Intempora S.A, a software editor specialized in real-time multi-sensor software solutions, unveils IVS – Intempora Validation Suite – a new set of cutting-edge software tools for cloud-based testing and validation of perception and deep learning algorithms and relies on big-data and high-performing architecture provided by Microsoft Azure for managing high-volumes of recorded automotive sensors data.
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Autonomous driving has become the next challenge and strategic area for the whole automotive industry. Today, test systems and prototype vehicles are up and running around the world in order to record, simulate and process billions of kilometers. The road to fully autonomous future is tough and fraught with challenges.
A new standard called SOTIF (Safety of the Intended Functionality – ISO/PAS 21448) provides guidelines to address the way to guarantee the operational safety of functions (such as vision-based perception systems, neural network algorithms…) in the absence of a fault, hence complementing the functional safety standards such as ISO 26262.
Due to the high volume of sensor data generated by autonomous vehicles (up to tens of PetaBytes), the diversity of scenarios and the unpredictability of driving situations, perception algorithms are hard to certify and automotive engineers need to find new methods and solutions to perform statistical validation since formal proof becomes too complex and unaffordable.
Among these challenges, focusing tests on relevant scenarios and corner cases considering a given function (e.g. obstacle detection, accurate positioning, etc.) is key in order to reduce the amount of kilometers to test while ensuring good situations coverage and hence optimizing the IT infrastructure resources.
Intempora unveils IVS – Intempora Validation Suite, a set of new software tools for the benchmarking, testing and validation of Advanced driver assistance systems (ADAS) and Highly Automated Driving (HAD) functions including deep learning and perception algorithms.
IVS enables automotive and IT engineers to centralize, store and share their recordings of driving datasets, annotate and index them with tags (obstacles, weather and traffic conditions, road network information, vehicle data, etc.), search for particular situations, previews results, then post-process these huge amounts of recorded driving data on parallel computing clusters in order to validate their perception algorithms with specific scenarios.
« Data management and test automation for ADAS/HAD functions validation have been a longtime request by our users all over the world, especially with their huge amount of recorded autonomous driving sensors datasets. Today we are proud to release the Intempora Validation suite (IVS) powered by Microsoft Azure to answer the needs of the automotive industry »
Nicolas du Lac, Directeur Général de Intempora
« Intelligent data analytics and machine learning algorithms are key to the implementation of autonomous driving scenarios. By integrating IVS with Microsoft Azure‘s cloud and AI tools, Intempora helps the automotive industry tackle autonomous driving challenges that haven’t been solved yet. »
Sanjay Ravi, Directeur Général Industrie Automobile, Microsoft
With Intempora as a leading autonomous driving software company and IVS based on Azure, we aim to create with Microsoft a powerful synergy and a unique expertise in order to accelerate the deployment of intelligent vehicles on the road.
Intempora is a software editor company created in 2000, technology transfer from Center of Robotics Ecole Mines ParisTECH, one of the most famous and prestigious engineering schools in France. Intempora has among 20 years of experience in providing advanced software technologies for real-time multisensor applications such as ADAS and autonomous driving.
Intempora works with many OEMs, suppliers, engineering companies, research centers and universities evolved in research and development of autonomous driving around the world. The company ensures now a workflow and a complete toolchain from rapid prototyping, design, execution, to deployment and validation of advanced ADAS and HAD algorithms for autonomous vehicles.