陈喜群

陈喜群

教授

陈喜群,男,长聘教授,博士生导师,浙江大学智能交通研究所所长,浙江大学伊利诺伊大学厄巴纳香槟校区联合学院副院长,智慧交通浙江省工程研究中心副主任。荣获国家优秀青年基金、入选中国科协“青年人才托举工程”、浙江省杰出青年基金、浙江省特聘专家。2004-2015年,曾先后在清华大学土木工程系交通研究所、美国加州大学伯克利分校PATH研究所、美国马里兰大学土木与环境工程系、美国马里兰国家交通中心学习和工作。研究领域包括交通运输管理、共享出行、交通流建模与仿真优化、智能交通系统等。致力于大数据驱动的城市多模式交通管理与优化研究,在城市多模式交通共享出行行为机理、复杂动态交通流随机演化建模与预测、基于多源大数据的交通仿真优化等开展研究。担任世界交通运输大会交通管理与控制学科主席,美国土木工程师学会大中华分会理事,管理科学与工程学会理事,SCI期刊Transportation Research Part C: Emerging Technologies编委,Journal of Traffic and Transportation Engineering青年编委,中国公路学报青年编委。主持国家自然科学基金项目4项、国家重点研发计划课题1项、浙江省自然科学基金杰出青年基金1项、重点项目1项。参与美国交通部研究项目(USDOT)、美国国家科学基金(NSF)、美国联邦公路管理局研究项目(FHWA)、马里兰公路管理局研究项目(MSHA)、马里兰国家交通中心研究项目(NTC)等。在Management Science、Manufacturing & Service Operations Management (M&SOM)、Transportation Science、Transportation Research Part B、IEEE Transactions on Intelligent Transportation Systems等期刊发表SCI/SSCI论文90余篇,由Springer出版英文专著1部,参编3部。授权国家发明专利9件。获首届中国交通运输协会科技创新青年奖、IEEE国际智能交通学会最佳博士论文奖、国内外学术会议最佳论文奖6项、中国智能交通协会科技奖二等奖1项(排名第1)。
  • 教育背景
    • 2008/09 - 2013/01,清华大学土木工程系,博士
    • 2011/09 - 2012/08,加州大学伯克利分校交通研究所,博士生联合培养
    • 2004/08 - 2008/07,清华大学土木工程系,本科
  • 工作经历
    • 2022/05 - 至今,浙江大学伊利诺伊大学厄巴纳香槟校区联合学院,副院长
    • 2022/05 - 至今,浙江大学智能交通研究所,所长
    • 2021/09 - 至今,浙江大学-阿里巴巴数字交通创新应用中心,副主任
    • 2021/07 - 至今,智慧交通浙江省工程研究中心,副主任
    • 2021/01 - 至今,浙江大学建筑工程学院智能交通研究所,长聘教授,博士生导师
    • 2018/10 - 至今,浙江大学建筑工程学院土木工程系,副系主任
    • 2015/03 - 2020/12,浙江大学建筑工程学院智能交通研究所,“百人计划”研究员,博士生导师
    • 2014/07 - 2015/06,美国马里兰大学土木与环境工程系,副研究员(Research Associate)
    • 2013/10 - 2015/02,美国马里兰国家交通中心,科研主任(Research Director)
    • 2012/07 - 2014/06,美国马里兰大学土木与环境工程系,助理研究员(Faculty Research Assistant)
  • 论文发表
    一、专著与章节
    [4] Bai J., So K. C., Tang C. S., Chen X. and Wang H. (2019). Time-Based Payout Ratio for Coordinating Supply and Demand on an On-Demand Service Platform. M. Hu (ed.), Sharing Economy: Making Supply Meet Demand, in Springer Series in Supply Chain Management, S. C. Tang (Series Ed.). Springer Nature Switzerland AG, 2019. (专著章节)
    [3] Chen X.* (2018). Simulation-Based Optimization for Network Modeling with Heterogeneous Data. Wang, Y., Zeng, Z. (Ed.) Data-driven Solutions to Transportation Problems. Elsevier, 2018. (专著章节)
    [2] Chen X.*, Li L. and Shi Q. (2015) Stochastic Evolutions of Dynamic Traffic Flow: Modeling and Applications. Springer, Heidelberg. (英文专著)
    [1] Xiong C., Chen X. and Zhang L.* (2014). Multidimensional travel decision-making: Descriptive behavioural theory and agent-based models. Timmermans, H.J.P., Rasouli, S. (Ed.) Bounded Rational Choice Behavior: Applications in Transport. Emerald, UK. Oct. 2014. (专著章节)

    二、国际期刊论文
    [108] Zhu Z., Xu M., Di Y., Chen X.* and Yu J. (2023) Modeling ride-sourcing matching and pickup processes based on additive Gaussian process models. Transportmetrica B: Transport Dynamics, in press. (SCI/SSCI, 影响因子3.410)
    [107] Zhu J., Xie N., Cai Z., Tang W. and Chen X.* (2023) A comprehensive review of shared mobility for sustainable transportation systems. International Journal of Sustainable Transportation, in press. (SSCI, 影响因子3.963)
    [106] Wan Y., Xie C.*, Waller T., Xu M. and Chen X. (2023) On the primal and dual formulations of traffic assignment problems with perception stochasticity and demand elasticity. Transportation Letters, in press. (SSCI, 影响因子2.844)
    [105] Xie C.*, Hou J., Zhang T., Waller T. and Chen X. (2023) Modeling and evaluating the impact of electricity price on commute network flows of battery electric vehicles. Transportation Letters, in press. (SSCI, 影响因子2.844)
    [104] Ni L., Wang X., Chen X. and Zhang D.* (2023) Analyzing time-varying trip distributions with a random-effect spatial OD dependence model. PLOS One, 18(1), e0280162. (SSCI, 影响因子3.752)
    [103] Zhu, Z., Xu, M., Ke, J., Yang, H. and Chen, X.* (2023). A Bayesian clustering ensemble Gaussian process model for network-wide traffic flow clustering and prediction. Transportation Research Part C: Emerging Technologies, 148, 104032. (SCI, 影响因子9.022)
    [102] Yu, J., Mo, D., Zhu, Z. and Chen, X.* (2023). A high-order hidden Markov model for dynamic decision analysis of multi-homing ride-sourcing drivers. Transportation Research Part C: Emerging Technologies, 148, 104031. (SCI, 影响因子9.022)
    [101] Xu, M., Di, Y., Yang, H., Chen, X. and Zhu, Z.* (2023). Multi-task supply-demand prediction and reliability analysis for docked bike-sharing systems via transformer-encoder-based neural processes. Transportation Research Part C: Emerging Technologies, 147, 104015. (SCI, 影响因子9.022)
    [100] Liu J., Li J., Chen Y., Lian S., Zeng J., Geng M., Zheng S., Dong Y., He Y., Huang P., Zhao Z., Yan X., Hu Q., Wang L., Yang D., Zhu Z., Sun Y., Shang W., Wang D., Zhang L., Hu S., Chen X.* (2023) Multi-scale urban passenger transportation CO2 emission calculation platform for smart mobility management. Applied Energy, 331, 120407. (SCI, 影响因子11.446)
    [99] Cai Z., Mo D., Geng M., Tang W., and Chen X.* (2023) Integrating ride-sourcing with electric vehicle charging under mixed fleets and differentiated services. Transportation Research Part E: Logistics and Transportation Review, 169, 102965. (SSCI, 影响因子10.047)
    [98] Zhan X., Szeto W. Y.* and Chen X. (2022) The dynamic ride-hailing sharing problem with multiple vehicle types and user classes. Transportation Research Part E: Logistics and Transportation Review, 168, 102891. (SSCI, 影响因子10.047)
    [97] Xie N., Liu Z., Chen X.*, Li S. (2022) Fair assignment for reserved nucleic acid testing. Sustainability, 14(18), 11752. (SCI/SSCI, 影响因子3.889)
    [96] Ke J., Chen X.*, Yang H. and Li S. (2022) Coordinating supply and demand in ride-sourcing markets with pre-assigned pooling service and traffic congestion externality. Transportation Research Part E: Logistics and Transportation Review, 166, 102887. (SSCI, 影响因子10.047)
    [95] Di Y., Xu M., Yang H., Chen X. and Zhu Z.* (2022) Analysis of ride-sourcing drivers' working pattern(s) via spatiotemporal work slices: A case study in Hangzhou. Transport Policy, 125, 336-351. (SSCI, 影响因子6.173)
    [94] Chen Y. and Chen X.* (2022) A novel reinforced dynamic graph convolutional network model with data imputation for network-wide traffic flow prediction. Transportation Research Part C: Emerging Technologies, 143, 103820. (SCI, 影响因子9.022)
    [93] Li J., Xie N., Zhang K., Guo F., Hu S. and Chen X.* (2022) Network-scale traffic prediction via knowledge transfer and regional MFD analysis. Transportation Research Part C: Emerging Technologies, 141, 103719. (SCI, 影响因子9.022)
