2019年

发布者:莫栋发布时间:2019-12-28浏览次数:147

[1]  梅振宇, 章伟. 基于复杂性测度的泊位占有率序列动力学分析[J]. 浙江大学学报(工学版), 2018(4).

[2]  朱文韬, 钱国敏, 王殿海, 马东方. 考虑路口上游停靠站影响的公交延误模型[J]. 浙江大学学报(工学版), 2019.

[3]  王芳杰, 王福建, 王雨晨, 边驰. (2019) 基于LightGBM算法的公交行程时间预测[J]. 交通运输系统工程与信息, 19(2): 116-121. (EI)

[4]  方守恩,曲小波,王亦兵,刘洋泽西. (2019) 基于强化协作博弈方法的双车道混合交通流特性[J]. 同济大学学报(自然科学版), 47(7): 976-983. (EI)

[5]    Wang,  D., Cai, Z., Cui, Y., & Chen, X. (2019).Nonnegative tensor  decomposition for urban mobility analysis and applications with mobile  phone data, Transportmetrica A: Transport Science, DOI:  10.1080/23249935.2019.1692961

[6]    Dongfang Ma, Bowen Sheng, Dianhai Wang, Sheng Jin* and Xiang Song. Prompt prediction of spillovers in urban street networks by using rolling time occupancy data. Transportmetrica A: Transport Science, 2019, 15(2), 1041-1060.

[7]     Xu Wang, Xiaobo Qu, Sheng Jin*. Hotspot Identification Considering Daily Variability of Traffic Flow and Crash Record: A Case Study. Journal of Transportation Safety & Security, 2019. DOI: 10.1080/19439962.2018.1477893

[8]     Sheng Jin, Liang Xu, Cheng Xu, Dongfang Ma. Lane Width based Cellular Automata Model for Mixed Bicycle Traffic Flow. Computer - Aided Civil and Infrastructure Engineering, 2019, 2019, 34(8), 696–712.

[9]   Cheng Xu, Haifeng Guo, Liang Xu, Sheng Jin*. Speeding behavior and speed limits for heterogeneous bicycle flow. Traffic Injury Prevention, 2019, 20(7), 759-763.

[10]     Xiaoqin Luo, Sheng Jin*, Yue Gong, Dianhai Wang, Dongfang Ma. Queue length estimation for signalized intersections using License Plate Recognition data. IEEE Intelligent Transportation Systems Magazine, 2019, 11(3), 209-220.

[11]    Xiaoqin Luo, Dianhai, Wang, Dongfang, Ma, Sheng Jin*. Grouped travel time estimation in signalized arterials using point-to-point detectors. Transportation Research Part B, 2019, 130, 130-151.

[12]      Zahiri M., Liu J. and Chen X.* (2019) A new approach in efficiency and sustainability of taxi industry. Sustainability, 11(18), 4944. (SCI/SSCI, 影响因子2.592)

[13]      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5.744)

[14]      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5.775)

[15]      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4.051)

[16]      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2.667)

[17]      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5.775)

[18]      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4.253)

[19]      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2.050)

[20]      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1.988)

[21]   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5.744)

[22]   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5.744)

[23]   Zhou L. and Chen X.* (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2.568)

[24]   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3.294)

[25]   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2.229)

[26]   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3.310)

[27]   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.

[28]   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.

[29]   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.

[30]   Mei, Z., Zhang, W., Zhang, L., & Wang, D. (2020). Optimization of reservation parking space configurations in city centers through an agent-based simulation. Simulation Modelling Practice and Theory, 99, 102020

[31]   Mei, Z. Y., Qiu, H., Feng, C., & Cheng, Y. (2019). Research on a forecasting model of tourism traffic volume in theme parks in China. Transportation Safety and Environment, 1(2), 135-144.

[32]   Mei, Z., Feng, C., Ding, W., Zhang, L., & Wang, D. (2019). Better lucky than rich? Comparative analysis of parking reservation and parking charge. Transport Policy, 75(3), 47-56.

[33]   Mei, Z., Zhang, W., Zhang, L., & Wang, D. (2019). Real-time multistep prediction of public parking spaces based on Fourier transform–least squares support vector regression. Journal of Intelligent Transportation Systems, 1-13.

[34]   Mei, Z., Tan, Z., Zhang, W., & Wang, D. (2019). Simulation analysis of traffic signal control and transit signal priority strategies under Arterial Coordination Conditions. Simulation, 95(1), 51-64

[35]   E. Owen D. Waygooda, Yilin Sun, Jan-Dirk Schmöckerc.2019 Transport sufficiency: Introduction & case study. Travel Behaviour and Society. No. 15: 54-62.

[36]    Hongsheng Qi, Xianbiao Hu,Monte Carlo Tree Search-based intersection signal optimization model with channelized section spillover,Transportation Research Part C: Emerging Technologies,Volume 106,2019.

[37]    Hongsheng Qi & Lihui Zhang (2019) Behaviour of channelized section spillover: a numerical simulation study, Transportmetrica A: Transport Science, 15:2, 824-848, DOI: 10.1080/23249935.2018.1538171

[38]    Hongsheng Qi, Mengwei Chen & Dianhai Wang (2019) Recurrent and non-recurrent bottleneck analysis based on traffic state rank distribution, Transportmetrica B: Transport Dynamics, 7:1, 275-294, DOI: 10.1080/21680566.2017.1401496

[39]    Fan P., Guo J., Zhao H., Wijnands J. S. and Wang Y.* (2019) Car-following modeling incorporating driving memory based on autoencoder and long short-term memory neural networks. Sustainability, 11, 6755. (SCI)

[40]    Guo J., Chen X., Pang Y. and Wang Y*. and Zheng P. (2019) Bottlenecks, shockwave, and off-ramp blockage on freeways. Sustainability, 11, 4991. (SCI)

[41]    Liu Y. and Wang Y*. (2019) Managed lane strategies for the mixed traffic with connected and automated vehicles using a reinforcement learning approach. Transportation Research Record, accepted. (SCI)

[42]    Kan Y., Wang Y.*, Wang D., Sun J., Shao C. and Papageorgiou M. (2019) A novel approach to estimating missing pairs of on/off ramp flows. IEEE Transactions on Intelligent Transportation Systems, accepted. (SCI)

[43]    Wang Y.*, Yu X., Zhang S., Zheng P., Zhang L., Hu J. and Cheng S. (2019) Freeway traffic control in presence of capacity drop. IEEE Transactions on Intelligent Transportation Systems, accepted. (SCI)



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