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个人简介

傅挺,同济大学交通运输工程学院研究员,博士生导师。2018年博士毕业于加拿大麦吉尔大学,2020年1月加入同济大学,同年入选上海市“海外高层次人才计划”,上海市青年英才扬帆计划。 研究涉及轨迹大数据挖掘,交通安全风险,交通智慧感知与主动安全管控。担任国际汽车工程师学会(SAE International)交通安全替代指标研究委员会秘书、决策委员、委员,及世界交通运输大会(WTC)交通与空间优化委员会技术委员;担任《Digital Transportation and Safety》副主编;担任《铁道科学与工程学报》青年编委,担任IEEE Trans on ITS、Accident Analysis & Prevention、IEEE Vehicular Technology Magazine、IET Intelligent Transportation Systems、Tunnelling and Underground Space Technology、Journal of Advanced Transportation、Journal of Transportation Safety & Security等十余个SCI/SSCI期刊审稿人。 近年在道路交通安全领域的国际会议及期刊发表高质量论文50余篇(其中一作或通讯发表SCI论文22篇,其中12篇JCR一区,1篇ESI),申请专利14项,获批5项;主持国家自然科学基金青年项目、国家重点研发计划子课题等科研与企业服务类项目7项,目前作为核心人员主要参与包括国家重点研发计划课题《港珠澳大桥智能化运维技术集成应用》等科研项目7项,参与编写国际标准《Concepts, Terms and Definitions related to Surrogate Measures of Safety》(SAE标准)1项,目前参与编写交通部及公安部行业标准、中国工程建设标准化协会标准等共6项。成果获国际、国家及省部级科学技术以及学术论文奖11 项,包括加拿大交通学会优秀论文奖1项,上海市交通工程学会科学技术奖一等奖(排名第三)1项。 工作经历 2023.1-至今 同济大学交通运输工程学院 副教授 2021.4-至今 同济大学交通运输工程学院 研究员 2020.1-2021.3 同济大学交通运输工程学院 助理教授 2018.7-2019.12 加拿大滑铁卢大学(University of Waterloo) 土木与环境工程学院 博士后研究员 教育经历 2014.1-2018.12 加拿大麦吉尔大学(McGill University) 土木工程学院 博士 2011.9-2014.5 加拿大麦吉尔大学(McGill University) 土木工程学院 硕士 2007.9-2011.7 同济大学 交通运输工程学院 学士学位 获奖情况 2020,上海市交通工程学会科学技术奖一等奖(排名第三) 2020,上海市海外高层次人才 2020,上海市青年科技英才杨帆计划资助 2019,加拿大魁北克省道路安全组织年会(RRSR),学术报告及海报奖第二名 2019,加拿大魁北克省道路安全组织优秀博士后学术奖 2018,加拿大魁北克省道路安全组织(RRSR),学术论文奖第二名 2017,加拿大道路安全协会(CARSP),学术论文奖 2017,加拿大魁北克省道路安全组织(RRSR),学术论文奖第一 2017,加拿大魁北克省道路安全组织(RRSR)优秀博士生奖学金 2016,加拿大交通工程学会 (TAC),学术论文奖 2016,加拿大道路安全协会(CARSP),学术论文奖 2014-2017,加拿大麦吉尔大学优秀工程博士奖学金资助 2012-2018,均获得麦吉尔大学年度优秀研究生奖学金

研究领域

主要研究方向为道路交通安全风险解析与量化辩识。主要围绕基于道路使用者轨迹大数据的交通安全替代分析方法理论研究与实践成果展开研究,在交通感知及轨迹数据提取、替代方法分析技术、基于轨迹挖掘的交通行为研究、安全分析自动化方面形成了新颖和独到的研究特点。成果概括为:(1)开发验证包括基于热感应摄像技术和基于激光雷达检测的道路使用者轨迹采集技术;(2)建立了基于轨迹分析的行人过街安全理论模型以及基于轨迹的高速公路风险评估方法。围绕成果,近年来发表论文40余篇,其中第一作者或通讯作者发表英文期刊27篇(SCI及SSCI检索22篇,其中JCR-Q1区12篇,ESI高被引1篇,EI检索5篇)。