    [92] Zhang J., Mo D. and Chen X.* (2022) Analyzing ride-sourcing market equilibrium and its transitions with heterogeneous users. Journal of Advanced Transportation, 5894250. (SCI, 影响因子2.249)
    [91] Wang D., Cai Z., Cui Y. and Chen X.* (2022) Nonnegative tensor decomposition for urban mobility analysis and applications with mobile phone data. Transportmetrica A: Transport Science, 18(1), 29-53. (SCI/SSCI, 影响因子3.277)
    [90] Liu J., Ong G.* and Chen X.* (2022) GraphSAGE-based traffic speed forecasting for road segment network with sparse data. IEEE Transactions on Intelligent Transportation Systems, 23(3), 1755-1766. (SCI, 影响因子9.551)
    [89] Xu M., Di Y., Zhu Z.*, Yang H. and Chen X. (2022) Designing van-based mobile battery swapping and rebalancing services for dockless ebike-sharing systems based on the dueling double deep Q-network. Transportation Research Part C: Emerging Technologies, 138, 103620. (SCI, 影响因子9.022)
    [88] Tang W., Wang H., Wang Y., Chen C. and Chen X.* (2022) A bi-level optimization model for ride-sourcing platform's spatial pricing strategy. Journal of Advanced Transportation, 2022, 9120129. (SCI, 影响因子2.249)
    [87] Zhan X., Szeto W. Y.* and Chen X. (2022) A simulation-optimization framework for a dynamic electric ride-hailing sharing problem with a novel charging strategy. Transportation Research Part E: Logistics and Transportation Review, 159, 102615. (SSCI, 影响因子10.047)
    [86] Mo D., Chen X.* and Zhang J. (2022) Modeling and managing mixed on-demand ride services of human-driven vehicles and autonomous vehicles. Transportation Research Part B: Methodological, 157, 80-119. (SCI/SSCI, 影响因子7.632)
    [85] Yu J., Xie N., Zhu J., Qian Y., Zheng S. and Chen X.* (2022) Exploring impacts of COVID-19 on city-wide taxi and ride-sourcing markets: Evidence from Ningbo, China. Transport Policy, 115, 220-238. (SSCI, 影响因子6.173)
    [84] Chen X., Zheng H., Wang Z. and Chen X.* (2021) Exploring impacts of on-demand ridesplitting on mobility via real-world ridesourcing data and questionnaires. Transportation, 48, 1541-1561. (SSCI, 影响因子4.814)
    [83] Ni L., Chen C., Wang X. and Chen X.* (2021) Modeling network equilibrium of competitive ride-sourcing market with heterogeneous transportation network companies. Transportation Research Part C: Emerging Technologies, 130, 103277. (SCI, 影响因子9.022)
    [82] Chen C., Yao F., Mo D., Zhu J. and Chen X.* (2021) Spatial-temporal pricing for ride-sourcing platform with reinforcement learning. Transportation Research Part C: Emerging Technologies, 130, 103272. (SCI, 影响因子9.022)
    [81] Chen C., Hu S., Ochieng W., Xie N. and Chen X.* (2021) Understanding city-wide ride-sourcing travel flow: A geographically weighted regression approach. Journal of Advanced Transportation, 9929622. (SCI, 影响因子2.249)
    [80] Chen X., Chen X., Zheng H. and Xiao F. (2021) Efficient dispatching for on-demand ride services: Systematic optimization via Monte-Carlo tree search. Transportation Research Part C: Emerging Technologies, 127, 103156. (SCI, 影响因子9.022)
    [79] Zhan X., Szeto W. Y.*, Shui C. S. and Chen X. (2021) A modified artificial bee colony algorithm for the dynamic ride-hailing sharing problem. Transportation Research Part E: Logistics and Transportation Review, 150, 102124. (SSCI, 影响因子10.047)
    [78] Yu J., Mo D., Xie N., Hu S. and Chen X.* (2021) Exploring multi-homing behavior of ride-sourcing drivers via real-world multiple platforms data. Transportation Research Part F: Traffic Psychology and Behaviour, 80, 61-78. (SSCI, 影响因子4.349)
    [77] Yu H., Jiang R., He Z.*, Zheng Z.*, Li L.*, Liu R. and Chen X. (2021) Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives. Transportation Research Part C: Emerging Technologies, 127, 103101. (SCI, 影响因子9.022)
    [76] Zhu Z., Sun L., Chen X.* and Yang H. (2021) Integrating probabilistic tensor factorization with Bayesian supervised learning for dynamic ridesharing pattern analysis. Transportation Research Part C: Emerging Technologies, 124, 102916. (SCI, 影响因子9.022)
    [75] Shen L., Shao Z., Yu Y. and Chen X.* (2021) Hybrid approach combining modified gravity model and deep learning for short-term forecasting of metro transit passenger flows. Journal of Transportation Research Board: Transportation Research Record, 2675(1), 25-38. (SCI, 影响因子2.019)
    [74] Zhang S., Zhou L., Chen X.*, Zhang L., Li L.* and Li M. (2020) Network-wide traffic speed forecasting: 3D convolutional neural network with ensemble empirical mode decomposition. Computer-Aided Civil and Infrastructure Engineering, 35(10), 1132-1147. (SCI, 影响因子10.066)
    [73] Zhou L., Zhang S., Yu J. and Chen X.* (2020) Spatial-temporal deep tensor neural networks for large-scale urban network speed prediction. IEEE Transactions on Intelligent Transportation Systems, 21(9), 3718-3729. (SCI, 影响因子9.551)
    [72] Mo D., Yu J. and Chen X.* (2020) Modeling and managing heterogeneous ride-sourcing platforms with government subsidies on electric vehicles. Transportation Research Part B: Methodological, 139, 447-472. (SCI/SSCI, 影响因子7.632)
    [71] Yao F., Zhu J., Yu J., Chen C. and Chen X.* (2020) Hybrid operations of human-driving vehicles and automated vehicles with data-driven agent-based simulation. Transportation Research Part D: Transport and Environment, 86, 102469. (SCI/SSCI, 影响因子7.041)
    [70] Yu J., Tang C.S., Shen Z.M. and Chen X. (2020) A balancing act of regulating on-demand ride services. Management Science, 66(7), 2975-2992. (SSCI, 影响因子6.172)
    [69] Chen X., Zheng H., Ke J. and Yang H.* (2020) Dynamic optimization strategies for on-demand ride services platform: Surge pricing, commission rate, and incentives. Transportation Research Part B: Methodological, 138, 23-45. (SCI/SSCI, 影响因子7.632)
    [68] Xiong C., Yang D.*, Ma J., Chen X. and Zhang L. (2020) Measuring and enhancing the transferability of Hidden Markov Models for dynamic travel behavioral analysis. Transportation, 47, 585-605. (SSCI, 影响因子4.814)
    [67] Ding Z., Dai Z., Chen X.* and Jiang R.* (2020) Simulating on-demand ride services in a Manhattan-like urban network considering traffic dynamics. Physica A, 545, 123621. (SCI, 影响因子3.778)
    [66] Li L., Jiang R., He Z.*, Chen X.*, Zhou X.* (2020) Trajectory data-based traffic flow studies: A revisit. Transportation Research Part C: Emerging Technologies, 114, 225-240. (SCI, 影响因子9.022)
