using the top-down approach.
For instance, the market for the component segment was derived using the top-down approach to estimate the hardware and software subsegments. Mapping was carried out at the regional level to understand the contribution by type of component. The market size was derived at the regional level in terms of value. The total value of the market was multiplied by the cost penetration percentage of each segment at the regional level.
Data Triangulation
After arriving at the overall market size of the global market through the above-mentioned methodology, this market was split into several segments and subsegments. The data triangulation and market breakdown procedure were employed, wherever applicable, to complete the overall market engineering process and arrive at the exact market value data for the key segments and subsegments. The extrapolated market data was triangulated by studying various macro indicators and regional trends from both the demand- and supply-side participants.
Market Definition
Sensor fusion is the process of combining data from multiple sensors to create a more comprehensive and accurate representation of the environment. It is used in a variety of applications, including autonomous vehicles, advanced driver assistance systems (ADAS). In vehicles, sensor fusion is used to improve the accuracy and reliability of perception systems. Perception systems are responsible for understanding the vehicle's surroundings, including the presence and location of other vehicles, pedestrians, cyclists, and objects.
List of Key Stakeholders
- Automotive Sensor Manufacturers
- ADAS Integrators
- ADAS Solution Suppliers
- Automotive Component Manufacturers
- Automotive SoC (system on chip) and ECU (electronic control unit) Manufacturers
- Automotive Software and Platform Providers
- Autonomous Driving Platform Providers
- Connectivity Service Providers
- Country-specific Automotive Associations
- Designing and Testing Companies
- European Automobile Manufacturers’ Association (ACEA)
- National Highway Traffic Safety Administration (NHTSA)
Report Objectives
- To segment and forecast the sensors fusion market in terms of volume (thousand units) and value (USD million)
- To define, describe, and forecast the sensor fusion market based on technology, level of autonomy, application, data fusion type, fusion level, EV type, vehicle type, sensor platform approach, algorithm and region
- To segment the market and forecast its size, by volume and value, based on region (Asia Pacific, Europe, and North America)
- To analyze and forecast the sensor fusion market for automotive based on fusion level (data, feature, and decision)
- To analyze and forecast the market based on sensor platform approach (low-level fusion, mid-level fusion, high-level fusion)
- To qualitatively analyze the market based on data fusion type (homogeneous and heterogeneous)
- To analyze and forecast the market based on ICE vehicle type [passenger car, light commercial vehicle (LCV), and heavy commercial vehicle (HCV)]
- To analyze and forecast the market based on electric vehicle type [battery electric vehicle (BEV), plug-in hybrid electric vehicle (PHEV) and fuel-cell electric vehicle (FCEV)]
- To analyze and forecast the market based on by level of autonomy (L2, L3, and L4)
- To qualitatively analyze the market based on sensor type[Camera, Radar, Lidar, Ultrasonic Sensor, Infrared Sensor]
- To qualitatively analyze the market based on Algorithm [Kalman filter, Bayesian filter, central limit theorem, convolutional neural network]
- To analyze and forecast the market based on technology [ADAS, autonomous driving]
- To analyze the technological developments impacting the sensor fusion market
- To analyze opportunities for stakeholders and the competitive landscape for market leaders
- To provide detailed information regarding the major factors influencing the market growth (drivers, challenges, restraints, and opportunities)
- To strategically analyze markets with respect to individual growth trends, prospects, and contributions to the total market
-
To study the following with respect to the market
- Value Chain Analysis
- Ecosystem Analysis
- Porter’s Five Forces Analysis
- Technology Analysis
- Case Study Analysis
- Patent Analysis
- Buying Criteria
- To strategically profile key players and comprehensively analyze their market shares and core competencies
- To track and analyze competitive developments such as deals (joint ventures, mergers & acquisitions, partnerships, collaborations), new product developments, and other activities carried out by key industry participants
Available Customizations
With the given market data, MarketsandMarkets offers customizations in line with company-specific needs.
- Further breakdown of the sensor fusion market for automotive, by vehicle type
- Additional countries (apart from those already considered in report) with significant sensor fusion market
Company Information
- Profiles of additional market players (up to five)
Growth opportunities and latent adjacency in Sensor Fusion Market