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    • This project contains the source code and data for the paper titled "Adaptive Safety Performance Testing for Autonomous Vehicles with Adaptive Importance Sampling".
      Jupyter Notebook
      0100Updated Nov 6, 2025Nov 6, 2025
    • This project contains the source code and data for the paper titled "Adaptive Safety Evaluation for Connected and Automated Vehicles with Sparse Control Variates".
      Jupyter Notebook
      0100Updated Nov 6, 2025Nov 6, 2025
    • This project contains the source code and data for the paper titled "Adaptive Testing Environment Generation for Connected and Automated Vehicles with Dense Reinforcement Learning".
      Jupyter Notebook
      0100Updated Nov 6, 2025Nov 6, 2025
    • A Multimodal Large Language Model–Driven Framework for Generating Corner Cases in Autonomous Vehicle Testing Using Real-World Data
      Python
      0100Updated Oct 26, 2025Oct 26, 2025
    • This project contains the source code for the paper titled "A Provable Safety Metric for Autonomous Driving via Deep Reinforcement Learning and PAC Verification". We propose a real-time automonous driving safety metric called Provable Minimum Collision Time (PMCT) that provably predict the minimum time to collision from the inputed initial state.
      Python
      0100Updated Sep 4, 2025Sep 4, 2025