61 citations · 63 across the 6 of their papers we have counts for
6 papers
MetaFollower: Adaptable Personalized Autonomous Car Following
Xianda Chen, Kehua Chen, Meixin Zhu +5
Car-following (CF) modeling, a fundamental component in microscopic traffic simulation, has attracted increasing interest of researchers in the past decades. In this study, we prop…
Learning Car-Following Behaviors Using Bayesian Matrix Normal Mixture Regression
Chengyuan Zhang, Kehua Chen, Meixin Zhu +2
Learning and understanding car-following (CF) behaviors are crucial for microscopic traffic simulation. Traditional CF models, though simple, often lack generalization capabilities…
GRANP: A Graph Recurrent Attentive Neural Process Model for Vehicle Trajectory Prediction
Yuhao Luo, Kehua Chen, Meixin Zhu
As a vital component in autonomous driving, accurate trajectory prediction effectively prevents traffic accidents and improves driving efficiency. To capture complex spatial-tempor…
LC-LLM: Explainable Lane-Change Intention and Trajectory Predictions with Large Language Models
Mingxing Peng, Xusen Guo, Xianda Chen +2
To ensure safe driving in dynamic environments, autonomous vehicles should possess the capability to accurately predict lane change intentions of surrounding vehicles in advance an…
Risk-anticipatory autonomous driving strategies considering vehicles' weights, based on hierarchical deep reinforcement learning
Di Chen, Hao Li, Zhicheng Jin +2
Autonomous vehicles (AVs) have the potential to prevent accidents caused by drivers errors and reduce road traffic risks. Due to the nature of heavy vehicles, whose collisions caus…
Semantic-Fused Multi-Granularity Cross-City Traffic Prediction
Kehua Chen, Yuxuan Liang, Jindong Han +3
Accurate traffic prediction is essential for effective urban management and the improvement of transportation efficiency. Recently, data-driven traffic prediction methods have been…