吴兵教授课题组成立于2001年,主要从事交通规划、管理与控制等方面的研究与发展。目前,课题组教师团队拥有教授1人、副教授2人,其中博士研究生导师3人。
课题组自成立以来,发扬“激情、奋进、责任、博爱”的精神,在交通学科领域努力钻研,勇猛精进。学术研究把握交通发展前沿,注重学科交叉特点,运用多学科理论与技术来解析交通系统现象、探索交通规律,从而提出交通优化策略,构建创新理论;人才培养秉承因材施教、理论研究与实践训练相结合的理念,努力创建交通研究精英团队;社会服务注重理论联系实践,把脉城市交通,积极运用研究成果解决实际问题。
学术研究方面。近年来,课题组先后承担了国家高技术研究发展计划(863计划)项目“特殊需求下区域交通协同管控技术(批准号:2011AA110305)”、国家自然科学基金重点项目“基于多源检测数据的城市路网交通流主动流主动式管理与控制理论研究(批准号:51138003)”、国家自然科学基金面上项目“基于出行服务链的城镇群交通模式发展研究(批准号:51178346)”、国家自然科学基金项目“基于行为动力分析的公交竞争力研究(批准号:70901057)”等国家级项目以及教育部博士点基金项目“城市土地再开发条件下的交通拥挤研究(批准号:200802470030)”、教育部博士点新教师基金项目“基于行为动力分析的公交规模与政策研究(批准号:20090072120011)”、交通部规划司项目“‘十二五期’我国城镇化发展对交通发展的影响及对策研究(招标号:0701-0841ITC2C064)”、浙江省交通运输厅项目“杭州市公路网抗击自然灾害能力评估与应对机制研究”等省部级项目;主持编写了中华人民共和国行业标准《公路养护安全作业规程(JTG H30-2004)》、上海市行业标准《城市道路养护维修作业安全技术规程(SZ-51-2006)》、以及《高速公路养护作业危险源控制和安全管理对策》;此外,课题组还完成了大量决策咨询和应用研究课题。出版专著《特殊需求下区域交通协同管控理论与技术》(2015年出版)、《“十二五期”我国城镇化发展对交通发展的影响及对策研究》(2011年出版),发表学术论文110多篇。
教学及人才培养方面。迄今为止,课题组已培养博士6名、硕士44名,分布于国内外的大学、科研机构以及行业管理和咨询部门。课题组教师主讲“交通管理与控制”、“交通系统控制方法与实践”等专业课程,其中吴兵教授主讲的专业主干课程“交通管理与控制”于2006年入选上海市精品课程,2010年入选国家精品课程,2012年入选国家精品共享资源课程。课题组教师还主持编写了《交通管理与控制》,参与编写了《城市群交通规划》、《物流工程》等多部高等学院交通工程专业教材。
社会服务方面。近年来,课题组承担了上海市、天津市、广州市、杭州市、宁波市、济南市、青岛市等多个城市的交通规划编制、交通影响研究、交通组织、交通设计以及交通管理系统开发等工作。课题组力争将理论研究与实践应用密切集合,尽最大努力服务社会、回报社会。
更多信息请访问http://wubing.tongji.edu.cn/
● 论文
1. Wu B, Dong Z, Wang Y, et al. A Joint Modeling Analysis of Passengers??? Intercity Travel Destination and Mode Choices in Yangtze River Delta Megaregion of China[J]. Mathematical Problems in Engineering,2016,(2016-7-19), 2016, 2016(7):1-10.
2. Dong Z, Wu B, Li L. The Analysis of Transportation Demand Generation Mechanisms of the Urban Agglomerations in China[C]// International Conference of Chinese Transportation Professionals. 2009:1-6.
3. 吴兵, 李林波, 李晔. 《交通管理与控制》课程教学改革探索与实践[J]. 教育教学论坛, 2012(31):155-157.
4. 吴兵, 董治, 李林波. 城市公共交通规划中的民众参与问题研究[J]. 山东交通学院学报, 2008, 16(2):32-35.
5. 吴兵, 杨佩昆. 高速道路入口匝道通行能力研究[J]. 同济大学学报(自然科学版), 1999(4):422-426.
6. 吴兵, 杨佩昆. 道路养护作业时的交通事故风险度预测[J]. 人类工效学, 1995(2):32-34.
7. 王艳丽, 吴兵, 李林波. 基于VISSIM的“交通管理与控制”实验课程设计[J]. 实验室研究与探索, 2016, 35(3):210-212.
8. 操春燕, 栗慧龙, 吴兵. 基于神经网络的交叉口交通流量预测方法研究[J]. 交通科技与经济, 2007, 9(1):99-100.
9. 周茂松, 吴兵. 美国道路作业区交通管理研究与启示[J]. 中外公路, 2005, 25(1):116-119.
10. 周茂松, 吴兵, 盖松雪. 高速公路养护维修作业区通行能力影响因素的微观仿真研究[J]. 交通信息与安全, 2004, 22(6):54-57.
11. Li L, Xiong J, Chen A, et al. Key Strategies for Improving Public Transportation Based on Planned Behavior Theory: Case Study in Shanghai, China[J]. Journal of Urban Planning and Development, 2014, 141(2): 04014019.
