Vehicle Data

Vehicle data analysis is a rapidly evolving field focused on leveraging the massive datasets generated by modern vehicles to improve safety, efficiency, and automation in transportation. Current research emphasizes developing robust methods for data processing, including federated learning to address privacy concerns and deep learning architectures like convolutional neural networks, recurrent neural networks (LSTMs), and transformers for tasks such as anomaly detection, trajectory prediction, and driver behavior analysis. These advancements are crucial for enhancing autonomous driving systems, optimizing traffic management, and improving road safety through data-driven insights and predictive modeling.