activity
20232026
most citedFollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling

88 citations · 160 across the 15 of their papers we have counts for

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Showing 2024Show all

9 papers · 1 filter

cs.RO2024★ 1 cited

From Words to Wheels: Automated Style-Customized Policy Generation for Autonomous Driving

Xu Han, Xianda Chen, Zhenghan Cai +3

Autonomous driving technology has witnessed rapid advancements, with foundation models improving interactivity and user experiences. However, current autonomous vehicles (AVs) face…

cs.RO2024

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…

cs.LG2024

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…

cs.RO2024

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…

cs.AI2024

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…

cs.RO2024★ 2 cited

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…

cs.LG2024★ 1 cited

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…

cs.AI2024

Generating and Evolving Reward Functions for Highway Driving with Large Language Models

Xu Han, Qiannan Yang, Xianda Chen +2

Reinforcement Learning (RL) plays a crucial role in advancing autonomous driving technologies by maximizing reward functions to achieve the optimal policy. However, crafting these…

cs.AI2024★ 61 cited

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…