English
教职工
曲小波

车辆与运载学院  教授、博士生导师

欧洲科学院(Academia Europaea)院士

地址:清华大学李兆基科技大楼A486

邮箱:xiaobo'at'tsinghua.edu.cn


个人主页

        曲小波,清华大学车辆与运载学院长聘教授、博士生导师,出生于山东省滨州市邹平市。于2021年12月起全职任教于清华大学车辆与运载学院,并入选国家海外高层次人才-长江学者讲席教授。归国之前任瑞典查尔莫斯理工大学讲席教授,在澳大利亚、瑞典任教10年。

        其致力于引入最新的控制、通讯、运筹决策等技术到未来城市交通系统中,针对出行瓶颈,提高交通系统的效率、安全、环保及公平性,并着重研究立体交通、空地协同物流及出行等方面。在上述领域发表期刊论文100余篇。在过去五年,曲教授主持欧盟、瑞典科技部、瑞典基金委、澳大利亚基金委、中国教育部等科研经费超过1000万欧元。受邀担任欧委会人才项目、澳洲基金委卓越科学中心(Centre of Excellence)、荷兰基金委重大项目(VICI)、香港研究理事会主题项目(Theme Based Scheme)、新加坡主题项目(Thematic Research Grant)、国内人才等重大项目的初评或终评专家。

        现任Communications in Transportation Research主编,Transportation Research Part A, Part E、Cell综合性期刊The Innovation、IEEE Trans on Cybernetics, ASCE Journal of Transportation Engineering, IEEE ITSM等期刊编委,以及世界交通大会协会交通建模委员会主席。曾荣获新加坡交通部部长创新奖、澳大利亚教育部奋进长江研究奖等。培养博士生、博士后三十余人,均就职于中国、澳洲、欧洲的高校、交通部/厅、及知名互联网及车厂。2020年8月,入选欧洲科学院(Academia Europaea-The Academy of Europe)。


Xiaobo Qu is a Changjiang Chair Professor with the School of Vehicle and Mobility, Tsinghua University since Dec 2021. His research is focused on intelligent transportation systems, ground-air cooperation and vertical transportation systems, and emerging transport mode informed mobility services. He has authored or co-authored over 130 journal articles published at top tier journals, including 14 ESI highly cited papers. To date, Prof Qu has secured research funding well above 10 million Euros from the Australian Research Council, Swedish Innovation Agency Vinnova, STINT, and European Union, Ministry of Education China, including one Australian Research Council Discovery Project, four major grants from Swedish Innovation Agency, two projects from EU, and a number of projects from research foundations. He has been invited to serve as a panel/assessor for prestigious funding scheme such as the Australian Research Council Centre of Excellence (35 million AUD each), Future Fellowship (career grant, 1 million AUD each), Netherlands NWO VICI (career grant, 2.5 million Euros each), Hong Kong Research Council theme based scheme (30 million HKD each), Singapore Ministry of Education Thematic Research Program (5 million SD each), European Research Council, NSFC, Ministry of Education China etc. He is an elected Member of Academia Europaea–the Academy of Europe since Aug 2020, and an elected Fellow of the European Academy of Sciences since Jan 2020.  He was a faculty member at two Australian Universities from 2012-2017, joined Chalmers University of Technology, Sweden, as a Professor in Feb 2018, promoted to Chair Professor rank in Feb 2020. From Dec 2021, Xiaobo is teaching at the School of Vehicle and Mobility, Tsinghua University, China, at full time capacity, and will accept PhD students and postdocs from both China and overseas. 


2019-2020  瑞典查尔莫斯理工大学  高等教育研究生文凭

2009-2012  新加坡国立大学  博士

2006-2009  清华大学  工学硕士

2001-2005  吉林大学  工学学士

2021.12 - :           清华大学车辆与运载学院  教授

2020.03-2021.12:瑞典查尔莫斯理工大学  讲席教授

2018.03-2020.02:瑞典查尔莫斯理工大学  教授

2016.07-2018.02:澳大利亚悉尼科技大学  高级讲师

2012.02-2016.06:澳大利亚格里菲斯大学  讲师、高级讲师

智能交通系统;地空协同物流与出行;立体交通系统;未来公交系统;车城互联系统

讲授课程

1. 智能交通系统

2. 网联环境下的交通控制

3. 未来交通运载模式


研究生培养

已毕业博士:9人

在读博士:5人

主编:Communications in Transportation Research

执行主编:Journal of Intelligent and Connected Vehicles 

编委:The Innovation (A flagship journal under the cell group)、Transportation Research Part A/Part EComputer-Aided Civil and Infrastructure Engineering
副编/领域编辑:ASCE Journal of Transportation Engineering、ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems、IEEE Transactions on Cybernetics、IEEE ITS Magazine、Transportmetrica B、Journal of Intelligent and Connected Vehicles

最佳论文评选委员会主席:ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems

新加坡交通部部长创新奖-2010

格里菲斯大学校级优秀教学奖-2015

格里菲斯大学学部优秀教学奖-2014

澳大利亚教育部奋进长江研究奖-2016

欧洲科学院(Academia Europaea)院士-2020

长江学者讲席教授-2021



Selected 20 publications

1. Basso, R., Kulcsar, B., Sanchez-Diaz, I., Qu, X., 2022. Dynamic Stochastic Electric Vehicle Routing with Safe Reinforcement Learning. Transportation Research Part E, 157, 102496. 

