吴建平

职称:教授、博士生导师、清华大学-剑桥大学-麻省理工学院未来交通研究中心主任

通信地址:北京市海淀区清华大学土木系

邮编:100084

电话:010-62797229

传真:010-62797229

Email: jianpingwu@tsinghua.edu.cn

教育背景

1978.2 - 1982.1 浙江大学 土木工程系(水利水电专业) 工学学士
1982.2 - 1984.7 浙江大学 土木工程系(岩土工程专业) 工学硕士
1990.1 - 1994.1 英国南安普顿大学 土木与环境学院(交通工程专业)工学博士

工作履历

2013.11至今          清华大学-剑桥大学-麻省理工学院未来交通研究中心主任

2011.1-至今           清华大学教授

2007.10-2010.12   英国南安普敦大学教授、英国WSP国际集团高级董事

2006.10-2007.9     英国南安普敦大学教授、中英智能交通中心主任

2000.8-2006.9       中国教育部“长江学者”奖励计划特聘教授

1999.10-2000.7     英国南安普敦大学土木环境学院高级研究员

1994.1-1999.9       英国南安普敦大学土木环境学院研究员

1986.8-1989.12     浙江大学土木工程系讲师

1984.8-1986.7       浙江大学土木工程系助教

开设课程
  1. C-Campus“未来交通”(课程号:00030272)

  2. 交通分析与设计(课程号:40030942)

研究领域
  1. 交通行为、交通模型与交通仿真

  2. 大数据、智慧城市与智慧交通

  3. 无人驾驶与未来交通系统

科研项目
  1. 国家863课题 “基于物联网的城市空气环境调控技术研究及应用”(项目编号:2012AA063300),2012-2014

  2. 国家科技支撑子课题 “市政公用设施运行安全监测预警共性技术标准研究” (课题任务编号:2012BAK27B01-02),2012-2014

  3. 北京市科委自然科学基金面上项目 “北京市暴雨灾害交通预警、监测和疏导技术研究”,2013-2015

  4. 国家科技计划技术标准、认证认可备选项目 “公共管理与社会服务技术标准研究”“突发事件应急管理重要技术标准研究”,2013-2015

  5. 国际合作项目 “基于GPS数据的机动车能耗影响因素分析”,2013-2015

  6. 北京市朝阳区科委社会发展计划项目 “基于仿真的共享停车与动态交通组织系统研究”,2017-2018

  7. 国家自然科学基金-浙江两化融合联合基金项目 “智慧城市水务系统安全运行的检测与控制基础理论和方法”, 2016-2019

  8. 国家自然科学基金-浙江两化融合联合基金项目 “韧性视角下智慧城市基础设施系统安全与防护基础理论与关键技术”,2018-2021

  9. 中国科协调研课题 “智慧城市与智能交通领域前沿跟踪研究”,2018-2020

  10. NIHR 全球道路安全研究项目,英国国家健康研究委员会,2018-2020

  11. 未来社会出行模式研究,国际合作项目,2019-2021

  12. 未来交通仿真研究,IHI Coorpration,2019-2021

学术兼职
  1. 英国工程技术学会会士(FIET)

  2. 国际智能交通效益评估委员会 (IBEC ITS) 常务理事

  3. 联合国世界工程组织(WFEO)工程环境委员会委员

  4. 中国仿真学会交通建模与仿真专业委员会主任

  5. 中国仿真学会常务理事

  6. 中国城市研究会常务理事

  7. 中国交通部智慧机场专家委员会委员

  8. 中国科学技术协会海智计划专家

  9. 中国建设部城市公共交通顾问

  10. 浙江省大湾区院士专家委员会委员

  11. 北京、杭州、南宁、海口等城市顾问

  12. 2008北京奥运会组织委员会交通咨询专家

  13. IET ITS杂志副主编 (SCI检索)

奖励与荣誉

2020 福建省科学技术进步奖二等奖,排名第一

2018 北京市科学技术奖三等奖,排名第一

2017 中国仿真学会自然科学一等奖,排名第一

2016 日内瓦国际发明博览会金奖,排名第一

2016 中国仿真学会技术发明二等奖,排名第一

2015 第九届北京市发明创新大赛金奖,排名第一

2014 英国工程技术学会 会士(FIET)