近期论文

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Ting Fu, Weichao Hu*; Nicolas Saunier; Luis Miranda-Moreno, Investigating Secondary Pedestrian-vehicle Interactions at Non-signalized Intersections using Vision-based Trajectory Data, Transportation Research, Part C: Emerging Technologies, 2019, 105C:224-240. (SCI, Q1) Junhua Wang, Wenxiang Xu,Ting Fu*, Qiangqiang Shangguan, Anae Sobhani, Modeling Aggressive Driving Behavior Based on Graph Construction, Transportation Research, Part C: Emerging Technologies, 2022, 138:103654. (SCI, Q1) Hongren Gong,Ting Fu*, Yiren Sun, Zhongyin Guo, Lin Cong*, Wei Hu, Ziwen Ling. Two-vehicle driver-injury severity: A multivariate random parameters logit approach, Analytic Methods in Accident Research, 2021, 33: 100190. (SCI, Q1) Qiangqiang Shangguan, Junhua Wang*,Ting Fu*, Shou'en Fang, Liping Fu. An empirical investigation of driver car-following risk evolution using naturistic driving data and random parameters multinomial logit model with heterogeneity in means and variance, Analytic Methods in Accident Research, 2023. (SCI, Q1) Junhua Wang, Wenxiang Xu,Ting Fu*, Rui Jiang. Recognition of Trip-Based Aggressive Driving: A System Integrated With Gaussian Mixture Model Structured of Factor-Analysis, and Hierarchical Clustering, IEEE Transactions on Intelligent Transportation Systems, 2022. (SCI, Q1) Ting Fu*, Luis Miranda-Moreno, Nicolas Saunier. A Novel Framework to Evaluate Pedestrian Safety at Nonsignalized Locations; Accident Analysis & Prevention, 2018, 111:23-33. (SSCI, Q1, ESI高被引) Junhua Wang,Ting Fu*, Qiangqiang Shangguan*.Wide-area vehicle trajectory data based on advanced tracking and trajectory splicing technologies: Potentials in transportation research; Accident Analysis & Prevention, 2023, 186:107044. (SSCI, Q1) Qiangqiang Shangguan,Ting Fu*, Junhua Wang, Shou'en Fang, Liping Fu. A proactive lane-changing risk prediction framework considering driving intention recognition and different lane-changing patterns. Accident Analysis & Prevention, 2021, 164: 106500. (SSCI, Q1) Ting Fu, Xiaochen Yu, Binglei Xiong, Chaozhe Jiang*, Junhua Wang*. A Method in Modeling Interactive Pedestrian Crossing and Vehicle Yielding Decisions during Their Interactions at Intersections. Transportation Research Part F: Traffic Psychology and Behaviour, 2022, 88: 37-53. (SCI) Chaozhe Jiang, Rui Qiu,Ting Fu*, Liping Fu, Binglei Xiong, Zhengyang Lu. Impact of right-turn channelization on pedestrian safety at signalized intersections, Accident Analysis & Prevention, 2020, 136(105399). (SSCI, Q1) Qiangqiang Shangguan,Ting Fu*, Shuo Liu. Investigating Rear-end Collision Avoidance Behavior under Varied Foggy Weather Conditions: A Study using Advanced Driving Simulator and Survival Analysis, Accident Analysis & Prevention, 2020, 139(105499). (SSCI, Q1) Junhua Wang, Yumeng Kong,Ting Fu*, Expressway crash risk prediction using back propagation neural network: A brief investigation on safety resilience,Accident Analysis & Prevention, 2019,124:180-192. (SSCI, Q1) Junhua Wang, Tianyang Luo,Ting Fu*, Crash Prediction based on Traffic Platoon Characteristics using Floating Car Trajectory Data and the Machine Learning Approach, Accident Analysis & Prevention, 2019, 133(105320). (SSCI, Q1) Ting Fu*, Luis Miranda-Moreno, Nicolas Saunier. Pedestrian crosswalk safety at nonsignalized crossings during nighttime: use of thermal video data and surrogate safety measures. Transportation research record 2016, 2586(1): 90-99. (SCI) Qiangqiang Shangguan, Junhua Wang,Ting Fu*, Shou'en Fang. Quantification of cut-in risk and analysis of its influencing factors: a study using random parameters ordered probit model. Journal of Transportation Safety & Security, 2021. (SCI) 轨迹数据共享平台 Tongji Road Trajectory Sharing Platform(平台网址): Junhua Wang,Ting Fu. TJRD TS [EB/OL].https://www.tjrdts.com, 2021. 平台相关论文: Junhua Wang,Ting Fu*, Jiangtian Xue, Chengmin Li, Hao Song, Wenxiang Xu, Qiangqiang Shangguan. Realtime Wide-area Vehicle Trajectory Tracking using Millimeter-wave Radar Sensors and the Open TJRD TS Dataset,International Journal of Transportation Science and Technology, 2022. Junhua Wang,Ting Fu*, Qiangqiang Shangguan*. Wide-area vehicle trajectory data based on advanced tracking and trajectory splicing technologies: Potentials in transportation research; Accident Analysis & Prevention, 2023, 186:107044. (SSCI, Q1)

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