    [65] Zhan X., Zhang S., Szeto W. Y. and Chen X.* (2020) Multi-step-ahead traffic speed forecasting using multi-output gradient boosting regression tree. Journal of Intelligent Transportation Systems, 24(2), 125-141. (SCI, 影响因子3.839)
    [64] Yu J., Stettler M., Angeloudis P., Hu S. and Chen X.* (2020) Urban network-wide traffic speed estimation with massive ride-sourcing GPS traces. Transportation Research Part C: Emerging Technologies, 112, 136-152. (SCI, 影响因子9.022)
    [63] Zahiri M., Liu J. and Chen X.* (2019) Taxi downsizing: A new approach to efficiency and sustainability in the taxi industry. Sustainability, 11(18), 4944. (SCI/SSCI, 影响因子3.889)
    [62] Ke J., Yang H., Zheng H., Chen X.*, Jia Y., Gong P., Ye J. (2019) Hexagon-based convolutional neural network for supply-demand forecasting of ride-sourcing services. IEEE Transactions on Intelligent Transportation Systems, 20(11), 4160-4173. (SCI, 影响因子9.551)
    [61] Wang S., Li L.*, Ma W.* and Chen X. (2019) Trajectory analysis for on-demand services: A survey focusing on spatio-temporal demand and supply patterns. Transportation Research Part C: Emerging Technologies, 108, 74-99. (SCI, 影响因子9.022)
    [60] Wang Z., Chen X. and Chen X.* (2019) Ridesplitting is shaping young people’s travel behavior: Evidence from comparative survey via ride-sourcing platform. Transportation Research Part D: Transport and Environment, 75, pp. 57-71. (SCI/SSCI, 影响因子7.041)
    [59] Bai J., So K.C., Tang C., Chen X. and Wang H. (2019) Coordinating supply and demand on an on-demand service platform with impatient customers. Manufacturing & Service Operations Management, 21(3), 556-570. (SSCI, 影响因子7.103)
    [58] Liu J., Han K., Chen X.* and Ong G. P. (2019) Spatial-temporal inference of urban traffic emissions based on taxi trajectories and multi-source urban data. Transportation Research Part C: Emerging Technologies, 106, 145-165. (SCI, 影响因子9.022)
    [57] Ke J., Cen X., Yang H., Chen X.*, Ye J. (2019) Modelling drivers' working and recharging schedules in a ride-sourcing market with electric vehicles and gasoline vehicles. Transportation Research Part E: Logistics and Transportation Review, 125, 160-180. (SSCI, 影响因子10.047)
    [56] Chen X., Zhang S. and Li L.* (2019) Multi-model ensemble for short-term traffic flow prediction under normal and abnormal conditions. IET Intelligent Transport Systems, 13(2), 260-268. (SCI, 影响因子2.568)
    [55] Ke J., Zhang S., Yang H. and Chen X.* (2019) PCA-based missing information imputation for real-time crash likelihood prediction under imbalanced data. Transportmetrica A: Transport Science, 15(2), 872-895. (SCI/SSCI, 影响因子3.277)
    [54] Zhu Z., Chen X.*, Zhang X. and Zhang L. (2019) Probabilistic data fusion for short-term traffic prediction with semiparametric density ratio model. IEEE Transactions on Intelligent Transportation Systems, 20(7), 2459-2469. (SCI, 影响因子9.551)
    [53] Chen X., Zhang S., Li L.* and Li L. (2019) Adaptive rolling smoothing with heterogeneous data for traffic state estimation and prediction. IEEE Transactions on Intelligent Transportation Systems, 20(4), 1247-1258. (SCI, 影响因子9.551)
    [52] Chen X., Zhou L. and Li L.* (2019) Bayesian network for red-light-running prediction at signalized intersections. Journal of Intelligent Transportation Systems, 23(2), 120-132. (SCI, 影响因子3.839)
    [51] Zheng H., Chen X. and Chen X.* (2019) How does on-demand ridesplitting influence vehicle use and purchase willingness? A case study in Hangzhou, China. IEEE Intelligent Transportation Systems Magazine, 11(3), 143-157. (SCI, 影响因子5.293)
    [50] Zhu Z., Tang L., Xiong C., Chen X. and Zhang L.* (2019) The conditional probability of travel speed and its application to short-term prediction. Transportmetrica B: Transport Dynamics, 7(1), 684-706. (SCI/SSCI, 影响因子3.410)
    [49] Chen X., He X., Xiong C., Zhu Z. and Zhang L.* (2019) A Bayesian stochastic Kriging optimization model dealing with heteroscedastic simulation noise for freeway traffic management. Transportation Science, 53(2), 545-565. (SCI/SSCI, 影响因子4.898)
    [48] Zhu Z., Xiong C., Chen X.* and Zhang L.* (2018) Integrating mesoscopic dynamic traffic assignment with agent-based travel behavior models for cumulative land development impact analysis. Transportation Research Part C: Emerging Technologies, 93, 446-462. (SCI, 影响因子9.022)
    [47] Chen X., Chen C., Ni L. and Li L.* (2018) Spatial visitation prediction of on-demand ride services using the scaling law. Physica A, 508, 84-94. (SCI, 影响因子3.778)
    [46] Zhu Z., Xiong C., Chen X.* and Zhang L. (2018) Calibrating supply parameters of large-scale DTA models with surrogate-based optimisation. IET Intelligent Transport Systems, 12(7), 642-650. (SCI, 影响因子2.568)
    [45] Ni L., Wang X.C. and Chen X.* (2018) A spatial econometric model for travel flow analysis and real-world applications with massive mobile phone data. Transportation Research Part C: Emerging Technologies, 86, 510-526. (SCI, 影响因子9.022)
    [44] Zahiri M. and Chen X.* (2018) Measuring the passenger car equivalent of small cars and SUVs in rainy and sunny days. Journal of Transportation Research Board: Transportation Research Record, 2672(31), 110-119. (SCI, 影响因子2.019)
    [43] Xiong C., Zhu Z., Chen X. and Zhang L.* (2018) Optimal travel information provision strategies: an agent-based approach under uncertainty. Transportmetrica B: Transport Dynamics, 6(2), 129-150. (SCI/SSCI, 影响因子3.410)
    [42] Zhu Z., Xiong C., Chen X. and Zhang L.* (2018) A mixed Bayesian network for two-dimensional decision modeling of departure time and mode choice. Transportation, 45(5), 1499-1522. (SSCI, 影响因子4.814)
    [41] Li M., Chen X.*, Lin X., Xu D. and Wang Y. (2018) Connected vehicle-based red-light running prediction for adaptive signalized intersections. Journal of Intelligent Transportation Systems, 22(3), 229-243. (SCI, 影响因子3.839)
    [40] Chen X., Zhang L.*, Xiong C., He X. and Zhu Z. (2018) Simulation-based pricing optimization for improving network-wide travel time reliability. Transportmetrica A: Transport Science, 14(1-2), 155-176. (SCI/SSCI, 影响因子3.277)
    [39] Ke J., Zheng H., Yang H. and Chen X.* (2017) Short-term forecasting of passenger demand under On-demand ride services: A spatio-temporal deep learning approach. Transportation Research Part C: Emerging Technologies, 85, 591-608. (SCI, 影响因子9.022)
    [38] Chen X.*, Chen X., Zheng H. and Chen C. (2017) Understanding network travel time reliability with on-demand ride service data. Frontiers of Engineering Management, 4(4), 388-398.
