近5年代表性 SCI/EI 国内外论文如下：

   < SCI检索>  

1. Zang, D*., Ling, J., Wei, Z., Tang, K., Cheng, J. Long-Term Traffic Speed Prediction Based on Multiscale Spatio-Temporal Feature Learning Network. IEEE Transactions on Intelligent Transportation Systems, Vol.20, pp.3700-3709, 2019.

2. 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, 2019.

3. Wei, Y., Li, K., Tang, K*. Trajectory-Based Identification of Critical Instantaneous Decision Events at Mixed-Flow Signalized Intersections. Accident Analysis & Prevention, Vol.123, pp.324-335, 2019.

4.  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.

5. 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.

6. 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.

7. 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, 2019.

8. 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.

9. 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, 2019.

10. Wang, F*., Tang, K., Xu, Y., Li, K. Investigating Drivers’ Decision Zones at High-speed Intersections in China based on the Acceleration-Deceleration Diagram. Case Studies on Transport Policy, Vol.8(1), pp.112–118, 2020.

11. 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, pp.102739,2020.

12. 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, 2020.

13. 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, Vol. 23, No.3, pp.1829-1840 2020.  

14. 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.

15. 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, Vol.2021 ,2021.

16. 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, Vol.2021, 2021.

17. 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, 103241, 2021.

18. Tan, C., Yao, J., Ban, X., Tang, K*. 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.

19. Tang, K., Wu, H., Yao, J., Tan, C., Ji, Y*. Lane-Based Queue Length Estimation at Signalized Intersections Using Single-Section License Plate Recognition Data. Transportmetrica B: Transport Dynamics, Vol. 10, No.1, pp.293-311, 2022.

20. Chen, X., Yin, J., Tang, K., Tian, Y., Sun, J*. Vehicle Trajectory Reconstruction at Signalized Intersections Under Connected and Automated Vehicle Environment. IEEE Transactions on Intelligent Transportation Systems, Vol.23, No.10, pp.17986-18000 ,2022.

21. Chen, X., Yin, J., Qin, G., Tang, K., Wang, Y., Sun, J*. Integrated Macro-Micro Modelling for Individual Vehicle Trajectory Reconstruction Using Fixed and Mobile Sensor Data. Transportation Research Part C: Emerging Technologies, Vol. 145, pp. 103929 2022.

22. Zang, D., Chen, X., Lei, J., Wang, Z., Zhang, J., Cheng, J., Tang, K*. A Multi-Channel Geometric Algebra Residual Network for Traffic Data Prediction. IET Intelligent Transport Systems, Vol. 16, No.11, pp. 1549-1560, 2022.

23. Zang, D., Ding, Y., Qu, X., Miao, C., Chen, X., Zhang, J., Tang, K*. Traffic-Data Recovery Using Geometric-Algebra-Based Generative Adversarial Network. Sensors. 22(7):2744, 2022.

24. Tan, C., Wu, H., Tang, K.*, Tan, C. An Extendable Gaussian Mixture Model for Lane-Based Queue Length Estimation Based on License Plate Recognition Data. Journal of Advanced Transportation, Vol. 2022, pp. 1-14, 2022.

25. Yao, J., Wu, H., and Tang, K*.  A Bi-Level Programming Method for SPaT Estimation at Fixed-Time Controlled Intersections Using License Plate Recognition Data. Transportmetrica B: Transport Dynamics, Vol. 11, No.1, pp.1045-1070, 2023.

26. 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, Early Access, pp.1-18, 2023.

27. 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, Vol 18, No. 4, pp.709-722, 2023.

28. Tan, C., Cao, Y., Ban, X., and Tang, K*. Connected Vehicle Data-Driven Fixed-Time Traffic Signal Control Considering Cyclic Time-Dependent Vehicle Arrivals Based on Cumulative Flow Diagram. IEEE Transactions on Intelligent Transportation Systems, Early Access, pp.1-17, 2024.