12. Li L, Wang J, Song Z, et al. Analysing the impact of weather on bus ridership using smart card data[J]. IET Intelligent Transport Systems, 2014, 9(2): 221-229.
13. 李林波, 王曼, 董治, 吴兵. 基于泊位功能和区位条件的停车配建方法[J]. 中国公路学报, 2010, 23(1): 111-115.
14. 李林波, 吴兵. 2010 年上海世博会行李跟随系统[J]. 城市交通, 2009, 7(3):57-61.
15. 李林波, 杨东援. 基于空间特性的行李跟随系统的车辆调度方法[J]. 交通运输工程学报, 2008, 8(5):109-113.
16. 李林波, 杨东援, 熊文. 大公共交通系统之构建[J]. 城市规划学刊, 2005 (4): 72-75.
17. 吴兵, 李林波. 交通拥挤的进化动态分析[J]. 中国公路学报, 2006, 19(3): 106-110.
18. 李林波, 吴兵. 出行者心理因素对公共交通发展的影响[J]. 重庆交通学院学报, 2004, 23(3): 94-97.
19. 白玉方,李林波,吴兵. 出行者公交出行意愿影响因素研究[J]. 重庆交通大学学报(自然科学版),2012,31(1):72-76.
20. 朱锐,李林波,吴兵. 基于模糊评价的常规公交候车服务水平研究[J]. 重庆交通大学学报(自然科学版),2012,31(3):455-476.
21. 朱锐, 张婧姝, 李林波. 基于 ECR 模型的常规公交站点服务信息重要度研究[J]. 交通与运输, 2012, 27(B12): 76-80.
22. 张飞飞,吴兵,李林波. 新城区CBD区域停车需求预测方法[J]. 重庆交通大学学报(自然科学版),2012,31(5):1018-1022.
23. 吉锴, 李林波, 吴兵. 出行者特征要素对公交服务模式的影响分析[J]. 交通科技, 2011 (4): 96-99.
24. 董治, 吴兵, 王艳丽, 李林波. 中国城市群交通系统发展特征研究[J]. 中国公路学报, 2011, 24(2): 83-88.
25. Dong, Zhi; Li, Linbo; Wu, Bing; Zhao, Xiangmo, Investigating Mode Preference of Intercity Business Travelers in the Urban Agglomeration of China: Application of Fractional Multinomial Logit Model, The Proceeding of TRB 94nd annual meeting, 2015.1.Jan 11-15
26. Dong, Zhi; Li, Linbo; Wu, Bing. Who Makes the Choice? Modeling Mode Choice for Intercity Business Travel Based on Segmentation, The Proceeding of TRB 93nd annual meeting, 2014.1.Jan 12-16
27. Linbo Li, JieXiong, Zhi Dong, Yufang Bai and Bing Wu, Exploring the Factors Affecting Current Transit Passengers’ Loyalty by Structural Equation Model: Case Study of Shanghai, China, The Proceeding of TRB 92nd annual meeting, 2013.1
28. 李林波,熊婕,可预知特殊需求下网络禁向变结构优化方法[J],第七届中国智能交通年会优秀论文集,2012,9:833-838
29. LI Linbo, WANG Man, WU Bing, Study on the location parking index based on function division of parking space,Proceedings of the 9th International Conference of Chinese Transportation Professionals,ASCE, 2009: pp 1-8
30. LI Linbo, YANG Dongyuan, Study of the VRP based on the fuzzy demand[C], Proceedings of the 8th International Conference of Chinese Logistics and Transportation Professionals-Logistics: the Emerging Frontiers of Transportation and Development In China, ASCE, 2008, Vol2.: pp 1178~1184.
31. LI Linbo, WU Bing, Analysis of Traffic Congestion’s Inherence Based on Game Theory[C], Proceedings of the 8th International Conference of Chinese Logistics and Transportation Professionals-Logistics: the Emerging Frontiers of Transportation and Development In China, ASCE, 2008, Vol5.: pp 4226~4231.
32. 李林波,我国交通运输发展过程中的结构性问题研究[C],第七届世界华人交通运输学术大会会议,2007,4.
33. Zou, Y., Yang H., Zhang, Y., Tang J., and Zhang W., 2017. Mixture modeling of freeway speed and headway data using multivariate skew-t distributions. Transportmetrica A: Transport Science, in press.
34. Zou, Y., Tang J., Wu, L., Wang, Y. and Henrickson K., 2017. Quantile analysis of factors influencing the time taken to clear road traffic incidents. Proceedings of Transport, in press.
35. Peng, Y., Abdel-Aty, M., Lee, J., and Zou, Y. (通信作者), 2017. Analysis of the Impact of Fog-related Reduced Visibility on Traffic Parameters. Journal of Transportation Engineering , in press.
36. Tang, J., Zou, Y. (通信作者), Zhang W., and Wang, Y., 2017. An Improved Fuzzy Neural Network for Traffic Speed Prediction Considering Periodic Characteristic. Intelligent Transportation Systems, IEEE Transactions on, in press.
