5 papers
EcoFollower: An Environment-Friendly Car Following Model Considering Fuel Consumption
Hui Zhong, Xianda Chen, PakHin Tiu +2
To alleviate energy shortages and environmental impacts caused by transportation, this study introduces EcoFollower, a novel eco-car-following model developed using reinforcement l…
Continual Learning for Adaptable Car-Following in Dynamic Traffic Environments
Xianda Chen, PakHin Tiu, Xu Han +4
The continual evolution of autonomous driving technology requires car-following models that can adapt to diverse and dynamic traffic environments. Traditional learning-based models…
CAV-AHDV-CAV: Mitigating Traffic Oscillations for CAVs through a Novel Car-Following Structure and Reinforcement Learning
Xianda Chen, PakHin Tiu, Yihuai Zhang +2
Connected and Automated Vehicles (CAVs) offer a promising solution to the challenges of mixed traffic with both CAVs and Human-Driven Vehicles (HDVs). A significant hurdle in such…
GenFollower: Enhancing Car-Following Prediction with Large Language Models
Xianda Chen, Mingxing Peng, PakHin Tiu +4
Accurate modeling of car-following behaviors is essential for various applications in traffic management and autonomous driving systems. However, current approaches often suffer fr…
EditFollower: Tunable Car Following Models for Customizable Adaptive Cruise Control Systems
Xianda Chen, Xu Han, Meixin Zhu +4
In the realm of driving technologies, fully autonomous vehicles have not been widely adopted yet, making advanced driver assistance systems (ADAS) crucial for enhancing driving exp…