研究方向：智能交通系统优化、自动驾驶决策控制、驾驶行为分析
办公邮箱：2603332567@qq.com
个人简介：
汤茹茹，广东技术师范大学汽车与交通工程学院讲师。主要从事智能交通系统优化、自动驾驶决策控制、驾驶行为分析领域研究，发表SCI/EI论文10余篇。
教育背景：
2020年9月-2025年6月，澳门大学，土木工程（智能交通方向），博士学位
2017年9月-2019年6月，哈尔滨工业大学，交通信息与控制，硕士学位
2013年9月-2017年6月，郑州大学，交通工程，学士学位
代表性论文:
1. Z. Li,R. Tang, G. Li, and C. Xu, “Understanding social attitudes towards autonomous driving,” Transportation, 2024: 1-32.
2.R. Tang, Z. Li, and C. Xu, “An adaptive control framework for mixed autonomy traffic platoon,” Arabian Journal for Science and Engineering, 2024: 1-19.
3. Z. Li, H. Liao,R. Tang, G. Li, Y. Li, and C. Xu, “Mitigating the impact of outliers in traffic crash analysis: A robust bayesian regression approach with application to tunnel crash data,” Accident Analysis & Prevention, vol. 185, p. 107 019, 2023.
4. Y. Bie,R. Tang, Z. Liu, and D. Ma, “Mixed scheduling strategy for high frequency bus routes with common stops,” IEEE Access, vol. 8, pp. 34 442 – 34 454, 2020.
5. Y. Bie,R. Tang, and L. Wang, “Bus scheduling of overlapping routes with multi-vehicle types based on passenger od data,”IEEE Access, vol. 8, pp. 1406 – 1415, 2019.
6.别一鸣，汤茹茹，王运豪，文斌，冯天军，王琳虹,“信号交叉口进口车道饱和流率估计方法，”吉林大学学报（工学版），vol. 49（05），pp. 1459–1464,2019.
7.别一鸣，姜凯，汤茹茹，王琳虹，熊昕宇,“考虑方案过渡影响的单点交通控制时段划分方法，”吉林大学学报（工学版），vol. 49（06），pp. 1844–1851,2019.
8. W. Qi, Z. Wang,R. Tang, and L. Wang, “Driving risk detection model of deceleration zone in expressway based on generalized regression neural network,” Journal of Advanced Transportation, 2018.
9.R. Tangand Z. Li, “Driving risk field modeling based trajectory planning under mixed autonomy environment,”in Proceedings of the transportation research board 103rd annual meeting, Washington, DC: Transportation Research Board, 2024.
10.R. Tangand Z. Li, “A platoon stability control approach in mixed autonomy traffic environment,”in Proceedings of the transportation research board 103rd annual meeting, Washington, DC: Transportation Research Board, 2024.
11.R. Tang, H. Liao, Z. Li, C. Chen, Z. Pu, K. Zhang, W. Li, S. Li, and C. Xu, “Robust bayesian regression for outlier mitigation in traffic crash analysis,”in Proceedings of the transportation research board 103rdannual meeting, Washington, DC: Transportation Research Board, 2024.
12. H. Liao,R. Tang, X. Li, X. Wang, Z. Li, W. Li, K. Zhang, and C. Xu,“Mftraj: A map-free, efficient trajectory prediction model for autonomous driving,”in Proceedings of the transportation research board 103rdannual meeting, Washington, DC: Transportation Research Board, 2024.
13. Z. Li, H. Liao,R. Tang, G. Li, Y. Bie, and C. Xu, “An efficient bayesian robit model for traffic safety modeling,”in CICTP 2023, pp. 1592 – 1604.
14. H. Liao, C. Wang, H. Shen,R. Tang, Z. Li, and C. Xu, “Towards context-aware grounding command for autonomous driving: A cross-modal approach,”in CICTP 2024.
15. H. Liao, H. Kong, H. Shen, Z. Li,R. Tang, Z. Pu, S. Li, and C. Xu, “Achieving human-like trajectory prediction for autonomous vehicles: A behavior-aware approach,”in Proceedings of the transportation research board 103rd annual meeting, Washington, DC: Transportation Research Board, 2024.
16.R. Tang, Y. Wang, Y. Bie, and Z. Fang, “Estimation method of saturation flow rate for shared left-turn lane at the signalized intersection, part i: Methodology,”in Smart Transportation Systems 2019, Springer, 2019, pp. 39 – 47.
17.R. Tang, Y. Wang, Y. Bie, and Z. Fang, “Estimation method of saturation flow rate for shared left-turn lane at signalized intersection, part ii: Case study,”in Smart Transportation Systems 2019, Springer, 2019, pp. 49 – 56.
