STRADVISION showcases advanced perception solutions alongside AMD, aiming to redefine standards in automated driving technology and enhance ADAS capabilities.
A notable collaboration in the realm of automated driving technology was announced at CES 2025, held from January 7 to 10, in Las Vegas. STRADVISION, a leader in artificial intelligence-based vision perception technology, is partnering with AMD to showcase advanced perception solutions aimed at enhancing advanced driver assistance systems (ADAS) and paving the way for fully autonomous vehicles. This partnership marks STRADVISION’s first collaboration with AMD, combining their technology capabilities to create a powerful perception stack tailored for real-world driving conditions.
At this year’s CES, STRADVISION demonstrated their 3D Perception SVNet, which utilises AMD’s Versal™ AI Edge Series Adaptive System on Chip (SoC). The demo featured an 8MP front-facing camera as part of an integrated system that promises to deliver high-performance, low-latency AI inference critical for the safety and efficacy of automated driving applications. The demonstrations were available at both STRADVISION’s booth and AMD’s automotive demonstration space.
Philip Vidal, Chief Business Officer of STRADVISION, emphasized the significance of this collaboration, stating, “Combining cutting-edge real-time processing technology from AMD with our advanced 3D perception network, ‘SVNet’ enables us to redefine industry standards for performance, reliability, and scalability in automated driving systems.” Furthermore, Wayne Lyons, Senior Director of Marketing for AMD’s Automotive Segment, remarked, “STRADVISION is helping accelerate autonomous vehicles by increasing the access to ADAS technologies by reducing its cost without compromising its capability.”
In addition to the collaboration with AMD, STRADVISION is also partnering with Texas Instruments (TI) to showcase their new TDA4VPE-Q1 automotive system-on-chip integrated with the SVNet 3D perception network. This system targets Level 2 domain controllers for ADAS and autonomous driving features, allowing vehicles to perceive their environment with increased accuracy. The TDA4VPE-Q1 boasts a high computational performance of 16 TOPS (Tera Operations Per Second) alongside various features critical for multi-camera ADAS applications.
During CES 2025, attendees were able to view live demonstrations of the SVNet technology based on the TI TDA4VPE-Q1 horticultural chip, showcasing functionalities such as Level 2+ highway driving, auto valet parking, and advanced 3D imaging for comprehensive situational awareness. Philip Vidal remarked, “The TDA4VPE-Q1 automotive SoC, paired with STRADVISION’s SVNet, exemplifies our shared vision for advancing ADAS technologies.”
The outcomes of these collaborations are poised to set a new standard for the automotive industry, as both STRADVISION and their partners aim to meet the increasing demand for scalable and efficient solutions in the rapidly evolving landscape of automated driving. With the production-ready software development set for completion in 2025, a Start of Production (SoP) target is aimed for 2026, suggesting an impending significant impact on the automotive sector.
STRADVISION, founded in 2014, has positioned itself at the forefront of AI-driven perception technology for vehicles. Their solutions have garnered accolades, including Frost & Sullivan’s 2022 Global Technology Innovation Leadership Award, and recognition at the AutoSens Awards, ultimately embodying a commitment to quality and innovation within the automotive technology field.
Source: Noah Wire Services
- https://aimagazine.com/technology/stradvision-ai-based-vision-processing-technology – Corroborates STRADVISION’s role in AI-based vision processing technology and their involvement in advancing ADAS and autonomous vehicles.
- https://www.youtube.com/watch?v=_84BrKq6IRM – Provides details on STRADVISION’s SVNet technology and its application in automotive industry, including ADAS and autonomous driving.
- https://iconnect007.com/article/130146/stradvisions-aibased-vision-perception-software-svnet-powers-adas-camera-system/130149/ein – Supports the information about SVNet software and its use in ADAS camera systems, highlighting its deep learning-based perception algorithms.
- https://stradvision.com – Official website of STRADVISION, providing comprehensive information about their technology, partnerships, and innovations in the field of AI-based vision perception.
- https://www.noahwire.com – Source of the original article, although not directly linked, it is the basis for the information provided about the collaborations and technological advancements.
- https://www.stradvision.com/about-us/ – Provides background information on STRADVISION, including its founding year and commitment to innovation in the automotive technology field.
- https://www.frost.com/about/ – Corroborates the accolades received by STRADVISION, such as Frost & Sullivan’s 2022 Global Technology Innovation Leadership Award.
- https://autosens.org/ – Supports the recognition of STRADVISION at the AutoSens Awards, highlighting their commitment to quality and innovation.
- https://www.amd.com/en/products/fpga-and-adaptive-socs/versal-ai-edge – Details AMD’s Versal AI Edge Series Adaptive System on Chip (SoC), which is used in the collaboration with STRADVISION for advanced perception solutions.
- https://www.ti.com/product/TDA4VPE-Q1 – Provides information about Texas Instruments’ TDA4VPE-Q1 automotive system-on-chip, which is integrated with STRADVISION’s SVNet 3D perception network.
- https://www.ces.tech/ – Official website of CES, where the collaborations and demonstrations by STRADVISION and their partners were showcased.
- https://news.google.com/rss/articles/CBMixAFBVV95cUxNRlFmM0tVRDAtU2prN21SWnp6SksxRlVobFhnZ1JBMHNTRDkzZ2Rtekh5eVFxeGN6YzlkU1QxeDRtLV9QNmI3clZ2c055YnVHSFlIRnBQakdBTF9XbGlGdWtHbmY3Y21JT245ZXluYm9LWjJJQnQzWm1HTFl6RkhIWTYyYmZSR2xJWUJxVjVEOWpqV0MzYlo0V0l3a1pJeHU0S2ZaYWVKV1hSdTJlcndyb0FLTFVkRGd3MVIxckhPazFBLWVl?oc=5&hl=en-US&gl=US&ceid=US:en – Please view link – unable to able to access data
