15 citations · 16 across the 9 of their papers we have counts for
9 papers
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…
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…
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…
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…
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…
Communication Strategy on Macro-and-Micro Traffic State in Cooperative Deep Reinforcement Learning for Regional Traffic Signal Control
Hankang Gu, Shangbo Wang, Dongyao Jia +5
Adaptive Traffic Signal Control (ATSC) has become a popular research topic in intelligent transportation systems. Regional Traffic Signal Control (RTSC) using the Multi-agent Deep…
A Dynamic Temporal Self-attention Graph Convolutional Network for Traffic Prediction
Ruiyuan Jiang, Shangbo Wang, Yuli Zhang
Accurate traffic prediction in real time plays an important role in Intelligent Transportation System (ITS) and travel navigation guidance. There have been many attempts to predict…
Large-Scale Traffic Signal Control by a Nash Deep Q-network Approach
Yuli. Zhang, Shangbo. Wang, Ruiyuan. Jiang
Reinforcement Learning (RL) is currently one of the most commonly used techniques for traffic signal control (TSC), which can adaptively adjusted traffic signal phase and duration…
The Direction-Aware, Learnable, Additive Kernels and the Adversarial Network for Deep Floor Plan Recognition
Yuli Zhang, Yeyang He, Shaowen Zhu +1
This paper presents a new approach for the recognition of elements in floor plan layouts. Besides of elements with common shapes, we aim to recognize elements with irregular shapes…