How the Sim4CAMSens project aims to forge a robust perception sensor ecosystem.
In a rapidly evolving automotive landscape, the promise of autonomous vehicles heralds a new era of mobility characterized by efficiency, lowered operational costs and enhanced safety. Significant investments are being funneled into the development and deployment of AVs, with a critical emphasis on ensuring their safety to satisfy regulators. At the heart of this venture lies the indispensable role of simulation in the development and safety assurance of AVs, especially given the vast array of sensor types and the numerous factors affecting sensor performance. The challenges extend to the massive and diverse spectrum of training data required, and the vital need to establish the credibility of simulations. The Sim4CAMSens project seeks to address these challenges by developing and maturing a modeling and simulation supply chain specifically for perception sensor development and testing.
ADAS & Autonomous Vehicle International Magazine – January 2024 Issue
The Sim4CAMSens project is a collaborative effort of innovation aimed at nurturing the simulation, modeling and physical testing ecosystem for the developers of connected and automated mobility (CAM) perception sensors and systems. The project endeavors to construct a robust supply chain to elevate the quality of modeling, simulation, test and characterization capability. This initiative hopes to accelerate and de-risk the design, development, validation and utilization of perception sensors and the algorithms crucial for automated driving functions. By forging clear links between tools, methodologies, standards and safety cases, Sim4CAMSens is setting a course toward state-of-the-art modeling and simulation environments. These environments are anticipated to generate synthetic training data of requisite quality for training the AI systems employed in AVs.
The collaborative spirit of Sim4CAMSens manifests in its assembly of a world-class consortium of expert partners dedicated to fostering an emerging perception sensors and systems industry. The project is led by Claytex and includes rFpro, Oxford RF, Syselek, NPL, WMG, Compound Semiconductor Applications Catapult and AESIN. It is supported by funding from the UK’s Centre for Connected and Autonomous Vehicles as part of its Commercialising CAM program.
Read the full article here: Team effort
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