37. Wang, Y., Zou, Y. (通信作者), Kristian, H., Wang, Y., Tang, J., Park, B., 2017. Google Earth elevation data extraction and accuracy assessment for transportation applications. PLoS one, 12(4), e0175756.
38. Zou, Y., Ash, J.E., Park, B.J., Lord, D., and Wu, L., 2017. Application of Finite Mixture of Negative Binomial Regression Models in Estimating Empirical Bayes Estimates. Journal of Applied Statistics, in press.
39. Yuan, S., Wright, B., Zou, Y., and Wang, Y., 2017. Quantification of variability of valid travel times with FMMs for buses, passenger cars, and taxis. IET Intelligent Transport Systems, 11(1), 1-9.
40. Zou, Y., Zhang, Y., 2016. A copula-based approach to accommodate the dependence among microscopic traffic variables, Transportation Research Part C, 70, 53-68.
41. Zhang, W., Tang, J., Henrickson K., Zou, Y., and Wang, Y., 2016. Hybrid Short-term Prediction of Traffic Volume at Ferry Terminal based on Data Fusion. IET Intelligent Transport Systems, 10(8), 524-534.
42. Tang, J., Zou, Y., Ash, J., Zhang S., Liu F, Wang, Y., 2016. Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System. PLoS ONE 11(2): e0147263.
43. Zhang, W., Zou, Y., Tang, J., Ash, J.E., and Wang, Y., 2016. Short-term prediction of vehicle waiting queue at ferry terminal based on machine learning method. Journal of Marine Science and Technology, 21(4), 729-741.
44. Zou, Y., Henrickson K., Lord, D., Wang, Y., and Xu K., 2016. Application of finite mixture models for analyzing freeway incident clearance time. Transportmetrica A: Transport Science, 12(2), 99-115.
45. Zha, L., Lord, D., Zou, Y. (通信作者), 2016. Examining the Poisson Inverse Gaussian generalized linear regression model for analyzing motor vehicle crash data. Journal of Transportation Safety & Security, 8(1), 18-35.
46. Zou, Y., Hua, X., Zhang, Y., Wang, Y., 2015. Hybrid short-term freeway speed prediction methods based on periodic analysis. Canadian Journal of Civil Engineering, 42 (8), 570-582.
47. Wu, L., Lord, D., Zou, Y. (通信作者), 2015. Validation of Crash Modification Factors Derived from Cross-Sectional Studies with Regression Models. Transportation Research Record, 2514, 88-96. (TRB Committee ANB20 2015 Young Researcher Paper Award)
48. Wright, B., Zou, Y. (通信作者), Wang, Y., 2015. The impact of traffic incidents on the reliability of freeway travel times. Transportation Research Record, 2484, 90-98.
49. Kristian, H., Zou, Y., Wang, Y., 2015. Flexible and robust method for missing loop detector data imputation. Transportation Research Record, 2527, 29-36.
50. Zou, Y., Wu, L., Lord, D., 2015. Modeling over-dispersed crash data with a long tail: examining the accuracy of the dispersion parameter in negative binomial models. Analytic Methods in Accident Research, 5, 1-16.
51. Zou, Y., Zhu, X., Zhang, Y., Zeng, X., 2014. A space-time diurnal method for short-term freeway travel time prediction. Transportation Research Part C, 43(1), 33-49.
52. Zou, Y., Zhang, Y., Zhu, X., 2014. Constructing a bivariate distribution for freeway speed and headway data. Transportmetrica A: Transport Science, 10(3), 255-272.
53. Peng, Y., Lord, D., Zou, Y., 2014. Applying the Generalized Waring model for investigating sources of variance in motor vehicle crash analysis. Accident Analysis & Prevention, 73, 20-26.
54. Zou, Y., Zhang, Y., Lord, D., 2014. Analyzing different functional forms of the varying weight parameter for finite mixture of negative binomial regression models. Analytic Methods in Accident Research, 1, 39-52.
55. Wu, L., Zou, Y. (通信作者), Lord, D., 2014. Comparison of Sichel and Negative Binomial models in hotspot identification. Transportation Research Record, 2460, 107-116.
56. Chen Z., Zhang, Y., Lv J., Zou, Y., 2014. Model for Optimization of Ecodriving at Signalized Intersections. Transportation Research Record, 2427, 54-62.
57. Zou, Y., Lord, D., Zhang, Y., Peng, Y., 2013. Comparison of Sichel and Negative Binomial models in estimating empirical bayes estimates. Transportation Research Record, 2392, 11-21.
58. Zou, Y., Zhang, Y., Lord, D., 2013. Application of finite mixture of negative binomial regression models with varying weight parameters for vehicle crash data analysis. Accident Analysis & Prevention, 50, 1042-1051.
59. Zou, Y., Zhang, Y., 2011. Use of skew-normal and skew-t distributions for mixture modeling of freeway speed data. Transportation Research Record, 2260, 67-75.
60. Gharaibeh, N.G., Zou, Y., Saliminejad, S., 2010. Assessing the agreement among pavement condition indexes. Journal of Transportation Engineering, 136(8), 765-772.