2014 北京市科技进步奖三等奖,排名第一

2014 中国科协优秀仿真科技工作者

2013 中国产学研合作创新成果奖,排名第一

2013 中国智能交通协会科学技术奖,排名第一

2011 南宁市科学技术进步二等奖,排名第一

2011 河南省交通运输科学技术奖,排名第一

2000 教育部智能交通系统“长江学者”奖励计划特聘教授

学术成果

发明专利

  1. (2012) 道路网关键节点诊断技术

  2. (2012) 一种基于模糊数学的车辆跟驰模拟方法

  3. (2013) 基于交通仿真的信号控制系统及方法

  4. (2013) 动态交通仿真平台及其仿真方法

  5. (2013) 智能交通眼镜及基于该眼镜的工作方法

  6. (2014) 一种区域交通动态调控方法及系统

  7. (2016) 一种在线交通仿真方法及系统

  8. (2016) 一种交叉口信号动态调整方法及装置、系统

  9. (2019) 一种无人驾驶汽车性能的测试方法

  10. (2020) 一种供水管网漏损的自动识别和定位方法


著作

  1. Joseph Sussman 著,吴建平 译 《运输系统导论》,五南出版社,ISBN 957-11-3694,2004

  2. 隋亚刚,郭敏,吴建平 编著 《道路交通组织优化与仿真评价理论与方法》,人民交通出版社,ISBN 978-7-114-07661-9,2009

  3. 郭敏,杜怡曼,吴建平 编著 《微观交通仿真基础理论及应用实例》,人民交通出版社, ISBN 978-7-114-08917-8,2012

  4. 黄玲,吴建平 著 《自行车交通微观行为研究》,人民交通出版社, ISBN: 9787114141133,2017

  5. 吴建平,方东平 著 《第14章, CPS在智能城市中的作用》,建筑环境中的网络物理系统,施普林格出版,总编辑:C。J. Anumba 和 N. Roofigari


近期主要SCI论文

  1.  Zhu, C., Wu, J., Liu, M., Luan, J., Li, T., & Hu, K. (2020). Cyber-physical resilience modelling and assessment of urban roadway system interrupted by rainfall. Reliability Engineering & System Safety, 204, 107095.

  2. Li, T., Wu, J., Chan, C. Y., Liu, M., Zhu, C., Lu, W., & Hu, K. (2020). A Cooperative Lane Change Model for Connected and Automated Vehicles. IEEE Access, 8, 54940-54951.

  3. Li, D., Wu, J., Xu, M., Wang, Z., & Hu, K. (2020). Adaptive Traffic Signal Control Model on Intersections Based on Deep Reinforcement Learning. Journal of Advanced Transportation, 2020.

  4. Luo, L., Wu, J., Hu, H., Chen, Y., & Xu, Z. (2020). Analysis and forecast of water supply and demand in beijing through system dynamics modeling. Urban Water Journal, 1-13.

  5. Xu, M., Wu, J., Huang, L., Zhou, R., Wang, T., & Hu, D. (2020). Network-wide traffic signal control based on the discovery of critical nodes and deep reinforcement learning. Journal of Intelligent Transportation Systems, 24(1), 1-10.

  6. McIlroy, R. C., Kokwaro, G. O., Wu, J., Jikyong, U., Nam, V. H., Hoque, M. S., ... & Stanton, N. A. (2020). How do fatalistic beliefs affect the attitudes and pedestrian behaviours of road users in different countries? A cross-cultural study. Accident Analysis & Prevention, 139, 105491.

  7. McIlroy, R. C., Nam, V. H., Bunyasi, B. W., Jikyong, U., Kokwaro, G. O., Wu, J., ... & Stanton, N. A. (2020). Exploring the relationships between pedestrian behaviours and traffic safety attitudes in six countries. Transportation research part F: traffic psychology and behaviour, 68, 257-271.

  8. Huang, L., Zhai, C., Wang, H., Zhang, R., Qiu, Z., & Wu, J. (2020). Cooperative Adaptive Cruise Control and exhaust emission evaluation under heterogeneous connected vehicle network environment in urban city. Journal of Environmental Management, 256, 109975.

  9. Huang, L., Guo, H., Zhang, R., Zhao, D., & Wu, J. (2020). A data-driven operational integrated driving behavioral model on highways. Neural Computing and Applications, 1-17.

  10. Huang, L., Wu, J., Zhang, R., Zhao, D., & Wang, Y. (2020). Comparative analysis & modelling for riders’ conflict avoidance behavior of E-bikes and bicycles at un-signalized intersections.

  11. Luo, L., Feng, M. Q., & Wu, J. (2020). A comprehensive alleviation technique for optical‐turbulence‐induced errors in vision‐based displacement measurement. Structural Control and Health Monitoring, 27(3), e2496.

  12. Li, T., Wu, J., Dang, A., Liao, L., & Xu, M. (2019). Emission pattern mining based on taxi trajectory data in Beijing. Journal of Cleaner Production, 206, 688-700.

  13. Xu, M., Wu, J., Wang, H., & Cao, M. (2019). Anomaly detection in road networks using sliding-window tensor factorization. IEEE Transactions on Intelligent Transportation Systems, 20(12), 4704-4713.

