IDM-Follower: A Model-Informed Deep Learning Method for Car-Following Trajectory Prediction
Published in IEEE Transactions on Intelligent Vehicles, 2024
We introduce a physics-informed neural network (PINN) model that integrates the Intelligent Driving Model (IDM) into a deep learning framework for car-following trajectory prediction. The proposed model exhibits robustness against real-time GPS noise.
Recommended citation: Y. Wang and Y. Feng* (2024). "IDM-Follower: A Model-Informed Deep Learning Method for Car-Following Trajectory Prediction." IEEE Transactions on Intelligent Vehicles, vol. 9, no. 6, pp. 5014-5020.
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