近5年代表性 SCI/EI 国内外论文如下：
< 国际期刊 >
1. Cao, Y., Yao, J., Tang, K., & Kang, Q.. Dynamic origin–destination flow estimation for urban road network solely using probe vehicle trajectory data. Journal of Intelligent Transportation Systems, 1-18,2023.(SCI, Q3)
2. Yao, J., Wu, H., &Tang, K.. A bi-Level programming method for SPaT estimation at fixed-time controlled intersections using license plate recognition data. Transportmetrica B: Transport Dynamics, 11(1), 1045-1070,2023.(SCI, Q2)
3. Tang, K., Chen, S., Cao, Y., Zang, D., & Sun, J.. Lane‐level short‐term travel speed prediction for urban expressways: An attentive spatio‐temporal deep learning approach. IET Intelligent Transport Systems ,2022. (SCI, Q3)
4. Tan, Chaopeng; Yao, Jiarong; Tang, Keshuang. A Matrix Completion Method for Cycle-based Traffic Volume Estimation Using Sampled Trajectory Data. IEEE Transactions on Intelligent Transportation Systems, 2022 (SCI, Q1)
5. Suzuki, Kazufumi; Tang, Keshuang; Alhajyaseen, Wael; Suzuki, Koji; Nakamura, Hideki. An international comparative study on driving attitudes and behaviors based on questionnaire surveys. IATSS research, 2022.(EI)
6. Tan, Chaopeng; Wu Hao; Tang, Keshuang. An Extendable Gaussian Mixture Model for Lane-Based Queue Length Estimation Based on License Plate Recognition Data. Journal of Advanced Transportation,2022.(SCI,Q3)
7. Toriumi, Azusa; Abu-Lebdeh, Ghassan; Alhajyaseen, Wael; Christie, Nicola; Gehlert, Tina; Mehran, Babak; Mussone, Lorenzo; Shawky, Mohamed; Tang, Keshuang; Nakamura, Hideki. A multi-country survey for collecting and analyzing facts related to road traffic safety: legislation, enforcement, and education for safer drivers. IATSS research,2022.(EI)
8. Zang, Di; Ding, Yongjie; Qu, Xiaoke; Miao, Chenglin; Chen, Xihao; Zhang, Junqi; Tang, Keshuang. Traffic-data recovery using geometric-algebra-based generative adversarial network. SENSORS,2022.(SCI,Q2)
9. Zang, Di; Chen, Xihao; Lei, Juntao; Wang, Zengqiang; Zhang, Junqi; Cheng, Jiujun; Tang, Keshuang. A multi‐channel geometric algebra residual network for traffic data prediction. IET Intelligent Transport Systems,2022.(SCI,Q3)
10. Chen, Xuejian; Yin, Juyuan; Qin, Guoyang; Tang, Keshuang; Wang, Yunpeng; Sun, Jian. Integrated macro-micro modelling for individual vehicle trajectory reconstruction using fixed and mobile sensor data. Transportation Research Part C: Emerging Technologies,2022.(SCI,Q1)
11. Xuejian Chen; Juyuan Yin; Keshuang Tang; Ye Tian; Jian Sun. Vehicle Trajectory Reconstruction at Signalized Intersections Under Connected and Automated Vehicle Environment. IEEE Transactions on Intelligent Transportation Systems,2022.(SCI,Q1)
12. Chaopeng Tan, Yujia Shi, LinBai,Keshuang Tang, Kazufumi Suzuki, Hideki Nakamura. Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behavior. IATSS Research,2022.(EI)
13. C Tan, Y Cao, K Tang*. Cumulative Flow Diagram Estimation and Prediction Based on Sampled Vehicle Trajectories at Signalized Intersections. IEEE Transactions on Intelligent Transportation Systems. vol. 23, no. 8, pp. 11325-11337, 2022. (SCI, Q1)
14. C Tan, H Wu, K Tang*, C Tan. An Extendable Gaussian Mixture Model for Lane-Based Queue Length Estimation Based on License Plate Recognition Data. Journal of Advanced Transportation, vol. 2022, Article ID 5119209, 14 pages, 2022. (SCI, Q3)