    [37] Jiang Z., Chen X.* and Ouyang Y. (2017) Traffic state and emission estimation for urban expressways based on heterogeneous data. Transportation Research Part D: Transport and Environment, 53, 440-453. (SCI/SSCI, 影响因子7.041)
    [36] Cai Z., Wang D. and Chen X.* (2017) A novel trip coverage index for transit accessibility assessment using mobile phone data. Journal of Advanced Transportation, 9754508. (SCI, 影响因子2.249)
    [35] Li L. and Chen X.* (2017) Vehicle headway modeling and its inferences in macroscopic/microscopic traffic flow theory: A survey. Transportation Research Part C: Emerging Technologies, 76, 170-188. (SCI/SSCI, 影响因子9.022)
    [34] Chen X.*, Zahiri M. and Zhang S. (2017) Understanding ridesplitting behavior of on-demand ride services: An ensemble learning approach. Transportation Research Part C: Emerging Technologies, 76, pp. 51-70. (SCI, 影响因子9.022)
    [33] Jiang X., Zhang X., Lu W., Chen X.* and Zhang L. (2017) Competition between high-speed rail and airline based on game theory. Mathematical Problems in Engineering, 1748691. (SCI, 影响因子1.430)
    [32] Li M., Lin X. and Chen X.* (2017) A surrogate-based optimization algorithm for network design problems. Frontiers of Information Technology & Electronic Engineering, 18(11), 1693-1704. (SCI, 影响因子2.526)
    [31] He X., Chen X.*, Xiong C., Zhu Z. and Zhang L.* (2017) Optimal time-varying pricing for toll roads under multiple objectives: A simulation-based optimization approach. Transportation Science, 51(2), 412-426. (SCI/SSCI, 影响因子4.898)
    [30] Li L., Chen X.*, Li Z. and Zhang L. (2016) A global optimization algorithm for trajectory data based car-following model calibration. Transportation Research Part C: Emerging Technologies, 68, pp. 311-332. (SCI, 影响因子9.022)
    [29] Chen X., Xiong C., He X. Zhu, Z. and Zhang L.* (2016) Time-of-day vehicle mileage fees for congestion mitigation and revenue generation: A simulation-based optimization method and its real-world application. Transportation Research Part C: Emerging Technologies, 63, pp. 71-95. (SCI, 影响因子9.022)
    [28] Li M., Chen X.* and Ni, W. (2016) An extended generalized filter algorithm for urban expressway traffic time estimation based on heterogeneous data. Journal of Intelligent Transportation Systems, 20(5), pp. 474-484. (SCI, 影响因子3.839)
    [27] Xiong C., Chen X., He X., Lin X. and Zhang L.* (2016) Agent-based en-route diversion: Dynamic behavioral responses and network performance represented by Macroscopic Fundamental Diagrams. Transportation Research Part C: Emerging Technologies, 64, pp. 148-163. (SCI/SSCI, 影响因子9.022)
    [26] Chu C., Xie N.*, Chen X., Wu Y. and Sun X. (2015) Temporal-spatial analysis of traffic congestion based on modified CTM. Mathematical Problems in Engineering, 136102. (SCI, 影响因子1.430)
    [25] Chen X., Zhu Z., He X. and Zhang L.* (2015) Surrogate-based optimization for solving a mixed integer network design problem. Journal of Transportation Research Board: Transportation Research Record, 2497, pp. 124-136. (SCI, 影响因子2.019)
    [24] Chen X., Zhu Z. and Zhang L.* (2015) Simulation-based optimization of mixed road pricing policies in a large real-world network. Transportation Research Procedia, 8, pp. 215-226. (EI)
    [23] Xiong C., Chen X., He X., Guo W. and Zhang L.* (2015) The analysis of dynamic travel mode choice: A heterogeneous hidden Markov approach. Transportation, 42(6), pp. 985-1002. (SCI/SSCI, 影响因子4.814)
    [22] Xiong C., Zhu, Z., He, X., Chen X., Zhu S., Mahapatra S., Chang G.-L. and Zhang L.* (2015) Developing a 24-hour large-scale microscopic traffic simulation model for the before-and-after study of a new tolled freeway in the Washington DC-Baltimore region. ASCE Journal of Transportation Engineering, 141(6), 05015001. (SCI, 影响因子1.930)
    [21] Zhu Z., Xiong C., Chen X., He X. and Zhang L.* (2015) Agent-based microsimulation approach for design and evaluation of flexible work schedules. Journal of Transportation Research Board: Transportation Research Record, 2537, pp. 167-176. (SCI, 影响因子2.019)
    [20] Jiang X.*, Chen X., Zhang L. and Zhang R. (2015) Dynamic demand forecasting and ticket assignment for high speed rail revenue management in China. Journal of Transportation Research Board: Transportation Research Record, 2475, pp. 37-45. (SCI, 影响因子2.019)
    [19] Wang Z., Chen X., Ouyang Y. and Li M.* (2015) Emission mitigation via longitudinal control of intelligent vehicles in a congested platoon. Computer-Aided Civil and Infrastructure Engineering, 30(6), pp. 490-506. (SCI, 影响因子10.066)
    [18] Chen X., Li Z., Jiang H. and Li M.* (2015) Investigations of interactions between bus rapid transit and general traffic flows. Journal of Advanced Transportation, 49(3), pp, 326-340. (SCI, 影响因子2.249)
    [17] Chen X., Zhang L.*, He X., Xiong C. and Li Z. (2014) Surrogate-based optimization of expensive-to-evaluate objective for optimal highway toll charges in transportation network. Computer-Aided Civil and Infrastructure Engineering, 29(5), pp. 359-381. (SCI/SSCI, 影响因子10.066)
    [16] Jiang X.*, Zhang L. and Chen X. (2014) 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 in China. Transportation Research Part C: Emerging Technologies, 44, pp. 110-127. (SCI, 影响因子9.022)
    [15] Li L., Chen X.* and Zhang L. (2014) Multimodel ensemble for traffic state estimations. IEEE Transactions on Intelligent Transportation Systems, 15(3), pp. 1323-1336. (SCI, 影响因子9.551)
    [14] Chen X., Li Z., Li L.* (2014) A traffic breakdown model based on queueing theory. Networks and Spatial Economics, 14(3-4), pp. 485-504 (SCI/SSCI, 影响因子2.484)
    [13] Chen X., Yin M., Song M., Zhang L. and Li M.* (2014) Social welfare maximization of multimodal transportation: Theory, metamodel, and application to Tianjin Ecocity, China. Journal of Transportation Research Board: Transportation Research Record, 2451, pp. 36-49. (SCI, 影响因子2.019)
    [12] Chen X., Li Z., Li L.* and Shi Q. (2014) Characterizing scattering features in flow-density plots using a stochastic platoon model. Transportmetrica A: Transport Science, 10(9), pp. 820-845. (SCI/SSCI, 影响因子3.277)
    [11] Li L., Chen X.*, Li Z. and Zhang L. (2013) Freeway travel-time estimation based on temporal-spatial queueing model. IEEE Transactions on Intelligent Transportation Systems, 14(3), pp. 1536-1541. (SCI, 影响因子9.551)
    [10] Li L.*, Chen X. and Li Z. (2013) Asymmetric stochastic Tau theory in car-following. Transportation Research Part F: Traffic Psychology and Behaviour, 18, pp. 21-33. (SSCI, 影响因子4.349)
    [9] Chen X., Li L.* and Li Z. (2012) Phase diagram analysis based on a temporal-spatial queueing model. IEEE Transactions on Intelligent Transportation Systems, 13(4), pp. 1705-1716. (SCI, 影响因子9.551)
    [8] Yin S., Chen X., Li M.*, Shi Q. and Li Z. (2012) Evaluation of accident induced indirect costs for measuring penalties on violations of laws. Journal of Transportation Research Board: Transportation Research Record, 2317, pp. 111-120. (SCI, 影响因子2.019)
    [7] Fang J.*, Qin Z., Chen X., Xu Z. and Jiang Z. (2012) Decentralized cooperation strategies in two-dimensional traffic of cellular automata. Communications in Theoretical Physics, 58(06), pp. 883-890. (SCI, 影响因子2.877)
    [6] Fang J.*, Qin Z., Chen X., Leng B. and Xu Z. (2012) Jamming transition of point-to-point traffic through co-operative mechanisms. International Journal of Modern Physics C, 23(11), p. 1250077. (SCI, 影响因子1.353)
    [5] Chen X., Li L.* and Zhang Y. (2010) A Markov model for headway/spacing distribution of road traffic. IEEE Transactions on Intelligent Transportation Systems, 11(4), pp. 773-785. (SCI, 影响因子9.551)
    [4] Chen X.*, Shi J., Xie W. and Shi Q. (2010) Perturbation and stability analysis of the multi-anticipative intelligent driver model. International Journal of Modern Physics C, 21(5), pp. 647-668. (SCI, 影响因子1.353)
    [3] Chen X., Li L.*, Jiang R. and Yang X. (2010) On the intrinsic concordance between the wide scattering feature of synchronized flow and the empirical spacing distributions. Chinese Physics Letter, 27(7), 074501. (SCI, 影响因子2.293)
    [2] Fang J.*, Shi J., Chen X. and Qin Z. (2010) A two-dimensional CA traffic model with dynamic route choices between residence and workplace. International Journal of Modern Physics C, 21(2), pp. 221-237. (SCI, 影响因子1.353)
    [1] Chen X., Shi Q. and Li L.* (2010) Location specific cell transmission model for freeway traffic. Tsinghua Science and Technology, 15(4), pp. 475-480. (SCI, 影响因子3.515)

    三、国内期刊论文
    [16] 陈喜群*, 钱忆薇, 莫栋 (2023) 电动汽车充电平台充电桩数量和价格协同优化. 浙江大学学报(工学版), in press. (EI)
    [15] 陈喜群*, 朱奕璋, 吕朝锋 (2023) 基于混合近端策略优化的交叉口信号相位与配时优化方法. 交通运输系统工程与信息, in press. (EI)
    [14] 陈喜群*, 曹震, 莫栋 (2022) 融合卡尔曼滤波的高速公路状态估计误差界限分析. 交通运输系统工程与信息, 22(4), 72-78. (EI)
    [13] 陈启香, 吕斌*, 陈喜群, 郝斌斌, 何佳曦 (2022) 空间异质性建成环境对出租车与地铁竞合关系的影响. 交通运输系统工程与信息, 22(3), 25-35. (EI)
    [12] 雷嘉薇, 唐薇, 王喆冰, 孙剑桥, 陈喜群* (2022) 空港枢纽停车场用户支付意愿模型. 交通运输研究, 8(2), 39-48.
