activity
20202026
most citedLeveraging Vehicle Connectivity and Autonomy to Stabilize Flow in Mixed Traffic Conditions: Accounting for Human-driven Vehicle Driver Behavioral Heterogeneity and Perception-reaction Time Delay

23 citations · 50 across the 19 of their papers we have counts for

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8 papers · 1 filter

cs.LG2026

Geometry-Aware Infrastructure-Anchored Denoiser for UWB Sensing and Work-Zone Reconstruction

Weizhe Tang, Jiaxi Liu, Junwei you +5

Accurate work-zone geometry perception is critical for intelligent transportation systems, and ultra-wideband sensing offers a low-cost approach for infrastructure-aided reconstruc…

cs.LG2026

PILD: Physics-Informed Learning via Diffusion

Tianyi Zeng, Tianyi Wang, Jiaru Zhang +7

Diffusion models have emerged as powerful generative tools for modeling complex data distributions, yet their purely data-driven nature limits applicability in engineering and scie…

cs.LG20241 cited

Crossfusor: A Cross-Attention Transformer Enhanced Conditional Diffusion Model for Car-Following Trajectory Prediction

Junwei You, Haotian Shi, Keshu Wu +4

Vehicle trajectory prediction is crucial for advancing autonomous driving and advanced driver assistance systems (ADAS), enhancing road safety and traffic efficiency. While traditi…

cs.LG2024

HAIM-DRL: Enhanced Human-in-the-loop Reinforcement Learning for Safe and Efficient Autonomous Driving

Zilin Huang, Zihao Sheng, Chengyuan Ma +1

Despite significant progress in autonomous vehicles (AVs), the development of driving policies that ensure both the safety of AVs and traffic flow efficiency has not yet been fully…

cs.LG2023

A Physics Enhanced Residual Learning (PERL) Framework for Vehicle Trajectory Prediction

Keke Long, Zihao Sheng, Haotian Shi +3

In vehicle trajectory prediction, physics models and data-driven models are two predominant methodologies. However, each approach presents its own set of challenges: physics models…

cs.LG20233 cited

EPG-MGCN: Ego-Planning Guided Multi-Graph Convolutional Network for Heterogeneous Agent Trajectory Prediction

Zihao Sheng, Zilin Huang, Sikai Chen

To drive safely in complex traffic environments, autonomous vehicles need to make an accurate prediction of the future trajectories of nearby heterogeneous traffic agents (i.e., ve…