15. K Tang, H Wu, J Yao, C Tan, Y Ji. Lane-based queue length estimation at signalized intersections using single-section license plate recognition data, Transportmetrica B: Transport Dynamics, 10:1, 293-311, 2022. (SCI, Q2)
16. D Zang, X Chen, J Lei, Z Wang, J Zhang, J Cheng, K Tang*. A multi-channel geometric algebra residual network for traffic data prediction. IET Intell. Transp. Syst. 16, 1549– 1560, 2022. (SCI, Q3)
17. D Zang, Y Ding, X Qu, C Miao, X Chen, J Zhang, K Tang*. Traffic-Data Recovery Using Geometric-Algebra-Based Generative Adversarial Network. Sensors. 22(7):2744, 2022. (SCI, Q2)
18. C Tan, J Yao, X Ban, K Tang*. Cumulative Flow Diagram Estimation and Prediction Based on Sampled Vehicle Trajectories at Signalized Intersections, IEEE Transactions on Intelligent Transportation Systems, 2021. (SCI, Q1)
19. Cao, Y., Tang, K.*, Sun, J., Ji, Y. Day-to-day dynamic origin–destination flow estimation using connected vehicle trajectories and automatic vehicle identification data, Transportation Research Part C: Emerging Technologies, Vol. 129, 2021, 103241. (SCI, Q1)
20. Chen, C., Cao, Y., Tang, K.*, Li, K. Dynamic Path Flow Estimation Using Automatic Vehicle Identification and Probe Vehicle Trajectory Data: A 3D Convolutional Neural Network Model, Journal of Advanced Transportation, 2021. (SCI, Q3)
21. Yin, J., Chen, P., Tang, K.*, Sun, J. Queue Intensity Adaptive Signal Control for Isolated Intersection Based on Vehicle Trajectory Data, Journal of Advanced Transportation, 2021. (SCI, Q3)
22. Tang K., Cao Y., Chen C., Yao J., Tan C., Sun J. Dynamic Origin-Destination Flow Estimation Using Automatic Vehicle Identification Data: A 3D Convolutional Neural Network Approach. Computer-Aided Civil and Infrastructure Engineering, 2021, DOI: https://doi.org/10.1111/mice.12559. (SCI, Q1)
23. Tang, K.*, Chen, S., Cao, Y., Li, X., Zang, D. Sun, J., Ji, Y. Short-Term Travel Speed Prediction for Urban Expressways: Hybrid Convolutional Neural Network Models, IEEE Transactions on Intelligent Transportation Systems, 2020. (SCI, Q1)
24. Tang, K.*, Tan, C., Cao, Y., Yao, J., Sun, J. A tensor decomposition method for cycle-based traffic volume estimation using sampled vehicle trajectories, Transportation Research Part C: Emerging Technologies, Vol.118, Article ID: 102739, DOI: https://doi.org/10.1016/j.trc.2020.102739, 2020. (SCI, Q1)
25. Tan, C., Liu, L., Wu, H., Cao, Y. and Tang, K.* Fuzing License Plate Recognition Data and Vehicle Trajectory Data for Lane-Based Queue Length Estimation at Signalized Intersections. Journal of Intelligent Transportation Systems, Vol.24, No.5, pp.449-466, DOI: 10.1080/15472450.2020.1732217, 2020. (SCI, Q2)
26. Tan, C., Yao, J., Tang, K.* and Sun, J. Cycle-based Queue Length Estimation for Signalized Intersections Using Sparse Vehicle Trajectory Data. IEEE Transactions on Intelligent Transportation Systems, Vol.22, No.1, pp.91-106, DOI:10.1109/TITS.2019.2954937, 2019. (SCI, Q1)
27. Yao, J., Li, F., Sun, J. and Tang, K.* Sampled Trajectory Data-Driven Method of Cycle-Based Volume Estimation for Signalized Intersections by Hybridizing Shockwave Theory and Probability Distribution. IEEE Transactions on Intelligent Transportation Systems, Vol.21, No.6, pp.2615-2627, DOI: 10.1109/TITS.2019.2921478, 2019. (SCI, Q1)
