Ruiyuan Jiang

According to our database, Ruiyuan Jiang authored at least 18 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

DRiVe: An Enhanced Coupling Design of Demand Prediction and Repositioning for Shared Autonomous Vehicle Systems.

Yang Jin, Ruiyuan Jiang, Chengming Wang, Dongyao Jia, Dong Ngoduy, Xiaobin Tan, Jianping Wang

IEEE Trans. Veh. Technol., May, 2026

A joint topology-data fusion graph network for robust traffic speed prediction with data anomalism.

Ruiyuan Jiang, Dongyao Jia, Eng Gee Lim, Pengfei Fan, Yuli Zhang, Shangbo Wang

Inf. Sci., 2026

A novel hybrid macroscopic fundamental diagram-informed deep learning method for lane-level traffic prediction.

Ruiyuan Jiang, Shangbo Wang, Bingyi Liu, Yuli Zhang, Pengfei Fan, Dongyao Jia

Inf. Fusion, 2026

Quantum MDS codes induced by the projective linear transformation.

Fengwei Li, Yuting Liu, Ruiyuan Jiang

Finite Fields Their Appl., 2026

2025

New MDS and self-dual generalized Roth-Lempel codes as well as their deep holes.

Fengwei Li, Ruiyuan Jiang, Yuting Liu

Des. Codes Cryptogr., November, 2025

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

Yuli Zhang, Pengfei Fan, Ruiyuan Jiang, Hankang Gu, Dongyao Jia, Xinheng Wang

CoRR, September, 2025

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

Pengfei Fan, Yuli Zhang, Xinheng Wang, Ruiyuan Jiang, Hankang Gu, Dongyao Jia, Shangbo Wang

CoRR, June, 2025

An Adaptive Prediction Model for Randomly Distributed Traffic Data in Urban Road Networks.

Ruiyuan Jiang, Shangbo Wang, Dongyao Jia, Guoqiang Mao, Eng Gee Lim

IEEE Trans. Veh. Technol., May, 2025

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

Yuli Zhang, Shangbo Wang, Dongyao Jia, Pengfei Fan, Ruiyuan Jiang, Hankang Gu, Andy H. F. Chow

CoRR, February, 2025

A knowledge-informed dynamic correlation modeling framework for lane-level traffic flow prediction.

Ruiyuan Jiang, Shangbo Wang, Wei Ma, Yuli Zhang, Pengfei Fan, Dongyao Jia

Inf. Fusion, 2025

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

Hankang Gu, Yuli Zhang, Chengming Wang, Ruiyuan Jiang, Ziheng Qiao, Pengfei Fan, Dongyao Jia

Proceedings of the 28th IEEE International Conference on Intelligent Transportation Systems, 2025

A Survey on RL-Based Approaches for Traffic Signal and Joint Vehicle-Signal Control.

Yuli Zhang, Pengfei Fan, Ruiyuan Jiang, Hankang Gu, Chengming Wang, Shangbo Wang, Dongyao Jia

Proceedings of the 11th International Conference on Computing and Artificial Intelligence, 2025

An Adaptive Multi-Source Correlation Fusion Approach for Lane-Level Traffic Flow Prediction.

Ruiyuan Jiang, Pengfei Fan, Chengming Wang, Yuli Zhang, Shangbo Wang, Dongyao Jia

Proceedings of the 11th International Conference on Computing and Artificial Intelligence, 2025

An Innovative Approach for Vehicle Speed Recognition through Noise Emission Analysis by Using Machine Learning.

Pengfei Fan, Yuli Zhang, Ruiyuan Jiang, Xinheng Wang, Chengming Wang, Shangbo Wang, Benson Zhu, Chenhao Wen

Proceedings of the 11th International Conference on Computing and Artificial Intelligence, 2025

2023

A Dynamic Temporal Self-attention Graph Convolutional Network for Traffic Prediction.

Ruiyuan Jiang, Shangbo Wang, Yuli Zhang

CoRR, 2023

Large-Scale Traffic Signal Control by a Nash Deep Q-network Approach.

Yuli Zhang, Shangbo Wang, Ruiyuan Jiang

CoRR, 2023

A Joint Traffic Flow Estimation and Prediction Approach for Urban Networks.

Ruiyuan Jiang, Shangbo Wang, Yuli Zhang, Valerio Selis

Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2023

Large-Scale Traffic Signal Control by a Nash Deep Q-network Approach.

Yuli Zhang, Shangbo Wang, Xiaoguang Ma, Wenwei Yue, Ruiyuan Jiang

Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems, 2023