collaborators

6 papers

cs.SD2025

MRSAudio: A Large-Scale Multimodal Recorded Spatial Audio Dataset with Refined Annotations

Wenxiang Guo, Changhao Pan, Zhiyuan Zhu +16

Humans rely on multisensory integration to perceive spatial environments, where auditory cues enable sound source localization in three-dimensional space. Despite the critical role…

cs.LG2025

A Hierarchical Deep Reinforcement Learning Framework for Traffic Signal Control with Predictable Cycle Planning

Hankang Gu, Yuli Zhang, Chengming Wang +4

Deep reinforcement learning (DRL) has become a popular approach in traffic signal control (TSC) due to its ability to learn adaptive policies from complex traffic environments. Wit…

cs.SD2025

Adaptive Vehicle Speed Classification via BMCNN with Reinforcement Learning-Enhanced Acoustic Processing

Yuli Zhang, Pengfei Fan, Ruiyuan Jiang +3

Traffic congestion remains a pressing urban challenge, requiring intelligent transportation systems for real-time management. We present a hybrid framework that combines deep learn…

cs.LG2025

A Joint Topology-Data Fusion Graph Network for Robust Traffic Speed Prediction with Data Anomalism

Ruiyuan Jiang, Dongyao Jia, Eng Gee Lim +3

Accurate traffic prediction is essential for Intelligent Transportation Systems (ITS), yet current methods struggle with the inherent complexity and non-linearity of traffic dynami…

cs.SD2025

Integrating Vehicle Acoustic Data for Enhanced Urban Traffic Management: A Study on Speed Classification in Suzhou

Pengfei Fan, Yuli Zhang, Xinheng Wang +4

This study presents and publicly releases the Suzhou Urban Road Acoustic Dataset (SZUR-Acoustic Dataset), which is accompanied by comprehensive data-acquisition protocols and annot…

cs.AI2025

Toward Dependency Dynamics in Multi-Agent Reinforcement Learning for Traffic Signal Control

Yuli Zhang, Shangbo Wang, Dongyao Jia +4

Reinforcement learning (RL) emerges as a promising data-driven approach for adaptive traffic signal control (ATSC) in complex urban traffic networks, with deep neural networks subs…