  14. Yang, S., Wu, J., Xu, Y., & Yang, T. (2019). Revealing heterogeneous spatiotemporal traffic flow patterns of urban road network via tensor decomposition-based clustering approach. Physica A: Statistical Mechanics and its Applications, 526, 120688.

  15. Luo, L., Feng, M. Q., Wu, J., & Leung, R. Y. (2019). Autonomous pothole detection using deep region-based convolutional neural network with cloud computing. Smart Structures and Systems, 24(6), 745-757.

  16. Huang, L., Guo, H., Zhang, R., Wang, H., & Wu, J. (2018). Capturing drivers’ lane changing behaviors on operational level by data driven methods. IEEE Access, 6, 57497-57506.

  17. McIlroy, R. C., Plant, K. L., Jikyong, U., Nam, V. H., Bunyasi, B., Kokwaro, G. O., ... & Stanton, N. A. (2019). Vulnerable road users in low-, middle-, and high-income countries: validation of a pedestrian behaviour questionnaire. Accident Analysis & Prevention, 131, 80-94.

  18. McIlroy, R. C., Plant, K. A., Hoque, M. S., Wu, J., Kokwaro, G. O., Nam, V. H., & Stanton, N. A. (2019). Who is responsible for global road safety? A cross-cultural comparison of Actor Maps. Accident Analysis & Prevention, 122, 8-18.

  19. Qi, G., Wu, J., Zhou, Y., Du, Y., Jia, Y., Hounsell, N., & Stanton, N. A. (2019). Recognizing driving styles based on topic models. Transportation research part D: transport and environment, 66, 13-22.

  20. Xu, M., Wu, J., Liu, M., Xiao, Y., Wang, H., & Hu, D. (2018). Discovery of critical nodes in road networks through mining from vehicle trajectories. IEEE Transactions on Intelligent Transportation Systems, 20(2), 583-593.

  21. Liao, L., Wu, J., Zou, F., Pan, J., & Li, T. (2018). Trajectory topic modelling to characterize driving behaviors with GPS-based trajectory data. Journal of Internet Technology, 19(3), 815-824.

  22. Hu, K., Wu, J., & Liu, M. (2018). Exploring the energy efficiency of electric vehicles with driving behavioral data from a field test and questionnaire. Journal of Advanced Transportation, 2018.

  23. Kong, Y., Wu, J., Xu, M., & Hu, K. (2017). Charging pile siting recommendations via the fusion of points of interest and vehicle trajectories. China Communications, 14(11), 29-38.

  24. Jia, Y., Wu, J., & Xu, M. (2017). Traffic flow prediction with rainfall impact using a deep learning method. Journal of advanced transportation, 2017.

  25. Jia, Y., Wu, J., Ben-Akiva, M., Seshadri, R., & Du, Y. (2017). Rainfall-integrated traffic speed prediction using deep learning method. IET Intelligent Transport Systems, 11(9), 531-536.

  26. Yang, S., Wu, J., Du, Y., He, Y., & Chen, X. (2017). Ensemble learning for short-term traffic prediction based on gradient boosting machine. Journal of Sensors, 2017.

  27. Hu, K., Wu, J., & Schwanen, T. (2017). Differences in energy consumption in electric vehicles: An exploratory real-world study in Beijing. Journal of Advanced Transportation, 2017.

  28. Yang, S., Wu, J., Qi, G., & Tian, K. (2017). Analysis of traffic state variation patterns for urban road network based on spectral clustering. Advances in Mechanical Engineering, 9(9), 1687814017723790.

  29. Du, Y., Wu, J., Yang, S., & Zhou, L. (2017). Predicting vehicle fuel consumption patterns using floating vehicle data. Journal of Environmental Sciences, 59, 24-29.

  30. Hu, D., Zhou, Y., Xu, M., Wu, J., Du, Y., Song, B., & Hu, K. (2017). Identifying regional service function from PM 2.5 mass concentration throughout a city with non-negative tensor factorization approach. Environmental Science and Pollution Research, 24(35), 26893-26900.

  31. Zhang, R., Wu, J., Huang, L., & You, F. (2017). Study of bicycle movements in conflicts at mixed traffic unsignalized intersections. IEEE Access, 5, 10108-10117.

  32. Huang, L., Wu, J., You, F., Lv, Z., & Song, H. (2016). Cyclist social force model at unsignalized intersections with heterogeneous traffic. IEEE Transactions on Industrial Informatics, 13(2), 782-792.

  33. J. Hunt and J. P. Wu, "Asian Urban Environment and Climate Change: Preface," (in English), Journal of Environmental Sciences, Editorial Material vol. 59, pp. 1-5, Sep 2017.