    [11] 陈喜群*, 曹震, 沈楼涛, 李俊懿 (2021) 融合路段传输模型和深度学习的城市路网短时交通流状态预测. 中国公路学报, 34(12), 203-216. (EI)
    [10] 陈喜群* (2021) 网约共享出行研究综述. 交通运输系统工程与信息, 21(5), 77-90. (EI)
    [9] 刘攀*, 刘志远, 田琼, 贾斌, 陈喜群 (2021) 城市多模式交通供需平衡机理与仿真系统研究. 中国基础科学, 23(1), 57-66.
    [8] 陈喜群*, 周凌霄, 曹震 (2020) 基于图卷积网络的路网短时交通流预测研究. 交通运输系统工程与信息, 20(4), 49-55. (EI)
    [7] 代宗, 陈喜群, 姜锐, 丁中俊* (2020) 曼哈顿网络中的网约车共乘系统的建模与优化. 合肥工业大学学报(自然科学版), 43(8), 1115-1121.
    [6] 陈喜群*, 刘教坤, 胡浩强, 崔尓佳, 张帅超 (2018) 网络行程时间可靠性评价方法与影响因素. 交通运输工程学报, 18(4), 1-11. (EI)
    [5] 张帅超, 朱谊, 陈喜群* (2018) 基于移动检测数据的宏观基本图特征. 浙江大学学报(工学版), 52(7), pp. 1338-1344. (EI)
    [4] 倪玲霖, 张帅超, 陈喜群* (2017) 基于手机信令数据的居民出行空间效应. 浙江大学学报(工学版), 51(5), pp. 887-895. (EI)
    [3] 陈喜群, 杨新苗*, 李力, 史其信 (2010) 基于智能交通信息的预期与适应性元胞传输模型. 控制理论与应用, 27(12), pp. 1591-1597. (EI)
    [2] 陈喜群, 李瑞敏* (2007) 基于仿真的交通信号控制优化策略研究. 交通与计算机, 25(5), pp. 17-20.
    [1] 陈喜群, 郑思齐* (2007) 平均收益期在工程投资互斥方案评价中的应用. 土木工程学报, 40(11), pp. 104-109. (EI)

    四、国际会议论文
    [77] Ye A., Zhou Q., Liu X., Zhang Y., Li J., Tao Z., Bell M. G. H., Bhattacharjya J., Ben S., Chen X., Hu S.* (2022) Modeling and managing an on-demand meal delivery system with mixed autonomy. The 25th IEEE International Conference on Intelligent Transportation Systems, Macau, China, October 8-12, 2022. (EI)
    [76] Shu S., Chen Z., Yu Z., Cao S., Wu G., Shi D., Wang G., Liu Z., Chen X., Na X., Wu C., Hu S.* (2022) Modeling freight-sharing platform operations for optimal compensation strategy using Markov decision processes. The 25th IEEE International Conference on Intelligent Transportation Systems, Macau, China, October 8-12, 2022. (EI)
    [75] Hu Q., Chen X., Hu S.* (2022) An optimization model for shared autonomous taxi routing in the network with parking facilities. The 101st Annual Meeting of Transportation Research Board, Washington DC, United States, January 9-13, 2022.
    [74] Zhu Z., Xu M., Di Y., Yu J. and Chen X.* (2022) Spatial-temporal modeling of ride-sourcing order matching and passenger pickup processes based on additive Gaussian process models. The 101st Annual Meeting of Transportation Research Board, Washington DC, United States, January 9-13, 2022.
    [73] Zhu Z., Xu M., Di Y., Yu J. and Chen X.* (2021) Modeling ride-sourcing order matching and passenger pickup processes based on additive Gaussian process models. The 25th International Conference of Hong Kong Society for Transportation Studies, Hong Kong, December 9-10, 2021.
    [72] Mo D., Chen X.*, Zhang J. (2021) Modeling and managing mixed on-demand ride services of human-driven vehicles and autonomous vehicles. The 12nd International Workshop on Computational Transportation Science (CTS), Harbin, China, July 28-30, 2021. (会议最佳论文奖)
    [71] Li J., Zhang K., Shen L., Wang Z., Guo F., Angeloudis P., Chen X., Hu S.* (2021) A domain adaptation framework for short-term traffic prediction. The 24th IEEE International Conference on Intelligent Transportation Systems, Indianapolis, IN, USA, September 19-22, 2021. (EI)
    [70] Mo D., Zheng S. and Chen X.* (2021) Modeling morning commute problem with real-time ridesharing services. The 20th and 21st Joint COTA International Conference of Transportation Professionals, Xi'an, China, July 2-5, 2021. (EI)
    [69] Zhang J., Geng M., Gu J. and Chen X.* (2021) Short-term speed forecasting of large-scale urban road network based on Transformer. The 20th and 21st Joint COTA International Conference of Transportation Professionals, Xi'an, China, July 2-5, 2021. (EI)
    [68] Ye A., Chen X., Wu C. and Hu S.* (2020) A new assessment framework for TOD design: Lessons learned from Chinese cities. The 20th COTA International Conference of Transportation Professionals, Xi'an, China, July 4-6, 2020. (EI)
    [67] Zhu J., Mo D. and Chen X.* (2020) A grouping approach to ridesplitting optimization. The 20th COTA International Conference of Transportation Professionals, Xi'an, China, July 4-6, 2020. (EI)
    [66] Yao F., Chen X.*, Angeloudis P., and Zhang W. (2020) Agent-based modeling and simulation for systematic operations of shared automated electric vehicles. The 20th COTA International Conference of Transportation Professionals, Xi'an, China, July 4-6, 2020. (EI)
    [65] Zhang J., Chen X.* and Wang Z. (2020) On network effects in the ride-sourcing market with heterogeneous users. The 20th COTA International Conference of Transportation Professionals, Beijing, China, July 4-6, 2020. (EI)
    [64] Ni L., Chen C. and Chen X.* (2020). Network equilibrium analysis of competitive ride-sourcing market. The 99th Annual Meeting of Transportation Research Board, Washington DC, United States, January 12-16, 2020.
    [63] Shen L., Shao Z., Yu Y. and Chen X.* (2020). Short-term forecasting of metro transit passenger flows: A hybrid approach combining modified gravity model and deep learning. The 99th Annual Meeting of Transportation Research Board, Washington DC, United States, January 12-16, 2020.
    [62] Zhu Z., Sun L., Chen X.* and Yang H. (2020). Bayesian supervised learning and latent class analysis of dynamic ridesharing behavior via probabilistic tensor factorization. The 99th Annual Meeting of Transportation Research Board, Washington DC, United States, January 12-16, 2020.
    [61] Zhu Z., Sun L., Chen X.* and Yang H. (2019) Understanding ride-sharing behavior in a ride-sourcing market using Bayesian conditional tensor factorization. The 24th International Conference of Hong Kong Society for Transportation Studies, Hong Kong, December 14-16, 2019.
    [60] Chen X., Chen C., Xie W.* (2019) Optimal spatial pricing for an on-demand ride-sourcing service platform. The 11th International Workshop on Computational Transportation Science (CTS), Tianjin, China, June 28-30, 2019. (会议最佳论文奖)
    [59] Chen X., Mo D., Ouyang Y.* (2019) Optimal pricing strategies of ridesharing platform for morning commute problem. The 11th International Workshop on Computational Transportation Science (CTS), Tianjin, China, June 28-30, 2019.
