Distilling Vision-Language Models for Explainable Vehicle Collision Prediction

This repository provides the code and supporting files for reproducing the experiments reported in “Distilling Vision-Language Models for Explainable Vehicle Collision Prediction.” It includes data-processing scripts for generating collision-prone and collision-free video clips from the MM-AU and CCD datasets, dataset manifests and annotations, VLM fine-tuning and knowledge-distillation scripts, and evaluation tools. The code was developed in a Linux environment using Python 3.10 and CUDA 11.8 or later. The required dependencies are listed in `requirements.txt`.