  34. Qi, G., Du, Y., Wu, J., Hounsell, N., & Jia, Y. (2015). What is the appropriate temporal distance range for driving style analysis?. IEEE Transactions on Intelligent Transportation Systems, 17(5), 1393-1403.

  35. Du, Y., Wu, J., Jia, Y., & Xu, M. (2016). An Improved Regional Traffic Volume Dynamic Feedback Control. International Journal of Software Engineering and Knowledge Engineering, 26(09n10), 1539-1554.

  36. Qi, G., Du, Y., Wu, J., & Xu, M. (2015). Leveraging longitudinal driving behaviour data with data mining techniques for driving style analysis. IET intelligent transport systems, 9(8), 792-801.

  37. Xu, M., Du, Y., Wu, J., & Zhou, Y. (2015). Map matching based on conditional random fields and route preference mining for uncertain trajectories. Mathematical Problems in Engineering, 2015.

  38. Du, Y., Wu, J., Qi, G., & Jia, Y. (2015). Simulation study of bicycle multi-phase crossing at intersections. In Proceedings of the Institution of Civil Engineers-Transport (Vol. 168, No. 5, pp. 457-465). Thomas Telford Ltd.

  39. Du, Y., Jia, Y., Wu, J., Xu, M., & Yang, S. (2015). Traffic Environmental Capacity and MFD Based Traffic Emission Dynamic Control Model. Journal of Residuals Science & Technology, 12(4).

  40. Song, B., Hu, D., Wu, J., Hu, K., & Du, Y. (2015). UNDERSTANDING OF THE IMPACT ON THE MOVING SPEED OF MONITORING VEHICLES ON MEASURED POLLUTANT CONCENTRATIONS. Fresenius Environmental Bulletin, 24(6 A), 2167-2178.

  41. Jia, Y., Du, Y., & Wu, J. (2014). Stability analysis of a car-following model on two lanes. Mathematical Problems in Engineering, 2014.

  42. Jia, Y. H., Du, Y. M., & Wu, J. P. (2014). An improved car-following model considering variable safety headway distance. Physics Essays, 27(4), 616-619.

  43. Song, B. I. N. G. Y. U. E., Wu, J., Zhou, Y. A. N. G., & Hu, K. E. Z. H. E. N. (2014). Fine-scale prediction of roadside CO and NOx concentration based on a random forest model. J. Residuals Sci. Technol, 11(3), 83.

  44. Dong, J. X., Cheng, T., Xu, J., & Wu, J. (2013). Quantitative assessment of urban road network hierarchy planning. The Town Planning Review, 445-472.

  45. Du, Y., Wu, J., & Qi, G. (2013). The Simulation Study for Hydro-Meteorological Hazards Contingency Plan in Henan Highway Network. In Applied Mechanics and Materials (Vol. 256, pp. 2786-2789). Trans Tech Publications Ltd.

  46. Qi, G., Wu, J., & Du, Y. (2013). Research on the traffic simulation platform based on the real-time mobile phone data. In Applied Mechanics and Materials (Vol. 253, pp. 1365-1368). Trans Tech Publications Ltd.

  47. Jia, Y., Wu, J., & Du, Y. (2013). Modification of traffic wave theory and the development of a new stop-wave model. In Applied Mechanics and Materials (Vol. 253, pp. 1615-1618). Trans Tech Publications Ltd.

  48. Huang, L., & Wu, J. (2009). Cyclists' path planning behavioral model at unsignalized mixed traffic intersections in China. IEEE Intelligent Transportation Systems Magazine, 1(2), 13-19.

  49. Wu, J., Sui, Y., & Wang, T. (2009, March). Intelligent transport systems in China. In Proceedings of the Institution of Civil Engineers-Municipal Engineer (Vol. 162, No. 1, pp. 25-32). Thomas Telford Ltd.

  50. Wu, J., McDonald, M., & Chatterjee, K. (2007). A detailed evaluation of ramp metering impacts on driver behaviour. Transportation Research Part F: Traffic Psychology and Behaviour, 10(1), 61-75.

  51. Huang, L., & Wu, J. (2003, October). Study on the cyclist behavior at signalized intersections. In Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems (Vol. 1, pp. 317-322). IEEE.

  52. Wu, J., Brackstone, M., & McDonald, M. (2003). The validation of a microscopic simulation model: a methodological case study. Transportation Research Part C: Emerging Technologies, 11(6), 463-479.

  53. Wu, J., Brackstone, M., & McDonald, M. (2000). Fuzzy sets and systems for a motorway microscopic simulation model. Fuzzy sets and systems, 116(1), 65-76.

  54. Wu, J., & Hounsell, N. (1998). Bus priority using pre-signals. Transportation Research Part A: Policy and Practice, 32(8), 563-583.


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