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Xiqun (Michael) Chen
Xiqun (Michael) Chen
Director of Institute of Intelligent Transportation Systems
Verified email at zju.edu.cn - Homepage
Title
Cited by
Cited by
Year
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
8002017
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
5372019
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
2892017
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
2212020
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
2032017
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
1932020
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
1882021
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
1802014
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
1742010
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
1722018
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
1462014
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
1192016
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
1152021
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
1152020
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
1052020
Sharing economy: making supply meet demand
M Hu
Springer, 2019
922019
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
902019
Multimodel ensemble for freeway traffic state estimations
L Li, X Chen, L Zhang
IEEE Transactions on Intelligent Transportation Systems 15 (3), 1323-1336, 2014
882014
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
872018
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
862019
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