Travel time prediction: Based on gated recurrent unit method and data fusion J Zhao, Y Gao, Y Qu, H Yin, Y Liu, H Sun IEEE Access 6, 70463-70472, 2018 | 72 | 2018 |
A novel prediction model for the inbound passenger flow of urban rail transit X Yang, Q Xue, X Yang, H Yin, Y Qu, X Li, J Wu Information Sciences 566, 347-363, 2021 | 66 | 2021 |
Optimizing the release of passenger flow guidance information in urban rail transit network via agent-based simulation H Yin, J Wu, Z Liu, X Yang, Y Qu, H Sun Applied Mathematical Modelling 72, 337-355, 2019 | 48 | 2019 |
Robust bus bridging service design under rail transit system disruptions J Liang, J Wu, Y Qu, H Yin, X Qu, Z Gao Transportation Research Part E: Logistics and Transportation Review 132, 97-116, 2019 | 47 | 2019 |
Optimizing last trains timetable in the urban rail network: social welfare and synchronization H Yin, J Wu, H Sun, L Kang, R Liu Transportmetrica B: Transport Dynamics 7 (1), 473-497, 2019 | 46 | 2019 |
Recognizing the critical stations in urban rail networks: an analysis method based on the smart-card data X Yang, H Yin, J Wu, Y Qu, Z Gao, T Tang IEEE Intelligent Transportation Systems Magazine 11 (1), 29-35, 2018 | 35 | 2018 |
Performance improvement of energy consumption, passenger time and robustness in metro systems: A multi-objective timetable optimization approach X Yang, J Wu, H Sun, Z Gao, H Yin, Y Qu Computers & Industrial Engineering 137, 106076, 2019 | 32 | 2019 |
Data-driven model for passenger route choice in urban metro network J Wu, Y Qu, H Sun, H Yin, X Yan, J Zhao Physica A: Statistical Mechanics and its Applications 524, 787-798, 2019 | 30 | 2019 |
Evaluating disruption in rail transit network: a case study of Beijing subway H Yin, B Han, D Li Procedia Engineering 137, 49-58, 2016 | 28 | 2016 |
Optimal bus-bridging service under a metro station disruption H Yin, J Wu, H Sun, Y Qu, X Yang, B Wang Journal of Advanced Transportation 2018, 2018 | 27 | 2018 |
Robust optimization of train timetable and energy efficiency in urban rail transit: A two-stage approach Y Qu, H Wang, J Wu, X Yang, H Yin, L Zhou Computers & Industrial Engineering 146, 106594, 2020 | 26 | 2020 |
Analyzing crowd dynamic characteristics of boarding and alighting process in urban metro stations Y Qu, Y Xiao, H Liu, H Yin, J Wu, Q Qu, D Li, T Tang Physica A: Statistical Mechanics and its Applications 526, 121075, 2019 | 24 | 2019 |
Modeling and simulating passenger behavior for a station closure in a rail transit network H Yin, B Han, D Li, J Wu, H Sun PLoS one 11 (12), e0167126, 2016 | 24 | 2016 |
Model and algorithm of coordinated flow controlling with station-based constraints in a metro system P Zhang, H Sun, Y Qu, H Yin, JG Jin, J Wu Transportation Research Part E: Logistics and Transportation Review 148, 102274, 2021 | 20 | 2021 |
A robust train timetable optimization approach for reducing the number of waiting passengers in metro systems L Zhou, X Yang, H Wang, J Wu, L Chen, H Yin, Y Qu Physica A: Statistical Mechanics and its Applications 558, 124927, 2020 | 18 | 2020 |
Designing a safe and fair network for hazmat road transportation H Yin, H Sun, S Peng, J Wu, Y Ge, Y Chen Journal of Transportation Safety & Security 12 (4), 482-500, 2020 | 14 | 2020 |
Multistation coordinated and dynamic passenger inflow control for a metro line X Wang, J Wu, X Yang, X Guo, H Yin, H Sun IET Intelligent Transport Systems 14 (9), 1068-1078, 2020 | 12 | 2020 |
Urban rail timetable optimization to improve operational efficiency with flexible routing plans: A nonlinear integer programming model Q Xue, X Yang, J Wu, H Sun, H Yin, Y Qu Sustainability 11 (13), 3701, 2019 | 12 | 2019 |
Dynamic schedule-based assignment model for urban rail transit network with capacity constraints B Han, W Zhou, D Li, H Yin The Scientific World Journal 2015, 2015 | 12 | 2015 |
An energy based method to measure the crowd safety H Yin, D Li, X Zheng Transportation Research Procedia 2, 691-696, 2014 | 12 | 2014 |