导师风采
涂然
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个人信息

Personal Information

  • 副研究员
  • 导师类别:硕士生导师
  • 性别: 女
  • 学历:博士研究生
  • 学位:博士

联系方式

Contact Information

  • 所属院系:交通学院
  • 所属专业: 交通运输工程  、 交通运输
  • 邮箱 : turancoolgal@seu.edu.cn
  • 工作电话 : -

个人简介

Personal Profile

教育背景

·        博士,2016.09 – 2020.04,多伦多大学土木工程学院,导师: MarianneHatzopoulou (marianne.hatzopoulou@utoronto.ca)

·        硕士,2014.08 – 2016.05,弗吉尼亚理工大学土木工程学院,导师:Hesham Rakha (hrakha@vt.edu)

·        交换生2013.09– 2014.01,瑞士联邦洛桑理工学院土木工程学院

·        工学学士,2010.09 – 2014.06,同济大学交通运输工程学院

工作经历

·        博士后,多伦多大学土木学院(2020.05-2020.09),导师:Marianne Hatzopoulou

·        研究助理,多伦多大学土木工程学院(2016 – 2019)、弗吉尼亚理工大学土木工程学院(2014 – 2016)


  • 研究方向Research Directions
机动车能耗和排放建模, 绿色交通运输策略
科研项目

  1. 驾驶员动态认知行为机制下生态驾驶诱导决策模型,国家自然科学基金青年科学基金项目,2022-2024(主持)
  2. 面向驾驶员认知行为异质性的生态驾驶诱导决策模型,江苏省基础研究计划(自然科学基金)--青年基金项目,2021-2024(主持)
  3. 面向低排放的驾驶员行为修正关键技术研究,国家科技部重点研发计划政府间国际科技创新合作专项项目,2021-2024(骨干)
  4. Eco-Score: environmental evaluation of driving operations,2019 – 2020 (参与,与加拿大道明保险公司合作,加拿大自然科学工程研究委员会NSERC资助)

