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CASIA OpenIR
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Foundation Models for Transportation Intelligence: ITS Convergence in TransVerse 期刊论文
IEEE Intelligent Systems, 2022, 卷号: 37, 期号: 6, 页码: 77-82
作者:  Zhao, Chen;  Dai, Xingyuan;  Yisheng Lv;  Tian, Yonglin;  Ren, Yuhai;  Wang, Fei-Yue
Adobe PDF(2790Kb)  |  收藏  |  浏览/下载：32/9  |  提交时间：2024/05/28
DeCAST in TransVerse for Parallel Intelligent Transportation Systems and Smart Cities: Three Decades and Beyond 期刊论文
IEEE Intelligent Transportation Systems Magazine, 2022, 卷号: 14, 期号: 6, 页码: 6-17
作者:  Zhao, Chen;  Lv, Yisheng;  Jin, Junchen;  Tian, Yonglin;  Wang, Jiangong;  Wang, Fei-Yue
Adobe PDF(2979Kb)  |  收藏  |  浏览/下载：39/13  |  提交时间：2024/05/28
Parallel Transportation in TransVerse: From Foundation Models to DeCAST 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 卷号: 24, 期号: 12, 页码: 15310-15327
作者:  Zhao, Chen;  Wang, Xiao;  Lv, Yisheng;  Tian, Yonglin;  Lin, Yilun;  Wang, Fei-Yue
Adobe PDF(4139Kb)  |  收藏  |  浏览/下载：181/9  |  提交时间：2023/11/16
Intelligent Transportation Systems (ITS)  Cyber-Physical-Social Systems (CPSS)  Artificial Systems, Computational Experiments, Parallel Execution (ACP)  Decentralized/Distributed Autonomous Operations and Organizations (DAO)  
A Semi-supervised End-to-end Framework for Transportation Mode Detection by Using GPS-enabled Sensing Devices 期刊论文
IEEE Internet of Things Journal, 2022, 卷号: 9, 期号: 10, 页码: 7842-7852
作者:  Zhishuai Li;  Gang Xiong;  Zebing Wei;  YIsheng Lv;  Noreen Anwar;  Fei-Yue Wang
Adobe PDF(2754Kb)  |  收藏  |  浏览/下载：234/72  |  提交时间：2022/04/08
Transportation mode detection , Semi-supervised learning, Human mobility , GPS trajectory.  
AdapGL: An adaptive graph learning algorithm for traffic prediction based on spatiotemporal neural networks 期刊论文
Transportation Research Part C, 2022, 期号: 99, 页码: 1-1
作者:  Wei Zhang;  Fenghua Zhu;  Yisheng Lv;  Chang Tan;  Wen Liu;  Xin Zhang;  Fei-Yue Wang
Adobe PDF(2619Kb)  |  收藏  |  浏览/下载：415/137  |  提交时间：2022/04/08
Adaptive graph learning, Traffic prediction, Graph convolutional network, Expectation maximization, Deep learning  
Traffic Signal Timing via Deep Reinforcement Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2016, 期号: 3, 页码: 247-254
作者:  Li Li;  Lv YS(吕宜生);  Fei-Yue Wang
Adobe PDF(509Kb)  |  收藏  |  浏览/下载：79/39  |  提交时间：2022/04/08
Traffic control , reinforcement learning , deep learning , deep reinforcement learning  
Three Principles to Determine the Right-of-Way for AVs: Safe Interaction With Humans 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 23, 期号: 7, 页码: 16
作者:  Li, Li;  Zhao, Can;  Wang, Xiao;  Li, Zhiheng;  Chen, Long;  Lv, Yisheng;  Zheng, Nan-Ning;  Wang, Fei-Yue
收藏  |  浏览/下载：200/0  |  提交时间：2022/01/27
Vehicles  Safety  Accidents  Sensors  Prototypes  Autonomous vehicles  Automation  Autonomous vehicles  driving safety  social interaction  
Acting As A Decision Maker: Traffic-Condition-Aware Ensemble Learning for Traffic Flow Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 期号: Accepted, 页码: Accepted
作者:  Yuanyuan Chen;  Hongyu Chen;  Peijun Ye;  Yisheng Lv;  Fei-Yue Wang
浏览  |  Adobe PDF(2382Kb)  |  收藏  |  浏览/下载：303/63  |  提交时间：2020/10/16
Traffic Flow Prediction  Ensemble Learning  Deep Learning  
Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2020, 卷号: 21, 期号: 10, 页码: 4063 - 4071
作者:  Fenghua Zhu;  Yisheng Lv;  Yuanyuan Chen;  Xiao Wang;  Gang Xiong;  Fei-Yue Wang
浏览  |  Adobe PDF(2879Kb)  |  收藏  |  浏览/下载：483/235  |  提交时间：2020/10/15
Intelligent transportation systems  
Traffic Flow Imputation Using Parallel Data and Generative Adversarial Networks 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 卷号: 21, 期号: 4, 页码: 1624-1630
作者:  Chen, Yuanyuan;  Lv, Yisheng;  Wang, Fei-Yue
浏览  |  Adobe PDF(2070Kb)  |  收藏  |  浏览/下载：394/67  |  提交时间：2020/06/02
Generators  Data models  Gallium nitride  Generative adversarial networks  Training  Loss measurement  Biological system modeling  Parallel data  generative adversarial networks  traffic flow imputation  data augmentation  deep learning