近5年国内外会议论文如下：

   < 国际会议 >   

1. L Bai, X Wang, K Tang*. Effect of Driver’s Attitude towards Traffic Safety Policy on Traffic Violation Behaviors. CICTP, pp.4180-4190, 2020.

2. B Liu, X Yi, K Tang*. Impacts of guidance information and disseminating strategies on parking choice behavior in commercial districts. Transportation Research Board 98th Annual Meeting Transportation Research Board, Washington D.C., 2019.

3. H Wu, J Yao, L Liu, Y Cao, K Tang*. Left-Turn Spillback Identification Based on License Plate Recognition Data. Transportation Research Board 98th Annual Meeting Transportation Research Board, Washington D.C., 2019.

4. D Zang*, Y Fang, D Wang, Z Wei, K Tang, X Li. Long Term Traffic Flow Prediction Using Residual Net and Deconvolutional Neural Network. Pattern Recognition and Computer Vision: First Chinese Conference (PRCV), pp.62-74, 2018.

5. K Dong, J Gu, Z Zeng, K Tang*. Modeling Operational Reliability of Urban Arterials Considering Congestion Correlations. CICTP: Intelligence, Connectivity, and Mobility, pp.1523-1535, 2018.

6. Yao, J., Li, F. & Tang, K.* Hybrid Cycle-based Volume Estimation Method for Signalized Intersections Based on Sampled Trajectory Data. Presented at the 97th Transportation Research Board Annual Meeting, Washington D.C., 2018.

7. Yao, J. & Tang, K.* Queue Length Estimation Considering Spillover Conditions Based on Low-Resolution Point Detector Data. Presented at the 97th Transportation Research Board Annual Meeting, Washington D.C., 2018.

8. Zang, D.*,Wang, D., Cheng, J., Tang, K., and Li,X. Traffic parameters prediction using a three-channel convolutional neural network, Proceedings of the 12 International Conference on Intelligence Science, 2017. (EI)

9. Zang, D.*, Ling, J., Cheng, J., Tang, K., and Li, X. Using convolutional neural network with asymmetrical kernels to predict speed of elevated highway, Proceedings of the 12 International Conference on Intelligence Science, 2017. (EI)

10. Zang, D.*, Ding, J., Cheng, J., Zhang, D. and Tang, K. A hybrid learning algorithm for the optimization of convolutional neural network, Proceedings of the 13th International Conference on Intelligent Computing, 2017. (EI)

11. Li, F., Tang, K.* & Li, K. Cycle-by-Cycle Estimation of Signal Timing and Queue Length at Signalized Intersections Based on Probe Data, Proceedings of the 96th Transportation Research Board Annual Meeting, Washington D.C., 2017.

12. Zang, D.*, Bao, M., Zhang, J., Cheng, J., Zhang, D., & Tang, K. Traffic Sign Detection Based On Cascaded Convolutional Neural Networks, The 17thIEEE/ACIS International Conference on Software Engineering Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), IEEE, Shanghai, 2016. (SCI)

13. Tang, K.*, Zhu, S., Xu, Y. & Wang, F. Empirical Analysis and Modeling of Stop-line Crossing Behavior during the Phase Transition Period at Signalized Intersections in China, Proceedings of the 95thTransportation Research Board Annual Meeting, Washington D.C., 2016.

14. Tang, K.* & Nakamura, H. Uncertainty Analysis of Safety Performance of the Permissive Right-turn Phase at Signalized Intersections, Proceedings of the 95th Transportation Research Board Annual Meeting, Washington D.C., 2016.

15. Wang, F., Tang, K.*, Xu, Y. & Li, K. Impacts of Flashing Green Signals on Risky Behaviour at Rural High-speed Intersections in China, Proceedings of the95th Transportation Research Board Annual Meeting, Washington D.C., 2016.

16. Wang, F., Tang, K.*, Xu, Y. & Li, K. Investigating Drivers’ Decision Zones at High-speed Intersections in China based on the Acceleration-Deceleration Diagram, Proceedings of the 14thWorld Conference on Transport Research, Shanghai, 2016.

17. Tang, K.*, Xu, Y. & Wang, F. Dilemma Zone Occurrences at the Rural High-Speed Intersections with Flashing Green and Insufficient Yellow Time in China. Proceedings of the 94th Transportation Research Board Annual Meeting, Washington D.C., 2015.

18. Tang, K.*, Zhu, S, Xu, Y. & Wang, F. Analytical Modeling of Dynamic Decision-Making Behavior of Drivers during the Phase Transition Period Based on a Hidden Markov Model. Proceedings of the 94thTransportation Research Board Annual Meeting, Washington D.C., 2015.  

19. Tang, K.* & Dong, K. Queue Discharge Patterns at Signalized Intersections with Green Signal Countdown Devices and Long Cycle Lengths. Proceedings of the 94th Transportation Research Board Annual Meeting, Washington D.C., 2015.

20. Yixie, B., Tang, K.* & Li, K. A Generalized Assessment Model for the Amount of Information of Variable Message Signs. Proceedings of CICTP 2015, Beijing, 2015. (EI)

21. Wang, F., Tang, K.* & Li, K. Probabilistic Evaluation of Traffic Randomness Effects on Intergreen Time Design based on a Safety Reliability Model. Proceedings of the 93th Transportation Research Board Annual Meeting, Washington D.C., 2014.  

22. Wang, F., Tang, K.*, Mei, Y., Kong, T. & Li,K. A Multi-Objective Group Based Signal Control Optimization Model for Mixed Traffic Flows at Isolated Intersections.Proceedings of the 93th Transportation Research Board Annual Meeting, Washington D.C., 2014.  

23. Kong, T., Lin, L. & Tang, K.* A New Dilemma Zone Protection Algorithm based on Real-Time Vehicle Trajectory. Proceedings of the 93th Transportation Research Board Annual Meeting, Washington D.C., 2014.

24. Di, D., Tang, K.* & Li, K. Modeling Driver’s Tradeoff between Time Benefit and Traffic Conflict Risk in Gap Acceptance at Signalized Intersections in China. Proceedings of CICTP 2014, Changsha, 2014.(EI)

   < 国内会议 >   

25. 陈思曲，李效松，唐克双*. 基于深度卷积神经网络的行程速度短时预测. 第十四届中国智能交通年会论文集，2019.

26. 刘家豪，姚佳蓉，唐克双*. 车辆轨迹融合电警数据的干道路径流量估计. 第十四届中国智能交通年会论文集，2019.

27. 吴浩，唐克双*. 基于电警数据的交叉口短车道排队溢出识别. 第十三届中国智能交通年会大会论文集, pp.544-554, 2018.

28. 曹喻旻，唐克双*. 基于车辆轨迹与定点检测数据的路网OD 估计. 共享与品质——2018 中国城市规划年会论文集 (06 城市交通规划)

29. 李福梁，姚佳蓉，朱金清，唐克双*. 稀疏车辆轨迹条件下信号控制交叉口排队长度估计方法. 第十二届中国智能交通年会优秀论文集, 2017.（年度优秀论文）

30. 唐克双*，孙剑，李克平，林航飞，刘涛，徐谨. 上海市五角场地区停车、行车诱导系统规划与设计. 第八届中国智能交通年会优秀论文集,pp.203-215, 2013.（年度优秀论文）