上官强强，特聘研究员，同济大学-加拿大滑铁卢大学联合培养博士，加拿大滑铁卢大学博士后，入选2024年上海市白玉兰人才计划青年项目。
主要研究方向为道路安全设计、危险驾驶行为机理解析、道路运行风险主动防控等。近五年在道路交通安全领域期刊及会议发表论文30余篇，其中以一作/通讯身份发表SCI期刊论文10篇（中科院一区5篇）。合作主编出版学术专著《危险驾驶行为机理解析》，授权国家发明专利2项。曾获2023年美国科学院交通研究委员会（TRB）最佳青年研究者论文奖（一作）和2022年加拿大道路安全委员会（CARSP）最佳论文奖第二名（一作）。参与完成加拿大自然科学与工程技术研究项目、加拿大交通部科研项目、多伦多市“Vision Zero”项目、国家重点研发计划及国家自然科学基金面上项目等科研项目十余项。受聘Journal of Traffic and Transportation Engineering（ESCI, IF: 7.4）、Digital Transportation and Safety、长安大学学报（自然科学版）等期刊青年编委，担任Analytic Methods in Accident Research、Transportation Research Part C: Emerging Technologies、Accident Analysis & Prevention等十余本行业知名期刊及会议论文审稿人。
教育经历
2021.12 – 2022.11 加拿大滑铁卢大学工程学院联合培养博士
2017.09 – 2022.11 同济大学交通运输工程学院博士
2013.09 – 2017.07 长安大学公路学院学士
工作经历
2024.07至今 同济大学交通学院特聘研究员
2022.12 – 2024.04 加拿大滑铁卢大学工程学院博士后
科研项目
1.Natural Sciences and Engineering Research Council of Canada (NSERC), Advancing “Vision Zero” road safety with operational AI and smart city data, 2021-2023,参与
2.Transport Canada Research Project, Development of GradeX Cost-Benefit Analysis (CBA) Module for Evaluating Grade Crossing Safety Improvement Projects, 2023-2024,参与
3.City of Toronto Research Project, A pilot project for continuous video-based traffic analysis and safety monitoring, 2021-2022,参与
4.国家重点研发计划项目，港珠澳大桥智能化运维技术集成应用，2020-2023，参与
5.国家自然科学基金面上项目，跟驰和换道中危险驾驶行为的病理诊断、致因和转归机理，2022-2025，参与
6.国家自然科学基金面上项目，高速公路容错性车流状态识别与管理控制方法研究，2019-2022，参与
获奖情况
1.2023, TRB Best Young Researcher Paper Award, Transportation Research Board (ACS10)
2.2023,第二届数字交通与智慧出行学术论坛优秀论文一等奖，广西道路运输协会
3.2022, CARSP Best Paper Award (2ndPlace), Canadian Association of Road Safety Professionals
4.2022,上海市普通高等学校优秀毕业生，上海市教育委员会
代表性学术论文
1.Shangguan, Q., Wang, Y., & Fu, L. (2024). Quantifying the effectiveness of an active treatment in improving highway-railway grade crossing safety in Canada: an empirical Bayes observational before–after study.Canadian Journal of Civil Engineering, 2024. (SCI).
2.Shangguan, Q., Wang J.*, Fu, T.*, Fang, S., & Fu, L. (2023). An empirical investigation of driver car-following risk evolution using naturistic driving data and random parameters multinomial logit model with heterogeneity in means and variances.Analytic Methods in Accident Research, 100265. (SSCI, Q1, IF=12.5)
3.Shangguan, Q., Keung J., Fu, L.*, Samara, L., Wang J., & Fu, T. (2023). Do Traffic Countermeasures Improve the Safety of Vulnerable Road Users at Signalized Intersections? A Combination of Case-Control and Cross-Sectional Studies Using Video-Based Traffic Conflicts.Transportation Research Record, 03611981231172748. (SCI)
4.Shangguan, Q., Fu, T.*, Wang, J., Fang, S., & Fu, L. (2022). A proactive lane-changing risk prediction framework considering driving intention recognition and different lane-changing patterns.Accident Analysis & Prevention, 164, 106500. (SSCI, Q1, IF=5.7).
5.Shangguan, Q., Fu, T., Wang, J.*, Luo, T., & Fang, S. (2021). An integrated methodology for real-time driving risk status prediction using naturalistic driving data.Accident Analysis & Prevention, 156, 106122. (SSCI, Q1, IF=5.7).
6.Shangguan, Q., Wang, J., Fu, T.*, & Fang, S. (2021). Quantification of cut-in risk and analysis of its influencing factors: a study using random parameters ordered probit model.Journal of Transportation Safety & Security, 1-26. (SSCI).
7.Shangguan, Q., Fu, T.*, Wang, J., Jiang, R., & Fang, S. (2021). Quantification of rear-end crash risk and analysis of its influencing factors based on a new surrogate safety measure.Journal of Advanced Transportation, 2021, 5551273. (SCI).
8.Shangguan, Q., Fu, T.*, & Liu, S. (2020). Investigating Rear-end Collision Avoidance Behavior under Varied Foggy Weather Conditions: A Study using Advanced Driving Simulator and Survival Analysis.Accident Analysis & Prevention, 139, 105499. (SSCI, Q1, IF=5.7).
9.Wang J., Fu, T.*, &Shangguan, Q.*. (2023). Wide-area Vehicle Trajectory Data based on Advanced Tracking and Trajectory Splicing Technologies: Potentials in Transportation Research.Accident Analysis & Prevention, 186, 107044. (SSCI, Q1, IF=5.7)
10.Lei, C., Ji, Y.*,Shangguan, Q.*, Du, Y., & Samuel, S. (2024). Vehicle group identification and evolutionary analysis using vehicle trajectory data.Physica A: Statistical Mechanics and its Applications, 639, 129656. (SCI)
学术专著
王俊骅；方守恩；傅挺；徐文翔；上官强强；《危险驾驶行为机理解析》，同济大学出版社，2023，ISBN 978-7-5765-0047-9
发明专利
1.宋昊；王俊骅；上官强强；一种基于交通数字孪生的交通运行风险平行仿真系统，2024，ZL202210450623.3
2.宋昊；王俊骅；上官强强；一种基于交互式自解释模型的高速公路事故风险优化方法，2024，ZL202310903318.X