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Found 4 papers, 1 papers with code
LC-LLM: Explainable Lane-Change Intention and Trajectory Predictions with Large Language Models
To the best of our knowledge, this is the first attempt to utilize LLMs for predicting lane change behavior.
EnsembleFollower: A Hybrid Car-Following Framework Based On Reinforcement Learning and Hierarchical Planning
The experimental results illustrate that EnsembleFollower yields improved accuracy of human-like behavior and achieves effectiveness in combining hybrid models, demonstrating that our proposed framework can handle diverse car-following conditions by leveraging the strengths of various low-level models.
EquiDiff: A Conditional Equivariant Diffusion Model For Trajectory Prediction
The growing popularity of deep learning has led to the development of numerous methods for trajectory prediction.
FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling
To address this gap and promote the development of microscopic traffic flow modeling, we establish a public benchmark dataset for car-following behavior modeling.
