CASIA OpenIR
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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:163/5  |  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)  
Social relation and physical lane aggregator: integrating social and physical features for multimodal motion prediction 期刊论文
Journal of Intelligent and Connected Vehicles, 2022, 卷号: 5, 期号: 3, 页码: 302-308
作者:  Chen QY(陈启元);  Wei ZB(魏泽兵);  Wang X(王晓);  Li LX(李灵犀);  Lv YS(吕宜生)
Adobe PDF(1118Kb)  |  收藏  |  浏览/下载:121/31  |  提交时间:2023/06/26
Improving Road Detection Results Based on Ensemble Learning and Key Samples Focusing 会议论文
Proceedings of the IEEE International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece; Online, 2020-9-20
作者:  Fan, Siqi;  Zhu, Fenghua;  Zhang, Hui;  Lv, Yisheng;  Wang, Xiao;  Xiong, Gang;  Wang, Feiyue
Adobe PDF(2270Kb)  |  收藏  |  浏览/下载:256/57  |  提交时间:2022/06/16
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:192/0  |  提交时间:2022/01/27
Vehicles  Safety  Accidents  Sensors  Prototypes  Autonomous vehicles  Automation  Autonomous vehicles  driving safety  social interaction  
Taxi Demand Prediction Using Parallel Multi-Task Learning Model 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2020, 卷号: 99, 期号: 1, 页码: 1-10
作者:  Chizhan Zhang;  Fenghua Zhu;  Xiao Wang;  Leilei Sun;  Haina Tang;  Yisheng Lv
浏览  |  Adobe PDF(3947Kb)  |  收藏  |  浏览/下载:229/91  |  提交时间:2020/10/15
Taxi demand prediction, pick-up/drop-off demand, multi-task learning, LSTM, deep learning