This project focuses on enhancing the current testbed for the Advanced Driver Assistance Systems (ADAS) feature. It does so by incorporating real-time weather data into the pipeline on Argonne’s On-Road Connected and Automated Vehicle (CAV) testbed. It leverages this data to train on-vehicle artificial intelligence (AI)/machine learning (ML) models for weather prediction. This project enables highly-accurate localized weather measurements on vehicles during dynamic driving scenarios. To enable localized weather prediction, the vehicle’s onboard sensors (i.e., cameras, LiDARs, and radars) are used to predict the localized weather using AI/ML.