Anil Babu Yadav Jenige

•Developed a safety-oriented autonomous driving decision framework integrating multi-sensor fault simulation, runtime monitoring, sensor Built-In Self-Test (BIST), and safety-caged LLM supervision for intersection handling in automated vehicles. •Designed and implemented a comparative evaluation pipeline for multiple LLMs including DeepSeek- LLM, Phi-3 Mini, DeepSeek Coder, and Falcon3, using structured safety and reliability metrics such as oracle pass rate, calibration error (ECE), BERTScore, latency

•Research on traditional validation methods, conducted an in-depth literature review on scenario-based validation, explored V-model integration, and evaluated Euro NCAP cut-in scenarios; identified & documented scenario evaluation metrics for future use in IPEK’s LLM-based scenario generation approach. •Developed a project homepage for IPEK, implemented and tested one selected scenario evaluation metric on a sample dataset, & validated abstract scenario outputs generated by AI-based scenario design tools.

•Analysed customer inquiries and enhanced communication strategies, resulting in a 25% increase in follow- up appointments. •Explained vehicle faults, maintenance needs, and estimated costs to customers; obtained approvals for additional part replacements, ensuring transparency and customer satisfaction during periodic maintenance services (PMS).

Autonomous driving, Artificial intelligence, Machine Learning, Software engineering.