    [58] Ke J., Cen X., Yang H. and Chen X.* (2019). Modelling the working and recharging schedules of electric-vehicle drivers in a ride-sourcing market. The 98th Annual Meeting of Transportation Research Board, Washington DC, United States, January 13-17, 2019.
    [57] Zhang S. and Chen X.* (2019). Gradient boosting regression tree for urban link travel speed. The 98th Annual Meeting of Transportation Research Board, Washington DC, United States, January 13-17, 2019.
    [56] Ke J., Cen X., Yang H., Chen X.*, Ye J. (2018) Modelling ride-sourcing market equilibrium with battery electric vehicles. The 23rd International Conference of Hong Kong Society for Transportation Studies, Hong Kong, December 8-10, 2018.
    [55] Kong K., Ma Y., Ye C., Lu J., Chen X., Zhang W. and Chen W.* (2018) A visual analytics approach for traffic flow prediction ensembles. In Proceedings of Pacific Graphics, Hong Kong, October 8-11, 2018.
    [54] Chen X., Mo D., Ouyang Y.* (2018) Optimal pricing strategies of the ridesharing platform based on multi-modal equilibrium model. The 10th International Workshop on Computational Transportation Science (CTS), Beijing, China, July 10-11, 2018.
    [53] Yu J., Wang S., Li L. and Chen X.* (2018) Traffic flow prediction based on probe vehicle GPS traces considering temporal and spatial correlations. The 18th COTA International Conference of Transportation Professionals, Beijing, China, July 5-8, 2018. (EI)
    [52] Zhou L. and Chen X.* (2018) Short-term forecasting of traffic flow and speed: A deep learning approach. The 18th COTA International Conference of Transportation Professionals, Beijing, China, July 5-8, 2018. (EI)
    [51] Zhan X., Zhang S., Szeto W. Y. and Chen X.* (2018). Multi-step-ahead traffic flow forecasting using multi-output gradient boosting regression tree. The 97th Annual Meeting of Transportation Research Board, Washington DC, United States, January 7-11, 2018.
    [50] Zheng H., Chen X. and Chen X.* (2018). How does on-demand ridesplitting influence vehicle use and ownership? A case study in Hangzhou, China. The 97th Annual Meeting of Transportation Research Board, Washington DC, United States, January 7-11, 2018.
    [49] Chen X., Zheng H., Wang Z. and Chen X.* (2018) Exploring on-demand ridesplitting behavior and impact on mobility: A case study in Hangzhou, China. The 97th Annual Meeting of Transportation Research Board, Washington DC, United States, January 7-11, 2018.
    [48] Ye Y. and Chen X.* (2018) Simulation-based optimization for time-of-day coordinated ramp metering of a large-scale urban expressway network. The 97th Annual Meeting of Transportation Research Board, Washington DC, United States, January 7-11, 2018.
    [47] Ke J., Zheng H., Yang H. and Chen X.* (2017) Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach. The 9th International Workshop on Computational Transportation Science (CTS), Lanzhou, China, July 13-15, 2017. (会议最佳论文奖)
    [46] Zheng H., Chen X. and Chen X.* (2017) Random forests for freeway short-term traffic speed prediction. The 17th COTA International Conference of Transportation Professionals, Shanghai, China, July 7-9, 2017. (EI)
    [45] Zhang S., Zhan X. and Chen X.* (2017) Gradient boosting regression tree for traffic flow prediction considering temporal and spatial correlations. The 17th COTA International Conference of Transportation Professionals, Shanghai, China, July 7-9, 2017. (EI)
    [44] Liu J., Cui E., Hu H., Chen X. and Chen X.* (2017) Short-term forecasting of emerging on-demand ride services. The 4th International Conference on Transportation Information and Safety, Banff, Alberta, Canada, August 8-10, 2017. (EI)
    [43] Ni L., Wang X. and Chen X.* (2017) A spatial econometric model for travel flow analysis and real-world applications with massive mobile phone data. The 96th Annual Meeting of Transportation Research Board, Washington DC, United States, January 8-11, 2017.
    [42] Jiang Z., Chen X.* and Ouyang Y. (2017) Traffic state and emission estimation for urban expressways. The 96th Annual Meeting of Transportation Research Board, Washington DC, United States, January 8-11, 2017.
    [41] Ke J., Zhang S. and Chen X.* (2017) Missing information imputation for traffic incident likelihood prediction for urban expressways. The 96th Annual Meeting of Transportation Research Board, Washington DC, United States, January 8-11, 2017.
    [40] Zhang S. and Chen X.* (2017) Rolling horizon optimization for traffic state estimation and prediction. The 96th Annual Meeting of Transportation Research Board, Washington DC, United States, January 8-11, 2017.
    [39] Zhu Z., Xiong C., Chen X.* and Zhang L. (2017) Calibrating supply parameters of large-scale dynamic traffic assignment models with simulation-based optimization. The 96th Annual Meeting of Transportation Research Board, Washington DC, United States, January 8-11, 2017.
    [38] Chen X., Zhang S. and Zahiri M. (2016) Cellular signaling data driven simulation-based dynamic traffic assignment and its applications to a real-world road network. The 19th International IEEE Conference on Intelligent Transportation Systems, Rio de Janeiro, Brazil, November 1-4, 2016. (EI, ISTP)
    [37] Zhu Z., Tang L., Chen X. and Zhang L.* (2016) Travel mode choice decision making via Bayesian decision network. The 95th Annual Meeting of Transportation Research Board, Washington DC, United States, January 10-14, 2016.
    [36] Jiang X., Zhang L., Lu W. and Chen X.* (2016) Competition between high-speed rail and airline based on game theory. The 95th Annual Meeting of Transportation Research Board, Washington DC, United States, January 10-14, 2016.
    [35] Xiong C., Yang D., Chen X. and Zhang L.* (2016) A mixed Bayesian network for two-dimensional decision modeling of departure time and lane choice. The 14th World Conference on Transport Research, Shanghai, China, July 10-15, 2016. 
    [34] Xiong C., Yang D., Chen X. and Zhang L.* (2015) On model transferability: A Bayesian approach to calibrating travel demand models. The 14th International Conference Travel Behaviour Research, Beaumont Estate, Windsor, United Kingdom, July 19-23, 2015.
    [33] Chen X., Zhang L.*, He X. and Xiong C. (2015) Simulation-based pricing optimization for improving network-wide travel time reliability. The 6th International Symposium on Transportation Network Reliability, Nara, Japan, August 2-3, 2015.
    [32] Xiong C., Chen X., He X. and Zhang L.* (2015) Simulation-based optimal travel information provision strategies: An agent-based approach under uncertainty. The 6th International Symposium on Transportation Network Reliability, Nara, Japan, August 2-3, 2015.
    [31] Zhu Z., Xiong C., Chen X., He X. and Zhang L.* (2015) Integrating dynamic traffic assignment and agent-based travel behavior models for cumulative land development impact analysis. The 7th International Symposium on Travel Demand Management, Tucson, Arizona, United States, April 13-15, 2015.
    [30] Chen X., Xiong C., He X., Zhu, Z. and Zhang L.* (2015) Congestion pricing for improving network service: A simulation-based optimization approach. The 94th Annual Meeting of Transportation Research Board, Washington DC, United States, January 11-15, 2015.
    [29] Chen X., He X., Xiong C. and Zhang L.* (2015) A Bayesian stochastic Kriging metamodel for simultaneous optimization of travel behavioral responses and traffic management. The 94th Annual Meeting of Transportation Research Board, Washington DC, United States, January 11-15, 2015.
    [28] He X., Chen X., Xiong C., Zhu Z. and Zhang L.* (2015) Integrated optimization of transportation demand management and traffic operations using simulation: A bootstrapped support vector regression method considering the statistical distribution of simulation noise. The 94th Annual Meeting of Transportation Research Board, Washington DC, United States, January 11-15, 2015.
    [27] Xiong C., Chen X., He X. and Zhang L.* (2015) Multidimensional travel decision-making: Descriptive behavioral theory and agent-based models. The 94th Annual Meeting of Transportation Research Board, Washington DC, United States, January 11-15, 2015.
    [26] Lu Y., Chen X. and Zhang L.* (2015) A national travel demand model for the U.S.: A person-based microsimulation approach. The 94th Annual Meeting of Transportation Research Board, Washington DC, United States, January 11-15, 2015.
