| Stacked bidirectional and unidirectional LSTM recurrent neural network for forecasting network-wide traffic state with missing values Z Cui, R Ke, Z Pu, Y Wang Transportation Research Part C: Emerging Technologies 118, 102674, 2020 | 1230* | 2020 |
| Traffic graph convolutional recurrent neural network: A deep learning framework for network-scale traffic learning and forecasting Z Cui, K Henrickson, R Ke, Y Wang IEEE Transactions on Intelligent Transportation Systems 21 (11), 4883-4894, 2019 | 1035 | 2019 |
| Deep learning architecture for short-term passenger flow forecasting in urban rail transit J Zhang, F Chen, Z Cui, Y Guo, Y Zhu IEEE Transactions on Intelligent Transportation Systems 22 (11), 7004-7014, 2020 | 217 | 2020 |
| Real-time bidirectional traffic flow parameter estimation from aerial videos R Ke, Z Li, S Kim, J Ash, Z Cui, Y Wang IEEE Transactions on Intelligent Transportation Systems 18 (4), 890-901, 2016 | 197 | 2016 |
| Forecasting transportation network speed using deep capsule networks with nested LSTM models X Ma, H Zhong, Y Li, J Ma, Z Cui, Y Wang IEEE Transactions on Intelligent Transportation Systems 22 (8), 4813-4824, 2020 | 147 | 2020 |
| Graph Markov network for traffic forecasting with missing data Z Cui, L Lin, Z Pu, Y Wang Transportation Research Part C: Emerging Technologies 117, 102671, 2020 | 124 | 2020 |
| Learning traffic as a graph: A gated graph wavelet recurrent neural network for network-scale traffic prediction Z Cui, R Ke, Z Pu, X Ma, Y Wang Transportation Research Part C: Emerging Technologies 115, 102620, 2020 | 124 | 2020 |
| Two-stream multi-channel convolutional neural network for multi-lane traffic speed prediction considering traffic volume impact R Ke, W Li, Z Cui, Y Wang Transportation Research Record 2674 (4), 459-470, 2020 | 102 | 2020 |
| A deep generative adversarial architecture for network-wide spatial-temporal traffic-state estimation Y Liang, Z Cui, Y Tian, H Chen, Y Wang Transportation Research Record 2672 (45), 87-105, 2018 | 67 | 2018 |
| Characterizing car-following behaviors of human drivers when following automated vehicles using the real-world dataset X Wen, Z Cui, S Jian Accident Analysis & Prevention 172, 106689, 2022 | 65 | 2022 |
| Road surface friction prediction using long short-term memory neural network based on historical data Z Pu, C Liu, X Shi, Z Cui, Y Wang Journal of Intelligent Transportation Systems 26 (1), 34-45, 2021 | 51 | 2021 |
| Monitoring public transit ridership flow by passively sensing Wi-Fi and Bluetooth mobile devices Z Pu, M Zhu, W Li, Z Cui, X Guo, Y Wang IEEE Internet of Things Journal 8 (1), 474-486, 2020 | 51 | 2020 |
| A vision-based hierarchical framework for autonomous front-vehicle taillights detection and signal recognition Z Cui, SW Yang, HM Tsai 2015 IEEE 18th International Conference on Intelligent Transportation …, 2015 | 46 | 2015 |
| Characterizing channel fading in vehicular visible light communications with video data Z Cui, C Wang, HM Tsai 2014 IEEE Vehicular Networking Conference (VNC), 226-229, 2014 | 44 | 2014 |
| Deep bidirectional and unidirectional LSTM recurrent neural network for network-wide traffic speed prediction. arXiv 2018 Z Cui, R Ke, Z Pu, Y Wang arXiv preprint arXiv:1801.02143, 1801 | 43 | 1801 |
| Multimodal traffic speed monitoring: A real-time system based on passive Wi-Fi and Bluetooth sensing technology Z Pu, Z Cui, J Tang, S Wang, Y Wang IEEE Internet of Things Journal 9 (14), 12413-12424, 2021 | 41 | 2021 |
| Advanced framework for microscopic and lane‐level macroscopic traffic parameters estimation from UAV video R Ke, S Feng, Z Cui, Y Wang IET Intelligent Transport Systems 14 (7), 724-734, 2020 | 40 | 2020 |
| A platoon-based cooperative optimal control for connected autonomous vehicles at highway on-ramps under heavy traffic Y Xue, X Zhang, Z Cui, B Yu, K Gao Transportation research part C: emerging technologies 150, 104083, 2023 | 35 | 2023 |
| Traffic performance score for measuring the impact of COVID-19 on urban mobility Z Cui, M Zhu, S Wang, P Wang, Y Zhou, Q Cao, C Kopca, Y Wang arXiv preprint arXiv:2007.00648, 2020 | 35 | 2020 |
| Distributed multiagent deep reinforcement learning for multiline dynamic bus timetable optimization H Yan, Z Cui, X Chen, X Ma IEEE Transactions on Industrial Informatics 19 (1), 469-479, 2022 | 29 | 2022 |
Yinhai WangProfessor of Civil and Environmental Engineering, University of Washingtonuw.edu üzerinde doğrulanmış e-posta adresine sahip
