The automotive industry continues to be a hotbed of patent innovation. The increasing demand for autonomous vehicles necessitates the integration of radar and cameras in their environment perception. The availability of high-performance computing platforms and advancements in artificial intelligence (AI) and machine learning algorithms are driving innovation in radar camera fusion. New sensor technologies and fusion algorithms are also being developed to enhance performance. Deep learning algorithms, high-resolution radar, multi-sensor fusion, and edge computing are crucial in radar camera fusion for autonomous driving applications. These algorithms improve object identification and classification, reduce interference, and process large amounts of data in real time, enhancing performance. In the last three years alone, there have been over 1.7 million patents filed and granted in the automotive industry, according to GlobalData’s report on Artificial intelligence in automotive: radar camera fusion. Buy the report here.
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However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilizing and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
300+ innovations will shape the automotive industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the automotive industry using innovation intensity models built on over one million patents, there are 300+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, autonomous on-demand logistics, end-to-end learning models, and adaptive driver alerting are disruptive technologies that are in the early stages of application and should be tracked closely. Vehicular vision, adaptive cruise control, and predictive acceleration control are some of the accelerating innovation areas, where adoption has been steadily increasing.
Innovation S-curve for artificial intelligence in the automotive industry
Radar camera fusion is a key innovation area in artificial intelligence
Radar camera fusion is the process of combining and integrating data from radar sensors and cameras to improve accuracy and reliability in various applications. This fusion allows for a more comprehensive perception of the surrounding environment by combining the strengths of both radar and camera technologies. By leveraging the strengths of each sensor, radar camera fusion enhances object detection, tracking, and recognition capabilities, leading to improved safety and performance in automotive and surveillance systems.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 30+ companies, spanning technology vendors, established automotive companies, and up-and-coming start-ups engaged in the development and application of radar camera fusion.
Key players in radar camera fusion – a disruptive innovation in the automotive industry
‘Application diversity’ measures the number of applications identified for each patent. It broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of countries each patent is registered in. It reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to radar camera fusion
Source: GlobalData Patent Analytics
Robert Bosch Stiftung is one of the leading patent filers in radar camera fusion technology, which combines radar and camera data to create a comprehensive view of the environment, improving driver assistance and autonomous driving systems. Major automotive companies such as Bosch, Toyota, and Denso are investing in this technology, giving them a competitive advantage. Some other key patent filers in this space are Toyota Motor and Denso.
In terms of application diversity, Intel leads the pack, while Kia and Nissan Motor stood in the second and third positions, respectively. By means of geographic reach, Intel held the top position, followed by Nissan Motor and Komatsu.
To further understand the key themes and technologies disrupting the automotive industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Automotive.
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
