Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach J Ke, H Zheng, H Yang, XM Chen Transportation research part C: Emerging technologies 85, 591-608, 2017 | 793 | 2017 |
Coordinating supply and demand on an on-demand service platform with impatient customers J Bai, KC So, CS Tang, X Chen, H Wang Manufacturing & Service Operations Management 21 (3), 556-570, 2019 | 536 | 2019 |
Understanding ridesplitting behavior of on-demand ride services: An ensemble learning approach XM Chen, M Zahiri, S Zhang Transportation Research Part C: Emerging Technologies 76, 51-70, 2017 | 288 | 2017 |
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 | 221 | 2020 |
Vehicle headway modeling and its inferences in macroscopic/microscopic traffic flow theory: A survey L Li, XM Chen Transportation Research Part C: Emerging Technologies 76, 170-188, 2017 | 202 | 2017 |
A balancing act of regulating on-demand ride services JJ Yu, CS Tang, ZJ Max Shen, XM Chen Management Science 66 (7), 2975-2992, 2020 | 193 | 2020 |
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 | 187 | 2021 |
Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications … X Jiang, L Zhang, XM Chen Transportation Research Part C: Emerging Technologies 44, 110-127, 2014 | 179 | 2014 |
A Markov model for headway/spacing distribution of road traffic X Chen, L Li, Y Zhang IEEE Transactions on Intelligent Transportation Systems 11 (4), 773-785, 2010 | 173 | 2010 |
Hexagon-based convolutional neural network for supply-demand forecasting of ride-sourcing services J Ke, H Yang, H Zheng, X Chen, Y Jia, P Gong, J Ye IEEE Transactions on Intelligent Transportation Systems 20 (11), 4160-4173, 2018 | 170 | 2018 |
Surrogate‐based optimization of expensive‐to‐evaluate objective for optimal highway toll charges in transportation network X Chen, L Zhang, X He, C Xiong, Z Li Computer‐Aided Civil and Infrastructure Engineering 29 (5), 359-381, 2014 | 146 | 2014 |
A global optimization algorithm for trajectory data based car-following model calibration L Li, XM Chen, L Zhang Transportation Research Part C: Emerging Technologies 68, 311-332, 2016 | 119 | 2016 |
Exploring impacts of on-demand ridesplitting on mobility via real-world ridesourcing data and questionnaires X Chen, H Zheng, Z Wang, X Chen Transportation 48, 1541-1561, 2021 | 114 | 2021 |
GraphSAGE-based traffic speed forecasting for segment network with sparse data J Liu, GP Ong, X Chen IEEE Transactions on Intelligent Transportation Systems 23 (3), 1755-1766, 2020 | 114 | 2020 |
Dynamic optimization strategies for on-demand ride services platform: Surge pricing, commission rate, and incentives XM Chen, H Zheng, J Ke, H Yang Transportation Research Part B: Methodological 138, 23-45, 2020 | 104 | 2020 |
Sharing economy: making supply meet demand M Hu Springer, 2019 | 92 | 2019 |
Spatial-temporal inference of urban traffic emissions based on taxi trajectories and multi-source urban data J Liu, K Han, XM Chen, GP Ong Transportation Research Part C: Emerging Technologies 106, 145-165, 2019 | 89 | 2019 |
Multimodel ensemble for freeway traffic state estimations L Li, X Chen, L Zhang IEEE Transactions on Intelligent Transportation Systems 15 (3), 1323-1336, 2014 | 88 | 2014 |
A spatial econometric model for travel flow analysis and real-world applications with massive mobile phone data L Ni, XC Wang, XM Chen Transportation research part C: emerging technologies 86, 510-526, 2018 | 87 | 2018 |
Ridesplitting is shaping young people’s travel behavior: Evidence from comparative survey via ride-sourcing platform Z Wang, X Chen, XM Chen Transportation research part D: transport and environment 75, 57-71, 2019 | 84 | 2019 |