| Learning traffic as images: A deep convolutional neural network for large-scale transportation network speed prediction X Ma, Z Dai, Z He, J Ma, Y Wang, Y Wang sensors 17 (4), 818, 2017 | 1545 | 2017 |
| Predicting station-level hourly demand in a large-scale bike-sharing network: A graph convolutional neural network approach L Lin, Z He, S Peeta Transportation Research Part C: Emerging Technologies 97, 258-276, 2018 | 470 | 2018 |
| A data-driven lane-changing model based on deep learning DF Xie, ZZ Fang, B Jia, Z He Transportation Research Part C: Emerging Technologies 106, 41-60, 2019 | 304 | 2019 |
| Trajectory data-based traffic flow studies: A revisit L Li, R Jiang, Z He, XM Chen, X Zhou Transportation Research Part C: Emerging Technologies 114, 225-240, 2020 | 232 | 2020 |
| Heterogeneous traffic mixing regular and connected vehicles: Modeling and stabilization DF Xie, XM Zhao, Z He IEEE Transactions on Intelligent Transportation Systems 20 (6), 2060-2071, 2019 | 219 | 2019 |
| Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives H Yu, R Jiang, Z He, Z Zheng, L Li, R Liu, X Chen Transportation research part C: emerging technologies 127, 103101, 2021 | 201 | 2021 |
| A simple nonparametric car-following model driven by field data Z He, L Zheng, W Guan Transportation Research Part B: Methodological 80, 185-201, 2015 | 175 | 2015 |
| Short-term origin-destination demand prediction in urban rail transit systems: A channel-wise attentive split-convolutional neural network method J Zhang, H Che, F Chen, W Ma, Z He Transportation Research Part C: Emerging Technologies 124, 102928, 2021 | 151 | 2021 |
| Vulnerability and resilience of transportation systems: A recent literature review S Pan, H Yan, J He, Z He Physica A: Statistical Mechanics and its Applications 581, 126235, 2021 | 144 | 2021 |
| Mapping to cells: A simple method to extract traffic dynamics from probe vehicle data Z He, L Zheng, P Chen, W Guan Computer‐Aided Civil and Infrastructure Engineering 32 (3), 252-267, 2017 | 111 | 2017 |
| Digital twin empowered mobile edge computing for intelligent vehicular lane-changing B Fan, Y Wu, Z He, Y Chen, TQS Quek, CZ Xu IEEE Network 35 (6), 194-201, 2021 | 105 | 2021 |
| Erasing lane changes from roads: A design of future road intersections Z He, L Zheng, L Lu, W Guan IEEE Transactions on Intelligent Vehicles 3 (2), 173-184, 2018 | 99 | 2018 |
| Electric vehicle routing problem with charging time and variable travel time S Shao, W Guan, B Ran, Z He, J Bi Mathematical Problems in Engineering 2017 (1), 5098183, 2017 | 93 | 2017 |
| Optimal toll design problems under mixed traffic flow of human-driven vehicles and connected and autonomous vehicles J Wang, L Lu, S Peeta, Z He Transportation Research Part C: Emerging Technologies 125, 102952, 2021 | 87 | 2021 |
| A jam-absorption driving strategy for mitigating traffic oscillations Z He, L Zheng, L Song, N Zhu IEEE Transactions on Intelligent Transportation Systems 18 (4), 802-813, 2017 | 87 | 2017 |
| Probe data-driven travel time forecasting for urban expressways by matching similar spatiotemporal traffic patterns Z Zhang, Y Wang, P Chen, Z He, G Yu Transportation Research Part C: Emerging Technologies 85, 476-493, 2017 | 84 | 2017 |
| Trajectory prediction for autonomous driving using spatial-temporal graph attention transformer K Zhang, X Feng, L Wu, Z He IEEE Transactions on Intelligent Transportation Systems 23 (11), 22343-22353, 2022 | 82 | 2022 |
| Commuters’ acceptance of and behavior reactions to license plate restriction policy: A case study of Tianjin, China N Jia, Y Zhang, Z He, G Li Transportation Research Part D: Transport and Environment 52, 428-440, 2017 | 74 | 2017 |
| Network-wide identification of turn-level intersection congestion using only low-frequency probe vehicle data Z He, G Qi, L Lu, Y Chen Transportation Research Part C: Emerging Technologies 108, 320-339, 2019 | 62 | 2019 |
| Mobile traffic sensor routing in dynamic transportation systems N Zhu, Y Liu, S Ma, Z He IEEE Transactions on Intelligent transportation systems 15 (5), 2273-2285, 2014 | 59 | 2014 |