研究成果

  • Tu,R., Li, T., Meng, C., Xie, Y., Xie, F., Yang, F., Chen,H., Li, Y., Gao, J., Liu, Y., 2021. Real-world Emissions of Construction MobileMachines and Comparison to a Non-road Emission Model. Sci. Total Environ. 771,145365. https://doi.org/10.1016/j.scitotenv.2021.145365
  • Tu, R,Xu, J., Wang, A., Zhai, Z., Hatzopoulou, M., 2021. Effects of ambienttemperature and cold starts on excess NOx emissions in a gasoline directinjection vehicle. Sci. Total Environ. 760, 143402. https://doi.org/10.1016/j.scitotenv.2020.143402
  • Tu, R., Gai, Y. (Jessie), Farooq, B., Posen, D.,Hatzopoulou, M., 2020. Electric vehicle charging optimization to minimizemarginal greenhouse gas emissions from power generation. Appl. Energy 277,115517. https://doi.org/10.1016/j.apenergy.2020.115517
  • Tu, R., Wang, A., Hatzopoulou,M., 2019. Improving the accuracy of emission inventories with amachine-learning approach and investigating transferability across cities. J.Air Waste Manag. Assoc. 69, 1377–1390. https://doi.org/10.1080/10962247.2019.1668872
  • Tu, R.,Alfaseeh, L., Djavadian, S., Farooq, B., Hatzopoulou, M., 2019. Quantifying theimpacts of dynamic control in connected and automated vehicles on greenhousegas emissions and urban NO2 concentrations. Transp. Res. Part D Transp.Environ. 73, 142–151. https://doi.org/10.1016/j.trd.2019.06.008
  • Tu, R., Kamel, I., Wang, A., Abdulhai, B.,Hatzopoulou, M., 2018. Development of a hybrid modelling approach for thegeneration of an urban on-road transportation emission inventory. Transp. Res.Part D Transp. Environ. 62, 604–618. https://doi.org/10.1016/j.trd.2018.04.011
  • Tu, R., Kamel, I., Abdulhai, B.,Hatzopoulou, M., 2018. Reducing Transportation Greenhouse Gas Emissions Throughthe Development of Policies Targeting High-Emitting Trips. Transp. Res. Rec. https://doi.org/10.1177/0361198118755714
  • Xu, J., Tu, R., Wang, A., Zhai, Z., Hatzopoulou, M., 2020. Generation ofspikes in ultrafine particle emissions from a gasoline direct injection vehicleduring on-road emission tests. Environ. Pollut. 267, 115695. https://doi.org/10.1016/j.envpol.2020.115695
  • Wang, A., Tu, R., Gai, Y., Pereira, L.G., Vaughan, J., Posen, I.D., Miller,E.J., Hatzopoulou, M., 2020. Capturing uncertainty in emission estimatesrelated to vehicle electrification and implications for metropolitan greenhousegas emission inventories. Appl. Energy 265, 114798. https://doi.org/10.1016/j.apenergy.2020.114798
  • Zhai, Z., Tu, R., Xu, J., Wang, A., Hatzopoulou, M., 2020. Capturing thevariability in instantaneous vehicle emissions based on field test data.Atmosphere (Basel). 11. https://doi.org/10.3390/ATMOS11070765
  • Alfaseeh,L., Tu, R., Farooq, B., Hatzopoulou,M., 2020. Greenhouse gas emission prediction on road network using deepsequence learning. Transp. Res. Part D Transp. Environ. 88, 102593. https://doi.org/10.1016/j.trd.2020.102593
  • Djavadian,S., Tu, R., Farooq, B., Hatzopoulou,M., 2020. Multi-objective eco-routing for dynamic control of connected &automated vehicles. Transp. Res. Part D Transp. Environ. 87, 102513. https://doi.org/10.1016/j.trd.2020.102513
  • Wang, A.,Xu, J., Tu, R., Saleh, M.,Hatzopoulou, M., 2020. Potential of machine learning for prediction of trafficrelated air pollution. Transp. Res. Part D Transp. Environ. 88, 102599. https://doi.org/10.1016/j.trd.2020.102599
  • Nan, S.,Yan, L., Tu, R., Li, T., 2020.Modeling lane-transgressing behavior of e-bike riders on road sections withmarked bike lanes: A survival analysis approach. Traffic Inj. Prev. 22,153–157. https://doi.org/10.1080/15389588.2020.1853711
  • Gao, J.,Chen, H., Liu, Y., Li, Y., Li, T., Tu,R., Liang, B., Ma, C., 2021. The effect of after-treatment techniques onthe correlations between driving behaviours and NOx emissions of a passengercars. J. Clean. Prod. 288, 125647. https://doi.org/10.1016/j.jclepro.2020.125647
  • Xu, J.,Saleh, M., Wang, A., Tu, R.,Hatzopoulou, M., 2019. Embedding local driving behaviour in regional emissionmodels to increase the robustness of on-road emission inventories. Transp. Res.Part D Transp. Environ. 73, 1–14. https://doi.org/10.1016/j.trd.2019.05.011
  • Xu, J.,Wang, J., Hilker, N., Fallah-Shorshani, M., Saleh, M., Tu, R., Wang, A., Minet, L., Stogios, C., Evans, G., Hatzopoulou,M., 2018. Comparing emission rates derived from a model with those estimatedusing a plume-based approach and quantifying the contribution of vehicleclasses to on-road emissions and air quality. J. Air Waste Manag. Assoc. 68,1159–1174. https://doi.org/10.1080/10962247.2018.1484395
  • Xu, J., Hilker, N., Turchet, M., Al-Rijleh, M.K., Tu, R., Wang, A., Fallahshorshani, M.,Evans, G., Hatzopoulou, M., 2018. Contrasting the direct use of data fromtraffic radars and video-cameras with traffic simulation in the estimation ofroad emissions and PM hotspot analysis. Transp. Res. Part D Transp. Environ.62, 90–101. https://doi.org/10.1016/j.trd.2018.02.010
  • *列表内已发表论文均为SCI收录


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