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AUTOSIM: Automated Urban Traffic Operation Simulation via Meta-Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 9, 页码: 1871-1881
作者:  Yuanqi Qin;  Wen Hua;  Junchen Jin;  Jun Ge;  Xingyuan Dai;  Lingxi Li;  Xiao Wang;  Fei-Yue Wang
Adobe PDF(3244Kb)  |  收藏  |  浏览/下载：88/17  |  提交时间：2023/08/10
Conditional generative adversarial network  signalized urban networks  short-term link speed prediction  
An Agent-Based Traffic Recommendation System: Revisiting and Revising Urban Traffic Management Strategies 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 页码: 13
作者:  Jin, Junchen;  Rong, Dingding;  Pang, Yuqi;  Ye, Peijun;  Ji, Qingyuan;  Wang, Xiao;  Wang, Ge;  Wang, Fei-Yue
收藏  |  浏览/下载：242/0  |  提交时间：2022/07/25
Switches  Control systems  Timing  Task analysis  Behavioral sciences  Analytical models  Research and development  Agent-based recommendation system  deep recommendation  human-in-the-loop  operation on-demand  traffic management strategies  
基于动态示教数据和行为克隆的深度Q学习网络优化方法 专利
专利类型: 发明专利, 专利号: ZL202011338992.0, 申请日期: 2021-06-29,
发明人:  李小双;  王晓;  王飞跃;  金峻臣;  陈薏竹
Adobe PDF(1330Kb)  |  收藏  |  浏览/下载：210/53  |  提交时间：2022/06/21
Deep Imitation Learning for Traffic Signal Control and Operations Based on Graph Convolutional Neural Networks 会议论文
, Rhodes, Greece, 2020-9
作者:  Li Xiaoshuang;  Guo Zhongzheng;  Dai Xingyuan;  Lin Yilun;  Jin Junchen;  Zhu Fenghua;  Wang Fei-Yue
Adobe PDF(314Kb)  |  收藏  |  浏览/下载：211/72  |  提交时间：2022/06/16
A GAN-Based Short-Term Link Traffic Prediction Approach for Urban Road Networks Under a Parallel Learning Framework 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 12
作者:  Jin, Junchen;  Rong, Dingding;  Zhang, Tong;  Ji, Qingyuan;  Guo, Haifeng;  Lv, Yisheng;  Ma, Xiaoliang;  Wang, Fei-Yue
收藏  |  浏览/下载：247/0  |  提交时间：2022/06/06
Roads  Predictive models  Data models  Recurrent neural networks  Generators  Computer architecture  Deep learning  Short-term link speed prediction  signalized urban networks  Wasserstein generative adversarial network  
PRECOM: A Parallel Recommendation Engine for Control, Operations, and Management on Congested Urban Traffic Networks 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 23, 期号: 7, 页码: 11
作者:  Jin, Junchen;  Rong, Dingding;  Pang, Yuqi;  Zhu, Fenghua;  Guo, Haifeng;  Ma, Xiaoliang;  Wang, Fei-Yue
收藏  |  浏览/下载：187/0  |  提交时间：2022/01/27
Engines  Control systems  Urban areas  Process control  Roads  Generators  Spatiotemporal phenomena  Spatial-temporal recommender system  urban traffic control  parallel traffic management  human-in-the-loop system  
Data Augmented Deep Behavioral Cloning for Urban Traffic Control Operations Under a Parallel Learning Framework 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 23, 期号: 6, 页码: 5128-5137
作者:  Li, Xiaoshuang;  Ye, Peijun;  Jin, Junchen;  Zhu, Fenghua;  Wang, Fei-Yue
Adobe PDF(2319Kb)  |  收藏  |  浏览/下载：300/59  |  提交时间：2022/01/27
Generative adversarial networks  Data models  Gallium nitride  Task analysis  Complex systems  Intelligent traffic signal operations  deep behavioral cloning  
SADRL: Merging human experience with machine intelligence via supervised assisted deep reinforcement learning 期刊论文
NEUROCOMPUTING, 2022, 卷号: 467, 页码: 300-309
作者:  Li, Xiaoshuang;  Wang, Xiao;  Zheng, Xinhu;  Jin, Junchen;  Huang, Yanhao;  Zhang, Jun Jason;  Wang, Fei-Yue
Adobe PDF(1244Kb)  |  收藏  |  浏览/下载：295/65  |  提交时间：2021/12/28
Deep reinforcement learning  Behavioral cloning  Dynamic demonstration  Double DQN  
An End-to-End Recommendation System for Urban Traffic Controls and Management Under a Parallel Learning Framework 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 22, 期号: 3, 页码: 1616-1626
作者:  Jin, Junchen;  Guo, Haifeng;  Xu, Jia;  Wang, Xiao;  Wang, Fei-Yue
收藏  |  浏览/下载：206/0  |  提交时间：2021/04/27
Control systems  Urban areas  Timing  Adaptive systems  Real-time systems  Recurrent neural networks  Process control  Intelligent traffic control  traffic signal control  parallel learning  recommendation systems  deep neural networks