Intelligent Driver Model

The Intelligent Driver Model (IDM) is a widely used microscopic traffic simulation model aiming to realistically replicate human car-following behavior. Current research focuses on improving IDM's accuracy and adaptability through techniques like incorporating vehicle dynamics, integrating reinforcement learning for fuel efficiency and safety optimization, and using meta-learning for personalized driver modeling. These advancements enhance the model's predictive power and interpretability, leading to improved traffic simulation, autonomous vehicle testing, and the development of safer and more efficient driving assistance systems.