Austin, TX, United States of America

Pratik Shivarkar


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2023-2025

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2 patents (USPTO):Explore Patents

Title: Innovator Profile: Pratik Shivarkar

Introduction

Pratik Shivarkar is an inventive mind based in Austin, Texas, known for his contributions in the field of connected vehicle infrastructure. With a single filed patent, Pratik showcases his expertise in vehicle traffic data evaluation and its applications in modern transportation systems.

Latest Patents

Pratik's notable patent is titled "System and Method for Vehicle Queue Length Detection in a Connected Vehicle Infrastructure Environment." This innovative system focuses on determining the vehicle queue length by evaluating vehicle traffic data from multiple vehicles. The system utilizes a processor with executable instructions to analyze basic safety messages, create a geometric representation of vehicle queues, and aggregate data to calculate the overall length of the queue based on segment lengths. This advancement not only enhances traffic management but also contributes significantly to the efficiency of connected vehicle technologies.

Career Highlights

Currently, Pratik is working with Yunex GmbH, where he leverages his skills and knowledge to further innovate in the field of vehicle infrastructure technology. His commitment to improving transportation systems reflects his dedication as an inventor and a professional in the industry.

Collaborations

While there is limited information available regarding specific collaborations, Pratik's role at Yunex GmbH implies that he is part of a broader team dedicated to pioneering advancements and solving complex problems in the field of connectivity and vehicle management.

Conclusion

Pratik Shivarkar stands out as a significant figure in innovative transportation solutions, specifically through his patented work on vehicle queue detection systems. As the connected vehicle landscape continues to evolve, his contributions hold the potential to influence future developments in traffic management and safety.

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