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涂然

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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

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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

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）
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）
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）
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
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