88 citations · 160 across the 15 of their papers we have counts for
15 papers
LongStream: Long-Sequence Streaming Autoregressive Visual Geometry
Chong Cheng, Xianda Chen, Tao Xie +5
Long-sequence streaming 3D reconstruction remains a significant open challenge. Existing autoregressive models often fail when processing long sequences because they anchor poses t…
Safety-Critical Traffic Simulation with Guided Latent Diffusion Model
Mingxing Peng, Ruoyu Yao, Xusen Guo +3
Safety-critical traffic simulation plays a crucial role in evaluating autonomous driving systems under rare and challenging scenarios. However, existing approaches often generate u…
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…
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…
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…
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…
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…
BEVGPT: Generative Pre-trained Large Model for Autonomous Driving Prediction, Decision-Making, and Planning
Pengqin Wang, Meixin Zhu, Hongliang Lu +5
Prediction, decision-making, and motion planning are essential for autonomous driving. In most contemporary works, they are considered as individual modules or combined into a mult…
EnsembleFollower: A Hybrid Car-Following Framework Based On Reinforcement Learning and Hierarchical Planning
Xu Han, Xianda Chen, Meixin Zhu +3
Car-following models have made significant contributions to our understanding of longitudinal driving behavior. However, they often exhibit limited accuracy and flexibility, as the…
EquiDiff: A Conditional Equivariant Diffusion Model For Trajectory Prediction
Kehua Chen, Xianda Chen, Zihan Yu +2
Accurate trajectory prediction is crucial for the safe and efficient operation of autonomous vehicles. The growing popularity of deep learning has led to the development of numerou…
FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling
Xianda Chen, Meixin Zhu, Kehua Chen +5
Car-following is a control process in which a following vehicle (FV) adjusts its acceleration to keep a safe distance from the lead vehicle (LV). Recently, there has been a booming…