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Last Updated: Apr 25, 2025 | Study Period: 2023-2030
The brain that combines sensor data from cameras, lidar, radar, inertial measurement units (IMUs), and map data for perception and decision-making is the ADAS domain controller. Electronic control units (ECUs) were first included into automobiles by automakers in the 1980s.
The primary focus of advanced driving assistance systems (ADAS) is on driver aids like night vision, driver awareness, and adaptive cruise control as well as collision avoidance technologies like lane departure warning and blind-spot applications.
Advanced Driver Assistance Technologies (ADAS) are passive and active safety systems created to eliminate human mistake from driving a variety of automobiles. ADAS systems use cutting-edge technology to aid the driver while they are driving and so enhance their performance.
Depending on how each ADAS application will be used, different ECUs were placed throughout the car. To identify potential threats around the car, the forward collision avoidance ECU, for instance, was installed in the windscreen. However, the more sophisticated driver aid systems needed for increasing degrees of automated driving cannot be supported by these decentralised system architectures.
Modern systems, on the other hand, necessitate high processing performance and integrate numerous functions into a single integrated domain controller, or ADAS ECU. Depending on how each ADAS application will be used, different ECUs were placed throughout the car. To identify potential threats around the car, the forward collision avoidance ECU, for instance, was installed in the windscreen.
Global ADAS control unit market accounted for $XX Billion in 2022 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2023 to 2030.
The need for faster, more accurate sensors and the capacity to process the received data in real time is inherent in the desire to pave the way for higher levels of autonomy. Applications like "Vulnerable Road Users" (VRU) protection, "Lane Support," "Automatic Emergency Steering," and "Automated Parking" demand processing multiple video feeds, even a 360-degree view of the vehicle.
âThe Hailo AI processor was made to scale, and it is capable of handling the taxing deep learning workloads needed by ADAS (Advanced Driver Assistance Systems).
Multiple video streams can be processed by a single small, low-power chip, and multiple chips can cooperate or cascade to achieve industry-leading efficiency, scalability, high processing throughput, and low latency. The adaptability of the solution permits the use of different types of camera.
Sl no | Topic |
1 | Market Segmentation |
2 | Scope of the report |
3 | Abbreviations |
4 | Research Methodology |
5 | Executive Summary |
6 | Introduction |
7 | Insights from Industry stakeholders |
8 | Cost breakdown of Product by sub-components and average profit margin |
9 | Disruptive innovation in the Industry |
10 | Technology trends in the Industry |
11 | Consumer trends in the industry |
12 | Recent Production Milestones |
13 | Component Manufacturing in US, EU and China |
14 | COVID-19 impact on overall market |
15 | COVID-19 impact on Production of components |
16 | COVID-19 impact on Point of sale |
17 | Market Segmentation, Dynamics and Forecast by Geography, 2023-2030 |
18 | Market Segmentation, Dynamics and Forecast by Product Type, 2023-2030 |
19 | Market Segmentation, Dynamics and Forecast by Application, 2023-2030 |
20 | Market Segmentation, Dynamics and Forecast by End use, 2023-2030 |
21 | Product installation rate by OEM, 2023 |
22 | Incline/Decline in Average B-2-B selling price in past 5 years |
23 | Competition from substitute products |
24 | Gross margin and average profitability of suppliers |
25 | New product development in past 12 months |
26 | M&A in past 12 months |
27 | Growth strategy of leading players |
28 | Market share of vendors, 2023 |
29 | Company Profiles |
30 | Unmet needs and opportunity for new suppliers |
31 | Conclusion |
32 | Appendix |