2. Chen Z, Li X, and Qu X., 2022. A continuous model for designing corridor systems with modular autonomous vehicles enabling station-wise docking. Transportation Science, 56(1), 1-30. 

3. Wu J, Kulcsár B, Selpi, Qu X., 2021. A Modular, Adaptive, and Autonomous Transit System (MAATS): A In-motion Transfer Strategy and Performance Evaluation in Urban Grid Transit Networks. Transportation Research Part A: Policy and Practice, 151, 81-98.

4. Zhang L, Wang S, and Qu X, 2020. Optimal electric bus fleet scheduling considering battery degradation and non-linear charging profile. Transportation Research Part E: Transportation and Logistics Review, 154, 102445, (also part of ISTTT2022 - acceptance rate: 10%).

5. Zhang J, Tang T, Yan Y, Qu X., 2021. Eco-driving control for connected and automated electric vehicles at signalized intersections with wireless charging. Applied Energy, 282, 116215. 

6. Wu J, Ahn S, Zhou Y, Liu P, Qu X., 2021. The cooperative sorting strategy for connected and automated vehicle platoons. Transportation Research Part C: Emerging Technologies, 123, 102986.

7. Wang T, Tang TQ, Huang HJ, Qu X., 2021. The adverse impact of electric vehicles on traffic congestion in the morning commute. Transportation Research Part C: Emerging Technologies, 125, 103073. 

8. Zhou M, Yu Y, Qu X., 2020. Development of an Efficient Driving Strategy for Connected and Automated Vehicles at Signalized Intersections: A Reinforcement Learning Approach. IEEE Transactions on Intelligent Transportation Systems, 21(1): 433-443. 

9. Wu J, Kulcsár B, Ahn S, Qu X., 2020. Emergency vehicle lane pre-clearing: From microscopic cooperation to routing decision making. Transportation Research Part B: Methodological, 141: 223-239.

10. Varga B, Tettamanti T, Kulcsár B, Qu X., 2020. Public transport trajectory planning with probabilistic guarantees. Transportation Research Part B: Methodological, 139: 81-101.

11. Qu X, Yu Y, Zhou M, Lin C, Wang X., 2020. Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach. Applied Energy, 257, 114030.

12. Wang S, Yan R, Qu X., 2019. Development of a non-parametric classifier: Effective identification, algorithm, and applications in port state control for maritime transportation. Transportation Research Part B: Methodological, 128: 129-157, (Impact Factor: 4.796).

13. Li X, Medal H, Qu X., 2019. Connected infrastructure location design under additive service utilities. Transportation Research Part B: Methodological, 120: 99-124.

14. Wang S, Zhang W, Qu X., 2018. Trial-and-error train fare design scheme for addressing boarding/alighting congestion at CBD stations. Transportation Research Part B: Methodological, 118: 318-335.

15. Li X, Ghiasi A, Xu Z, Qu X., 2018. A piecewise trajectory optimization model for connected automated vehicles: Exact optimization algorithm and queue propagation analysis. Transportation Research Part B: Methodological, 118: 429-456.

16. Zhou M, Qu X, Li X., 2017. A recurrent neural network based microscopic car following model to predict traffic oscillation. Transportation Research Part C: Emerging Technologies, 84: 245-264.

17. Zhou M, Qu X, Jin S., 2017. On the Impact of Cooperative Autonomous Vehicles in Improving Freeway Merging: A Modified Intelligent Driver Model-Based Approach. IEEE Transactions on Intelligent Transportation Systems, 18(6): 1422-1428.

18. Wang K, Wang S, Zhen L, Qu X., 2017. Cruise service planning considering berth availability and decreasing marginal profit. Transportation Research Part B: Methodological, 95: 1-18, (Impact Factor: 4.796).

19. Qu X, Zhang J, Wang S., 2017. On the stochastic fundamental diagram for freeway traffic: Model development, analytical properties, validation, and extensive applications. Transportation Research Part B: Methodological, 104: 256-271. 

20. Qu X, Wang S, Zhang J., 2015. On the fundamental diagram for freeway traffic: A novel calibration approach for single-regime models. Transportation Research Part B: Methodological, 71: 91-102.