Aptiv

Maxieye specializes in smart driving and travel solutions, focusing on the development of autonomous driving systems for the transportation sector in China. The company offers a diverse range of products, including the MAXIPILOT1.0 and PLUS, which provide intelligent cruise and pilot assistance features. Maxieye emphasizes cost-effective Level 2 (L2) solutions as well as high-end intelligence for passenger vehicles. Its offerings include full-working-condition, multi-scenario, and cross-platform advanced driver-assistance systems (ADAS) and autonomous driving systems (ADS). These products address a spectrum of technological levels from Level 0 to Level 4, enhancing vehicle safety and driving capabilities through advanced computer vision systems that detect obstacles and oncoming traffic.

StradVision, Inc. specializes in developing advanced perception algorithms designed to enhance the capabilities of vehicles in recognizing and understanding their surroundings. Founded in 2014 and headquartered in Seoul, South Korea, with additional offices in California, Japan, India, China, and Germany, the company provides solutions such as SVNet External for external vehicle perception and SVNet Internal for monitoring driver and passenger status. StradVision's technology supports advanced driver assistance systems and autonomous vehicle applications, utilizing camera-based perception AI and LiDAR to ensure safety and accuracy in real-time object detection and classification. The company has achieved notable rankings in technology evaluations and holds over 60 issued patents, with more than 150 pending, reflecting its commitment to innovation in the automotive sector. Its auto labeling tool enhances data training efficiency, minimizing the need for human intervention and facilitating the development of reliable self-driving capabilities.

StradVision, Inc. specializes in developing advanced perception algorithms designed to enhance the capabilities of vehicles in recognizing and understanding their surroundings. Founded in 2014 and headquartered in Seoul, South Korea, with additional offices in California, Japan, India, China, and Germany, the company provides solutions such as SVNet External for external vehicle perception and SVNet Internal for monitoring driver and passenger status. StradVision's technology supports advanced driver assistance systems and autonomous vehicle applications, utilizing camera-based perception AI and LiDAR to ensure safety and accuracy in real-time object detection and classification. The company has achieved notable rankings in technology evaluations and holds over 60 issued patents, with more than 150 pending, reflecting its commitment to innovation in the automotive sector. Its auto labeling tool enhances data training efficiency, minimizing the need for human intervention and facilitating the development of reliable self-driving capabilities.

TTTech Auto is a company that specializes in platform products and services aimed at enhancing system safety and security for software-defined vehicles. It develops a safety software platform designed for real-time control applications, which plays a crucial role in advancing driver assistance systems and fully automated driving. The company offers automotive software solutions, in-vehicle communication systems, and safety consulting services. Additionally, TTTech Auto addresses the technical challenges associated with complex vehicle electronics, enabling car manufacturers to achieve modularity, portability, and standardized interfaces. Through its innovative offerings, the company contributes significantly to the evolution of automotive technology, particularly in the realm of automation and safety.

StradVision, Inc. specializes in developing advanced perception algorithms designed to enhance the capabilities of vehicles in recognizing and understanding their surroundings. Founded in 2014 and headquartered in Seoul, South Korea, with additional offices in California, Japan, India, China, and Germany, the company provides solutions such as SVNet External for external vehicle perception and SVNet Internal for monitoring driver and passenger status. StradVision's technology supports advanced driver assistance systems and autonomous vehicle applications, utilizing camera-based perception AI and LiDAR to ensure safety and accuracy in real-time object detection and classification. The company has achieved notable rankings in technology evaluations and holds over 60 issued patents, with more than 150 pending, reflecting its commitment to innovation in the automotive sector. Its auto labeling tool enhances data training efficiency, minimizing the need for human intervention and facilitating the development of reliable self-driving capabilities.

Aptiv, headquartered in Gillingham, England, is a global technology company specializing in mobility solutions. It offers a range of products and services, including electrical components and systems for vehicles, advanced safety and user experience features, and over-the-air (OTA) software lifecycle and data management services. Aptiv's customer base is diverse, with its top 10 customers accounting for 54% of revenue, none of which are dominant. The company operates in 45 countries, with 14 technical centers and various manufacturing sites and customer support centers. Aptiv's mission is to deliver software capabilities, advanced computing platforms, and networking architecture to enable safer, greener, and more connected mobility solutions.

Ottomatika is a Pittsburgh-based company that specializes in developing advanced driver-assist and automated driving systems for vehicles. Founded in 2014, the company focuses on enhancing safety and efficiency in the transportation industry by offering automated driving software and products that assist drivers. Ottomatika collaborates with original equipment manufacturers, suppliers, and semiconductor companies to integrate its self-driving vehicle technology services. In 2015, the company was acquired by Delphi Automotive PLC, furthering its capabilities in the autonomous driving sector.