    [25] Ni W., Chen X. and Li M.* (2015) An extended generalized filter algorithm for urban expressway traffic state estimations based on heterogeneous data. The 94th Annual Meeting of Transportation Research Board, Washington DC, United States, January 11-15, 2015.
    [24] Wang Z., Chen X., Ouyang Y. and Li M.* (2015) Emission mitigation via longitudinal control of intelligent vehicles in a congested platoon: An exploratory study. The 94th Annual Meeting of Transportation Research Board, Washington DC, United States, January 11-15, 2015.
    [23] Chen X., Zhu Z., Zhang L.* (2014) Simulation-based optimization of mixed road pricing policies in a large real-world network. European Transport Conference, Frankfurt, Germany, September 29-October 1, 2014. (EI)
    [22] Zhang L., Chen X.*, He X., and Xiong C. (2014) Bayesian stochastic Kriging metamodel for active traffic management of corridors. IIE Annual Conference and Expo, Montreal, Canada, May 31-June 3, 2014. (EI)
    [21] Chen X., Wang F., Li Z. and Li L.* (2013) An asymmetric stochastic car-following model based on extended Tau Theory. The Sixth International Conference on Nonlinear Mechanics, Shanghai, China, August 12-15, 2013. (ISTP) (会议最佳论文奖)
    [20] Chen X., Lin X., Xu D., Wang Y. and Li M.* (2013) Applying least squares support vector machines for prediction of red-light-running based on continuous vehicle trajectories measurements. The 93rd Annual Meeting of Transportation Research Board, Washington DC, United States, January 12-16, 2014.
    [19] Xiong C., Zhu Z., He X., Chen X. and Zhang L.* (2013) A 24-hour large-scale microscopic simulation case study of inter-county connector in Maryland. The 93rd Annual Meeting of Transportation Research Board, Washington DC, United States, January 12-16, 2014.
    [18] He X., Chen X., Xiong C. and Zhang L.* (2013) Simulation-based optimization for highway toll charge using surrogate modeling. Conference on Agent-Based Modeling in Transportation Planning and Operations, Blacksburg, Virginia, United States, September 30-October 2, 2013.
    [17] Xiong C., Chen X., He X. and Zhang L.* (2013) Modeling agents’ en-route diversion behavior and its operations applications. Conference on Agent-Based Modeling in Transportation Planning and Operations, Blacksburg, Virginia, United States, September 30-October 2, 2013.
    [16] Zou M., Chen X., Yu H., Huang Z. and Li M.* (2013) Dynamic transportation planning and operations: Concept, framework and applications in China. The 13th COTA International Conference of Transportation Professionals, Shenzhen, China, August 13-16, 2013. (EI)
    [15] Song M., Yin M., Chen X., Zhang, L. and Li, M.* (2013) A simulation-based approach for sustainable transportation systems evaluation and optimization: Theory, systematic framework and applications. The 13th COTA International Conference of Transportation Professionals, Shenzhen, China, August 13-16, 2013. (EI)
    [14] Chen X., Xu D., Lin X., Cui X., Sun T. and Li, M.* (2013) Connected vehicle based dynamic all-red extension for adaptive signalized intersections. The 20th ITS World Congress, Tokyo, Japan, October 14-18, 2013. (EI)
    [13] Chen X., Li M.*, Jiang H. and Li Z. (2013) An empirical assessment of interactions between bus rapid transit and general traffic flows. The 92nd Annual Meeting of Transportation Research Board, Washington DC, United States, January 13-17, 2013.
    [12] Chen X., Li Z, Li M. and Li L.* (2012) Shockwave induced multistate Log-normal mixture model for oscillating travel time. The Annual Conference of the Canadian Society for Civil Engineering, Edmonton, Canada, June 6-9, 2012. (EI)
    [11] Chen X., Li M.*, Zhang L. and Li Z. (2012) Comparison of highway traffic breakdown features between U.S. and China using discrete wavelet transform: An empirical study. The 12th COTA International Conference of Transportation Professionals, CICTP 2012, Beijing, China, August 3-6, 2012. (EI, ISTP)
    [10] Chen X., Li L.*, Shi Q. and Cao J. (2010) Equilibrium analysis and comparison for general CTMs and LCTMs. The 13th International IEEE Conference on Intelligent Transportation Systems, ITSC 2010, Madeira Island, Portugal, September 19-22, 2010. (EI, ISTP)
    [9] Sun L.*, Chen X., Xie W. and Yang X. (2010) Calibration of acceleration-based and multi-anticipative car-following models by NGSIM trajectory data. In Proceedings of the 10th ASCE International Conference of Chinese Transportation Professionals, ICCTP 2010, Beijing, China, August 4-8, 2010. (EI)
    [8] Chen X., Li R.*, Xie W. and Shi Q. (2009) Stabilization of traffic flow based on multi-anticipative intelligent driver model. In Proceedings of the 12th International IEEE Conference on Intelligent Transportation Systems, ITSC 2009, St. Louis, MO, USA, October 3-7, 2009, pp. 72-77. (EI, ISTP)
    [7] Chen X.*, Yang X. and Shi Q. (2009) Traffic analysis zone based urban activity study with aggregate mobile network data. In Proceedings of the 2009 International IEEE Conference on Management and Service Science, MASS 2009, Beijing, China, September 20-22, 2009. (EI)
    [6] Qian R.*, Shi Q., Chen X. and Zhang L. (2009) Analysis of environmental conditions for dangerous goods transportation by container. In Proceedings of the 5th Japan-China Joint Seminar on City and ITS “Low-Carbon Urban Planning and Transportation Policies”, Hiroshima, Japan, August 23-24, 2009, pp. 76-81.
    [5] Fang Y., Chen X. and Yang X.* (2009) Evaluation and optimization of public transport subsidies for alternative energy. In Proceedings of the 9th ASCE International Conference of Chinese Transportation Professionals, ICCTP 2009, Harbin, China, August 5-9, 2009, pp. 3105-3111. (EI)
    [4] Chen X., Li R.*, Lu H. and Zhang J. (2009) Spatio-temporal evolution of traffic congestions on urban freeways. In Proceedings of the 2nd ASCE International Conference of Transportation Engineering, ICTE 2009, Chengdu, China, July 25-27, 2009, pp. 1643-1648. (EI)
    [3] Chen X.*, Shi Q., Qian R. and Yang X. (2009) Evolutionary algorithm of port based location routing problem. In Proceedings of the 2009 WRI Global Congress on Intelligent Systems, GCIS 2009, Xiamen, China, May 19-21, 2009, pp. 14-18. (EI)
    [2] Chen X.*, Yang X. and Shi Q. (2008) Estimation of vehicle usage rate based on capture-recapture model with license plate recognition data. In Proceedings of the 11th International IEEE Conference on Intelligent Transportation Systems, ITSC 2008, Beijing, China, October 12-15, 2008, pp. 139-144. (EI, ISTP)
    [1] Chen X.*, Yang X. and Shi Q. (2008) Vehicle usage rate estimation based on capture-recapture method using license plate recognition data. In Proceedings of the 9th Intelligent Transport Systems Asia-Pacific Forum & Exhibition, Singapore, July 14, 2008.

    五、授权发明专利
    [9] 王萌, 陈喜群. 交通流信息获取的方法、装置和计算机设备. 公开号: CN112863174A, 2021年5月28日.
    [8] 陈喜群, 张帅超, 周凌霄, 于静茹, 姚富根, 莫栋. 一种基于深度集成学习的城市大规模路网交通速度预测方法. 专利号: ZL201910496746.9
    [7] 柯锦涛, 杨海, 郑宏煜, 陈喜群, 贾倚天, 龚平华, 叶杰平. 一种地理区域内网约车供需缺口预测方法. 公开号: CN109948822A, 2019年6月28日.
