We believe that the road to autonomous vehicle safety is via rigorous analysis & quantification. Sensmetry employs mathematical modeling techniques and large-scale data analytics to evaluate the perception, planning and control layers in the AV/ADAS stack.
Our goal is to help companies and institutions transition from lax, convoluted safety definitions to formally expressed, modular system requirements which can be independently analyzed and measured using statistical tools and big data software.
Trust is crucial in establishing safety. At Sensmetry our mission is to bring transparency and trust to the public by providing unambiguous, interpretable safety arguments that both our clients and the end-users can rely on.
Sensmetry offers consulting services and software tools for accelerating safe autonomous system development. All of our work processes and tools derive from our proprietary Probabilistic Modular Safety methodology.
We help our clients build-up a probabilistic Operational Design Domain (ODD) model. The ODD model is used to formulate a data collection & evaluation strategy and is used as an input in our statistical tools for analyzing performance.
Our software tools combine state-of-the-art statistical modeling, probabilistic programming and deep learning techniques to perform an extensive analysis of different AV/ADAS tasks (sensing, detection, tracking, trajectory planning).
Our methodology provides a formal language and a process for guiding companies through the SOTIF framework. We offer help in refining business requirements, identifying system constraints and preparing the final safety case.
Autonomous safety is a collaborative effort and we are dedicated to establishing high-quality industry-wide safety procedures. Sensmetry is an active contributor to the emerging ISO 21448 SOTIF safety standards for ADAS & autonomous vehicles.
Sensmetry was founded by researchers and engineers in order to bring mathematical rigor to the development and testing of autonomous systems.
Our team has over 40 years of combined experience in developing safety-critical automotive systems, big data and machine learning solutions.Meet the team