Naturalistic Driving Study

Naturalistic driving studies (NDS) involve collecting real-world driving data to understand driver behavior and improve traffic safety. Current research focuses on developing advanced algorithms, such as transformers and Bayesian methods, to analyze this complex data for tasks like predicting driver actions, detecting traffic conflicts, and improving car-following models. These studies are crucial for developing more effective driver-assistance systems, enhancing traffic simulation accuracy, and ultimately reducing road accidents. The use of AI, including GANs for data anonymization, is also a growing area of focus to address ethical concerns related to data privacy.