28. Mei, Y., Gu, W., Chung, E., Li, F., and Tang, K.* A Bayesian approach for estimating vehicle queue lengths at signalized intersections using probe vehicle data. Transportation Research Part C, Vol.109, pp.233-249, 2019. (SCI, Q1)
29. Yao, J., Tan, C. and Tang, K.* An Optimization Model for Arterial Coordination Control Based on Sampled Vehicle Trajectories: The STREAM Model. Transportation Research Part C, Vol.109, pp.211-232, 2019. (SCI, Q1)
30. Yao, J. and Tang, K.* Cycle-based queue length estimation considering spillover conditions based on low resolution point detector data. Transportation Research Part C, Vol.109, pp.1-18, 2019. (SCI, Q1)
31. Wang, F., Tang, K.*, Li, K., Liu, Z., Zhu, L. A Group-Based Signal Timing Optimization Model Considering Safety for Signalized Intersections with Mixed Traffic Flows, Journal of Advanced Transportation, Vol. 2019, Article ID 2747569, DOI：https://doi.org/10.1155/2019/2747569, 2019. (SCI, Q3)
32. Zang, D., Fang, Y., Wei, Z., Tang, K.*, Cheng, J. Traffic Flow Data Prediction Using Residual Deconvolution Based Deep Generative Network, IEEE Access, Vol.7, pp.71311-71322, 2019. (SCI, Q2)
33. Zang, D., Lin J., Wei, Z., Tang, K.*, Chen, J. Long-Term Traffic Speed Prediction Based on Multiscale Spatio-Temporal Feature Learning Network. IEEE Transactions on Intelligent Transportation Systems, Vol.20, No.10, pp.3700-3709, 2018. (SCI, Q1)
34. Zang, D., Wei, Z., Bao, M., Cheng, J., Zhang, D., Tang, K.*, Li. Deep Learning-based Traffic Sign Recognition for Unmanned Autonomous Vehicles. Journal of Systems and Control Engineering, Vol.232, No.5, pp.497-505, 2018. (SCI, Q3)
35. Wei, Y., Li, K., Tang, K.*. Trajectory-based identification of critical instantaneous decision events at mixed-flow signalized intersections, Accident Analysis and Prevention, Vol.123, pp.324-335, 2018. (SSCI, Q1)
36. Tan, C., Zhou, N., Tang, K.* & Ji, Y.* Real-Time Prediction of Vehicle Trajectories for Proactively Identifying Risky Driving Behaviors at High-Speed Intersections. Transportation Research Record, Vol.2672, No.38, pp.233-244, 2018. (SCI, Q4)
37. Yin, J., Sun, J.* & Tang, K.* A Kalman Filter Based Queue Length Estimation with Low-Penetration Mobile Sensor Data at Signalized Intersections. Transportation Research Record, Vol.2672, No.45, pp.253-264, 2018. (SCI, Q4)
38. Li, F., Tang, K.*, Yao, J. & Li, K. Real-Time Queue Length Estimation for Signalized Intersections Using Vehicle Trajectory Data. Transportation Research Record, Vol.2623, No.1, pp.49-59, 2017. (SCI, Q4)
39. Tang, K.*, Wang, F., Yao, J. & Sun, J.* Empirical Analysis and Modeling of Stop-Line Crossing Time and Speed at Signalized Intersections. International Journal of Environmental Research and Public Health, Vol.14, No.1, Article ID: 9, DOI: 10.3390/ijerph14010009, 2017. (SCI, Q2)
40. Tang. K.*, Dong, K. & Edward, C. Queue Discharge Patterns at Signalized Intersections with Flashing Green Signals and Long Cycle Length. Journal of Advanced Transportation, Vol. 50, No. 8, pp. 2100-2115, 2016. (SCI, Q3)
41. Wang, F., Tang, K.*, Xu, Y., Sun, J. & Li, K. Modeling Risky Driver Behavior Under the Influence of Flashing Green Signal with Vehicle Trajectory Data, Transportation Research Record, Vol. 2562, No.1, pp.53-62, 2016. (SCI, Q4)
