Wipro has patented a method and system for validating Autonomous Vehicle (AV) stacks. The technology involves receiving Operational Design Domain (ODD) and real-world data, generating driving scenarios, simulating ADAS and AV algorithms, and determining performance metrics. The complexity of scenarios increases based on predefined thresholds. GlobalData’s report on Wipro gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Method for validating autonomous vehicle (av) stack
A recently granted patent (Publication Number: US11919530B2) outlines a method for validating an Autonomous Vehicle (AV) stack through a series of steps. The method involves receiving an Operational Design Domain (ODD) and real-world data to simulate an Advanced Driver Assistance System (ADAS) and the AV. For each iteration, a driving scenario is generated based on the ODD and real-world data, simulating the ADAS and AV, and determining performance metrics. If the performance metrics exceed a predefined threshold within a set number of iterations, the complexity of the driving scenario is increased based on various factors like the AV features, map location, traffic rules, sensor configuration, and past scenarios. The method also includes maintaining the complexity level if the performance metrics are below the threshold, generating an evaluation report, determining sequential tasks, and visualizing a dynamic model of AVs and the environment.
Furthermore, the patent also describes a system for validating an AV stack, comprising a processor and a computer-readable medium storing instructions to execute the validation method. The system receives ODD and real-world data, generates driving scenarios, simulates the ADAS and AV, determines performance metrics, and adjusts the complexity level based on the metrics. Additional features include maintaining complexity levels, generating evaluation reports, determining sequential tasks, visualizing dynamic models of AVs and the environment, and generating virtual environment data. The system aims to provide a comprehensive validation process for AVs, ensuring their performance meets predefined standards and can adapt to varying levels of complexity in driving scenarios.
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