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NSFDirectorate for Technology, Innovation, and Partnerships

I-Corps: Translation Potential of Mixed-Reality Technology for Scalable Validation and Testing of Advanced Vehicle Systems

Active
Institution
Clemson University, SC
Principal investigator
Yunyi Jia
Funding
$50K
Duration
2026–2027
Open portfolio

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Abstract

This I-Corps project is based on the development of a platform that combines real-world driving with virtual traffic environments to improve the testing of self-driving cars. Simulation alone cannot fully capture realistic interactions, while on-road testing is costly, time-consuming, difficult to reproduce, and often unable to safely evaluate rare but critical scenarios. This technology enables real vehicles to interact with virtual vehicles, pedestrians, traffic controls, and complex traffic events in real time, providing a scalable, repeatable, and cost-effective approach to testing self-driving cars. By combining the advantages of simulation and physical testing, this technology may enable scalable, cost-effective, and repeatable validation of challenging driving scenarios that are otherwise difficult or unsafe to evaluate. This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of a mixed-reality validation platform for advanced driver assistance systems (ADAS) and autonomous driving technologies. This technology integrates physical vehicles operating on real roads with synchronized virtual traffic participants and driving scenarios to create realistic, repeatable, and safety-critical testing environments that are difficult or impractical to reproduce using existing validation methods. The platform allows autonomous or human-driven vehicles to safely interact with simulated vehicles, pedestrians, traffic signals, and complex driving events while maintaining the realism of real-world driving conditions. Unlike conventional simulation or road testing alone, the platform combines the realism of physical vehicle operation with the flexibility and scalability of virtual scenario generation, enabling comprehensive evaluation of vehicle behavior under diverse operating conditions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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Directorate for Technology, Innovation, and Partnerships01002627DB NSF RESEARCH & RELATED ACTIVITI-Corpsscenarioslearningphysicalcostlycomprehensivefullyimpracticalunderintellectualcannot

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