29. Wu, H., Luo, L., Takashi OGUCHI, Tang, K*., Zhu H*. Stochastic Queue Profile Estimation using License Plate Recognition Data. Physica A: Statistical Mechanics and its Applications, Vol.643, pp.129790, 2024.

30. Wu, H., Yao, J., Cao, Y., Tang, K*. Left-Turn Queue Spillback Identification Based on Single-Section License Plate Recognition Data. Transportmetrica B: Transport Dynamics, Vol.12, pp.2363273, 2024

31. Zhu, H., Sun, F., Tang, K*., Han, T*., Xiang, J. A Coordination Graph Based Framework for Network Traffic Signal Control. IEEE Transactions on Intelligent Transportation Systems, Early Access, pp.1-15, 2024

32. Zhu, H., Sun, F*., Tang, K*., Wu, H., Feng, J., Tang, Z. Digital Twin-Enhanced Adaptive Traffic Signal Framework under Limited Synchronization Conditions. Sustainability, Vol. 16, No.13, 2024.

33. Zang, D*., Ding, Y., Zhao, J., Tang, K., Zhu, H. Predictive Resilience Assessment of Road Networks Based on Dynamic Multi-Granularity Graph Neural Network, Vol. 601, pp.128207, 2024.

    
    

  < EI检索>  

1. 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.

2. Bai, L., Wang, XH., Tang, K*. Effect of Drivers’ Attitude towards Traffic Safety Policy on Traffic Violation Behaviors. Transportation Research Record, Vol. 2672, No. 38, pp.233-244, 2018.

3. 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.

4. 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.

5. Suzuki, K.*, Tang, K., Alhajyaseen, W., Suzuki, K., Nakamura, H. An International Comparative Study on Driving Attitudes and Behaviors Based on Questionnaire Surveys. IATSS Research , Vol. 46, No.1, pp.26-35, 2022.

6. 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,Vol.34, No.11, pp.282-295,2020.

7. Tan, C., Shi, Y., Bai, L., Tang, K. *, Suzuki, K., Nakamura, H. Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behavior. IATSS Research, Vol. 46, No.1, pp.63-72,2022.

8. Zang, D., Ding, Y., Qu, X., Chen, X., Tang, K*., Zhang, J. Traffic Data Prediction with Geometric Algebra Spatial-Temporal Attention Neural Network. Proceedings of the 7th International Conference on Big Data and Computing, pp. 14-19, 2022.

9. Zhou, JJ.,Tang, K*., Tan, C. Precise Reconstruction of Shockwaves at Signalized Intersections by Fusing Multiple Data Sources. CICTP 2022, pp. 489-500.2022.

10. Zang, D., Qu, X., Ding, Y., Chen, Xi., Tang, K*., Zhang, J. Traffic Congestion Propagation Prediction Based on Multi-vector Deep Neural Networks. Proceedings of the 7th International Conference on Big Data and Computing, pp. 51-57, 2022.

11. Toriumi, A.*, Abu-Lebdeh, G., Alhajyaseen, W., Christie, N., Gehlert, T., Mehran, B., Mussone, L., Shawky, M., Tang, K., Nakamura, H. A Multi-Country Survey for Collecting and Analyzing Facts Related to Road Traffic Safety: Legislation, Enforcement, and Education for Safer Drivers. IATSS Research, Vol. 46, No.1, pp. 14-25, 2022.

12. 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. 中国公路学报, Vol. 35, No.3, pp.226-239,2022.

13. 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.同济大学学报(自然科学版).Vol. 50, No.12, pp.1798-1808,2022.

14. 伉沛喆, 张承志, 吴浩, 姚佳蓉, 曹喻旻, 唐克双*. 基于电警数据的干线自适应协调控制优化方法. 中国公路报. Vol. 36, No.10 , pp.251-268,2023.

15. 吴浩,刘磊,唐克双*. 基于集成学习的信号控制交叉口排队长度估计. 同济大学学报(自然科学版). Vol.51, No 03, pp.405-415.2023.