    [6] 陈喜群, 张帅超, 陈笑微, 陈楚翘, 郑宏煜, 刘教坤, 胡浩强, 崔尔佳. 一种基于路网行程时间可靠性的出行预留时间计算方法. 专利号: ZL201610948476.7
    [5] 陈喜群, 张帅超, 郑宏煜, 陈笑微, 陈楚翘, 周凌霄, 于静茹. 基于融合数据的城市快速路交通状态滚动预测方法. 专利号: ZL201610970246.0
    [4] 陈喜群, 张帅超, 陈楚翘, 陈笑微, 郑宏煜, 沈凯, 叶韫, 孙闻聪. 一种利用手机信令大数据和动态交通分配的OD标定方法. 专利号: ZL201610935968.2
    [3] 陈喜群, 张帅超, 郑宏煜, 陈楚翘, 陈笑微, 于静茹, 周凌霄. 基于融合数据的城市快速路交通状态滚动估计方法. 专利号: ZL201610970510.0
    [2] 陈喜群, 张帅超, 陈笑微, 郑宏煜, 陈楚翘, 胡浩强, 刘教坤, 崔尔佳. 一种基于网络约租车数据的路网行程时间可靠性评价方法. 专利号: ZL201610946924.X
    [1] 柳展, 陈喜群, 樊锦祥, 陈才君, 张帅超, 张书浆. 一种基于微波数据的交通流基本图参数标定方法. 公开号: CN105513357A, 2016年8月17日.

    六、会议演讲/摘要
    [11] Chen X.* (2017) Should on-demand ride services be regulated? An analytical evaluation of Chinese government policies. 2017 China-UK Researcher Links Workshop on Design and Optimization of Transport Systems in the Context of Urbanization, Shanghai, China, July 10-12, 2017.
    [10] Chen X.* (2017) Adaptive rolling smoothing with heterogeneous data for traffic state estimation and prediction. The 17th COTA International Conference of Transportation Professionals (CICTP 2017), Shanghai, China, July 7-9, 2017.
    [9] 陈喜群*. (2017) 网约车平台供需平衡机理与时空演化规律. 第179期双清论坛“新型城镇化导向下的城市群综合交通系统管理理论与方法”, 北京, 2017年5月22-23日.
    [8] 陈喜群*. (2017) Simulation based optimization (SBO): Surrogate modeling and applications in large-scale transportation systems. 国家自然科学基金创新研究群体项目第二次学术研讨会. 北京, 2017年4月21-22日.
    [7] 陈喜群*. (2016) 网约车平台智能出行分析及交通可靠性评价. 中国科协第308 次青年科学家论坛—未来通信和交通协同发展. 南昌, 2016年11月11-12日.
    [6] 陈喜群*. (2016) 大数据分析:城市机动性、交通规划辅助决策及相关研究问题. 滴滴杭州智能出行大数据发布会. 杭州, 2016年7月27日.
    [5] 陈喜群*. (2016) 基于多模型集成学习的高速/快速路交通状态估计. 第二届高校“交通信息工程及控制”学科青年学者论坛. 成都, 2016年5月21-22日.
    [4] 陈喜群*. (2016) 基于多源异构大数据的城市交通规划辅助决策. 滴滴长三角城市智能出行大数据发布会. 上海, 2016年4月19日.
    [3] Chen X. and Zhang L.* (2014) Congestion pricing for improving network service: A simulation-based optimization approach. INFORMS 2014 Annual Meeting, San Francisco, California, November 9-12, 2014.
    [2] Chen X., Zhang L.*, He X. and Xiong C. (2013) A simulation based optimization method in determining time varying pricing of toll roads. The XXVI EURO-INFORMS Joint International Conference, Rome, Italy, June 30-July 4, 2013.
    [1] Chen X.*, Yang X., Xie W. and Sun L. (2010) Intelligent transportation system modeling using synchronized multi-video processing technology. The 13th Annual NACOTA/WCTA Technical Symposium on Sustainable Transportation Development in China, Washington, DC, United States, January 10, 2010.

    七、国内会议论文
    [4] 陈喜群, 张帅超, 沈凯, 叶韫, 孙闻聪 (2016) 大数据驱动的动态交通分配仿真及实证研究. 第十一届中国智能交通年会论文集, 重庆, 2016年11月16-18 日.(优秀论文奖)
    [3] 陈喜群, 杨新苗*, 秦旭彦, 史其信 (2009) 智能驾驶员模型及稳定性分析. 第五届中国智能交通年会优秀论文集, 深圳, 2009年12月11-13日, pp. 87-92.
    [2] 郑岩丁, 陈喜群, 杨新苗* (2008) 夜间占道作业安全调研与改善措施. 第三届中国国际交通安全论坛论文集, 北京, 2008年11月24-25日, pp. 272-279.
    [1] 陈喜群, 杨新苗*, 史其信 (2008) 城市道路车牌识别系统在交通管理中的应用. 第四届中国智能交通年会论文集, 青岛, 2008年9月26-27 日, pp. 271-276.
     
    八、其他论著
    [2] 北京市地方标准(DB11/854-2012)《占道作业交通安全设施设置技术要求》, 北京市质量技术监督局, 2012年9月1日发布, 主要起草人.
    [1] 2008清华大学优秀毕业论文, 面向港口转运中心选址模型的遗传算法研究, 史其信教授指导.
     
  • 研究方向
    • 交通运输规划与管理
    • 共享出行
    • 交通流建模与仿真
    • 智能交通系统
  • 授课情况
    • 交通系统分析,本科生专业课
    • 交通大数据分析,研究生专业学位课
    • 交通运输工程科学与技术前沿,博士生专业学位课
  • 获奖情况
    • 2022 美国斯坦福大学全球前2%顶尖科学家榜单(物流与交通运输领域)
    • 2021 浙江大学建筑工程学院优秀共产党员荣誉称号
    • 2021 浙江大学建筑工程学院土木建筑规划教育基金教学先进奖
    • 2021 浙江省教学成果奖二等奖(4/9)全球化背景下土建类研究生培养国际化提升
    • 2021 浙江大学教学成果奖一等奖(4/9)土建类研究生“高水平-多层次- 全方位”国际化人才培养体系创建与实践
    • 2021 浙江大学教学成果奖一等奖(6/8)“土水交融通”的新工科人才培养探索与实践
    • 2021 第12届计算交通科学国际研讨会(CTS 2021)最佳论文奖
    • 2021 中国交通运输协会科技创新青年奖
    • 2020 浙江省优秀研究生教学案例
    • 2019 浙江大学优质教学奖二等奖
    • 2019 国家自然科学基金优秀青年基金获得者
    • 2019 中国管理科学与工程学会供应链与运营管理分会年会(ISCOM 2019)优秀论文奖
    • 2019 第11届计算交通科学国际研讨会(CTS 2019)最佳论文奖
    • 2018 中国科协青年人才托举工程
    • 2017 浙江大学校级先进工作者
    • 2017 中国智能交通协会科学技术奖二等奖(第一完成人)
    • 2017 第9届计算交通科学国际研讨会(CTS 2017)最佳论文奖
    • 2017 The First Prize, College of Supply Chain Management Student Paper Competition, Annual POMS Conference
    • 2016 浙江大学优秀研究生德育导师
    • 2016 浙江大学建工学院“我最喜爱的老师”
    • 2016 浙江省特聘专家
    • 2016 浙江省自然科学基金杰出青年项目获得者
    • 2016 第十一届中国智能交通年会优秀论文奖会议最佳论文奖
    • 2013 IEEE Intelligent Transportation Systems Society Best Ph.D. Dissertation Awards(智能交通学会最佳博士论文奖,全球平均每年评选2篇)
    • 2013 清华大学优秀博士论文(前10%)
    • 2013 北京市优秀毕业生(前5%)
    • 2013 会议最佳论文奖(The 6th Int. Conference on Nonlinear Mechanics)
    • 2012 清华大学研究生国家奖学金(前10%)
    • 2012 清华之友–中国石油奖学金(综合优秀一等奖)
    • 2012 STC Consortium/UT-MOELAB Student Poster Competition (2nd Prize)
    • 2011 国家留学基金委–高水平大学公派研究生项目联合培养博士生奖学金
    • 2011 清华土木工程系、建设管理系“学术新秀”提名奖
    • 2010 清华之友–中国航天科技CASC 一等奖学金(综合优秀一等奖)
    • 2009 清华校友–梅贻琦纪念奖学金(综合优秀二等奖)
    • 2009 清华大学土木水利学院优秀助教
    • 2008 清华大学本科生优秀毕业论文
    • 2007 清华之友–郑格如二等奖学金
    • 2007 第二届全国大学生交通科技竞赛二等奖、优秀奖
    • 2006 中国建设银行二等奖学金
    • 2006 清华大学暑期社会实践金奖第一名, 赴贵州黎平“重走长征路”
    • 2005 金门三等奖学金
    • 2005 清华大学优秀紫荆志愿者
陈喜群
陈喜群