Wipro has been granted a patent for a method and system to validate Autonomous Vehicle (AV) stacks. The technology involves receiving Operational Design Domain (ODD) and real-world data, simulating driving scenarios, and determining performance metrics. The method adjusts complexity 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.

According to GlobalData’s company profile on Wipro, Hybrid cloud mgmt was a key innovation area identified from patents. Wipro's grant share as of April 2024 was 62%. Grant share is based on the ratio of number of grants to total number of patents.

Method for validating autonomous vehicle (av) stack

Source: United States Patent and Trademark Office (USPTO). Credit: Wipro Ltd

A recently granted patent (Publication Number: US11919530B2) outlines a method for validating an Autonomous Vehicle (AV) stack using an Advanced Driver Assistance System (ADAS) and AV testing device. The method involves receiving an Operational Design Domain (ODD) and real-world data to simulate the ADAS and AV, generating driving scenarios based on the ODD and real-world data, simulating the ADAS and AV, determining performance metrics, and adjusting the complexity of the driving scenario based on predefined thresholds. The method also includes generating evaluation reports, determining sequential tasks for the ADAS and AV, visualizing dynamic models of AVs and the environment, and generating virtual environment data.

Furthermore, the patent describes a system for validating an AV stack, comprising a processor and a computer-readable medium storing instructions for executing the validation process. The system receives ODD and real-world data, generates driving scenarios, simulates the ADAS and AV, determines performance metrics, and adjusts the complexity of the scenario based on predefined thresholds. Additional features of the system include maintaining complexity levels, generating evaluation reports, determining sequential tasks, visualizing dynamic models, and generating virtual environment data. The performance metrics evaluated include distance, speed, accidents, perception, driving quality, and ride quality metrics, ensuring a comprehensive validation process for AV technology.

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