42. Tang, K.*, Zhu, S., Xu, Y. & Wang, F. Modeling Drivers’ Dynamic Decision-Making Behavior during the Phase Transition Period: An Analytical Approach Based on Hidden Markov Model Theory, IEEE Transactions on Intelligent Transportation Systems, Vol. 17, No.1, pp.206-214, 2016. (SCI, Q1)
43. Tang, K.*, Xu, Y., Wang, F. & Oguchi, T. Exploring Stop-Go Decision Zones at Rural High-Speed Intersections with Flashing Green Signal and Insufficient Yellow Time in China, Accident Analysis & Prevention, Vol. 95, pp. 470-478, 2016. (SSCI, Q1)
44. Dong, S., Zhou, J., Zhao, L., Tang, K.* & Yang, R. Feasibility analysis of phase transition signals based on e-bike rider behavior, Advances in Mechanical Engineering, Vol.7, No.11, DOI: 10.1177/1687814015618905, 2015. (SCI, Q4)
45. Tang, K.*, Di, D. & Li, K. Risk-Taking Behavior of Left-Turners in Gap Acceptance and Its Effects on Capacity Estimation at Signalized Intersections, Transportation Research Record, No. 2483, pp. 1-9, 2015. (SCI, Q4)
46. Mei, Y., Tang, K.* & Li, K. Real-time Identification of Probe Vehicle Trajectories in the Mixed Traffic Corridor. Transportation Research Part C, Vol. 57, pp. 55-67, 2015. (SCI, Q1)
47. Tang, K.*, Xu, Y., Wang, P. & Wang, F. Impacts of Flashing Green on Dilemma Zone Behavior at High-Speed Intersections: Empirical Study in China, Journal of Transportation Engineering, Vol.141, No.7, Article ID :04015005, DOI: http://dx.doi.org/10.1061/(ASCE)TE.1943-5436.0000770, 2015. (SCI, Q3)
48. Wang, F, Tang, K.* & Li, K. Stochastic Effects of Traffic Randomness on the Determination of Signal Change and Clearance Intervals at Signalised Intersections. IET Intelligent Transport Systems, Vol. 9, No. 3, pp. 250-263, 2015. (SCI, Q3)
49. Wang, F, Tang, K.* & Li, K. A Stochastic Computational Model for Yellow Time Determination and Its Application. Journal of Advanced Transportation, Vol. 49, No.3, pp. 457-474, 2015. (SCI, Q3)
< 国内期刊 >
50. 骆旅舟, 谈超鹏, 唐克双*.基于电警数据的单点自适应信号控制优化方法[J].同济大学学报(自然科学版),2022,50(12):1798~1808.（EI）
51. 姚佳蓉, 曹喻旻, 唐克双*. 基于抽样轨迹数据和改进最小二乘模型的信控路网路径流量估计方法[J]. 中国公路学报, 2022, 35(3):14.（EI）
52. 谈超鹏，姚佳蓉，曹喻旻，唐克双*. 基于网联车辆轨迹数据的周期排队长度估计，中国公路学报，Vol. 34, No.7, pp.140-151, 2021.（EI）
53. 唐克双*, 陈思曲, 曹喻旻, 张锋鑫. 基于Inception卷积神经网络的城市快速路行程速度短时预测, 同济大学学报, Vol. 49, No.3, pp.370-381, 2021.（EI）
54. 谈超鹏，姚佳蓉，唐克双*. 基于抽样车辆轨迹数据的信号控制交叉口排队长度分布估计,中国公路学报，http://kns.cnki.net/kcms/detail/61.1313.u.20201125.1530.004.html，2020（EI）.
55. 衣谢博闻，唐克双*，李克平. 基于信息熵的城市道路可变信息板布点方法，同济大学学报，Vol. 47, No. 8, pp.1148-1155, 2019. (EI)
56. 唐克双*，谈超鹏，周楠. 基于轨迹数据的交叉口相位切换期间危险驾驶行为实证分析，中国公路学报，Vol. 31，No. 4, pp.88-97, 2018. (EI)
57. 项俊平，唐克双*，陶晶晶. 周期与流量对交叉口排放和延误的影响, 同济大学学报, Vol. 45, No. 11, pp.1629-1639, 2017. (EI)
58. 唐克双*，杨博文，许凯，孙梓栗，周楠. 基于车辆轨迹数据的交叉口危险驾驶行为预测，同济大学学报, Vol. 45, No. 10, pp.1454-1461, 2017. (EI)
59. 唐克双*，徐天祥，董可然，李克平. 基于低频定点检测数据的交叉口交通状态估计, 同济大学学报, Vol. 45, No. 5, pp. 705-713, 2017. (EI)
60. 唐克双*，郝兆康，衣谢博闻，刘冰清. 停车场泊位占有率预测方法评价, 同济大学学报（自然科学版）, Vol. 45, No. 4, pp. 533-543, 2017. (EI)
61. 王鹏飞, 唐克双*. 出行者随机到达条件下的最优外生通行权发行方式，中国公路学报，Vol. 29, No. 10, pp.126-131, 2016. (EI)
62. 唐克双*，徐天祥，潘昂，李诗琪. 基于定点检测数据的城市干道车辆轨迹重构, 同济大学学报,Vol. 44, No. 10, pp. 1545-1552, 2016. (EI)
63. 唐克双*，周楠，狄德仕，李克平. 基于风险收益平衡的驾驶员停止通过决策行为研究, 同济大学学报, Vol. 44, No. 11, pp. 1687-1694, 2016. (EI)
64. 唐克双*, 董可然, 黄志荣, 王奋. 信号交叉口排队消散特性实证对比. 同济大学学报, Vol. 43, No. 11, pp. 1689-1695, 2015. (EI)
