This template doesn't support hiding the navigation bar.

    •  

       

       

       

       

    • Zhengbing He

      Ph.D., Professor, Vice Dean of the College
      College of Metropolitan Transportation, Beijing University of Technology, China

      For any discussion, please feel free to contact me: he dot zb at hotmail dot com

       

      贺正冰，博士，城市交通学院副院长/教授/博导、交通运输工程与信息学报主编、交通运输部青年科技英才、中国智能交通协会优秀科技创新领军人才、北京工业大学高层次人才。2011年于天津大学获得系统工程博士学位；2011-2018年就职于北京交通大学。研究方向为：智能交通系统、交通大数据分析、交通流理论等。主持国家重点研发计划课题/子课题、国家自然科学基金面上/青年项目（纵向课题总经费近1000万）。IEEE高级会员；IEEE TITS、TR C、IET ITS、IJIT、交通运输系统工程与信息、系统工程学报、交通运输研究等期刊编委；智能交通协会青年专家、管理科学与工程学会交通运输管理分会委员、公路学会自动驾驶工作委员会委员。获得公路学会及智能交通协会科技进步奖3项。发表学术论文100余篇（SCI 60余篇），第一作者论文发表在TR A/B/C/D、IEEE TITS/TIV、CACAIE等土木交通领域顶级期刊。

      Research Interests

      • Traffic Flow Theory and Characteristics
      • Intelligent Vehicles and Future Transportation
      • Urban Mobility
      • Sustainable Transportation

      Academic Service

      • IEEE, Senior Member
      • IEEE Transactions on Intelligent Transportation Systems, Associate Editor
      • Transportation Research Part C: Emerging Technologies, Editorial Advisory Board member
      • IET Intelligent Transport Systems, Associate Editor
      • International Journal of Intelligent Transportation Systems Research, Associate Editor
      • IEEE Intelligent Transportation Systems Conference (ITSC), Associate Editor, 22nd, 23rd, 24th, 
      • IEEE Access, Associate Editor (2017.10-2019.10), Outstanding Award (top 5%)
      • 2020-2021, IEEE International Conference on Intelligent Transportation Engineering, Award Chair
      • 2020 Forum on Integrated and Sustainable Transportation Systems, Delft, The Netherlands, Associate Editor
      • 19th COTA International Conference of Transportation Professionals, 2019, Nanjing, China, Area Editor: Traffic Operations, Control and Management
      • 29th IEEE Intelligent Vehicles Symposium, 2018, Changshu, China, Session Chair, Special Session on Connected and Autonomous Vehicle Test and Evaluations 
      • Outstanding Reviewer: Transportation Research Part A (top 10%)
      • Outstanding Reviewer: Transportation Research Part C (top 10%)
      • Outstanding Reviewer: Transportation Research Part D (top 10%)
      • Outstanding Reviewer: ASCE Journal of Transportation Engineering (3 persons/year, nominated)
      • Reviewing 3-5 papers every month for a number of journals, such as IEEE Series, TR Series, TS, TTR A/B
      • 交通运输工程与信息学报，主编
      • 交通运输系统工程与信息，编委
      • 系统工程学报，编委
      • 交通运输研究，编委
      • 中国公路学报，青年编委（2020-2021）
      • 交通与数据科学丛书，编委
      • 中国管理科学与工程学会，交通运输管理分委会委员
      • 中国智能交通协会，青年专家工作委员会专家
      • 中国公路学会-自动驾驶工作委员会，委员
      • 第16届中国智能交通年会，长沙，2021.11，学术论坛主席
      • 第13届中国智能交通年会，天津，2018.11，学术委员会委员
      • 第11届国际绿色智能交通系统与安全学术会议，北京，2020，组委会主席
      • 第11/12届国际绿色智能交通系统与安全学术会议，2020/2021，学术委员会委员
      • 第16届现代数学与力学会议 (MMM-XVI)，昆明，2018.9，分会召集人：网络与交通流理论
      • 创始成员：交通工程与管理青年论坛 https://traffic.sxl.cn

      Guest Edited Issues

      • IET Intelligent Transport Systems, Modelling, Operation and Management of Traffic Mixed with Connected and Automated Vehicles, 2021
      • Transportation Research Part D: Transport and Environment, Special Issue: Shared Mobility and Environment, 2020
      • Transportation Research Part C: Emerging Technologies, Special Issue: Emerging Methods for Data-driven Urban Transportation and Mobility Modeling, 2019
      • Transportmetrica A: Transport Science, Special Issue: Methodological Advancements in Understanding and Managing Urban Traffic Congestion, 2018
      • Journal of Intelligent Transportation Systems, Special Issue: Vehicle Sensor Data-based Transportation Research, 2018
      • 交通运输系统工程与信息，专刊副主编：20周年纪念特刊，2021
      • 清华大学学报（自然科学版），专刊组稿专家：城市群综合交通，2021
      • 交通运输工程学报，专刊组稿专家：车路协同机理与运行优化方法，2021
      • 智能科学与技术学报，专刊编委：智能交通系统与应用，2021
      • 交通信息与安全，专刊主编：车路协同交通管控，2020
      • 中国公路学报，专刊组稿专家：新基建条件下车路协同管控与服务，2020
      • 中国公路学报，专刊负责人：智能网联交通流，2019

      Published Journal Papers

      First-author papers have been published in many journals, including

      • Transportation Research Part A,
      • Transportation Research Part B,
      • Transportation Research Part C, 
      • Transportation Research Part D, 
      • Computer-Aided Civil and Infrastructure Engineering,
      • IEEE Transactions on Intelligent Transportation Systems,
      • IEEE Transactions on Intelligent Vehicles,
      • Transportmetrica B: Transport Dynamics,
      • ASCE Journal of Transportation Engineering,
      • Journal of Intelligent Transportation Systems,
      • Transportation Letters,
      • Proceedings of ICE-Transport,
      • Physica A: Statistical Mechanics and its Applications,
      • International Journal of Modern Physics C, etc.
      Corresponding-author papers
      • Transportation Research Part C, 
      • Transportation Research Part D, 
      • IEEE Transactions on Intelligent Transportation Systems,
      • Transportmetrica A: Transport Science,
      • Transportmetrica B: Transport Dynamics,
      • IET Intelligent Transport Systems,
      • Transportation Research Record,
      • International Journal of Sustainable Transportation, 
      • International Journal of Modern Physics B,
      • International Journal of Modern Physics C,
      • Physica A: Statistical Mechanics and its Applications, etc. 

      Education and Work Experience

      • 2018- , Beijing University of Technology, Distinguished Young Professor, College of Metropolitan Transportation
      • 2013-2017, Beijing Jiaotong University, Assistant Professor, School of Traffic and Transportation
      • 2011-2013, Beijing Jiaotong University, Postdoctoral Researcher, Collaborating with Prof. Wei Guan
      • 2008-2011, Tianjin University, Ph.D., Systems Engineering (in Transportation), Supervised by Prof. Shoufeng Ma
      • 2006-2008, Tianjin University, Master, Systems Engineering (in Transportation), Supervised by Prof. Shoufeng Ma
      • 2001-2006, Dalian University of Foreign Languages & Dalian University of Technology, Undergraduate, English and Literature
      • 2015.4-2015.8, University of Vienna, Guest Researcher, with Prof. Richard Hartl and Prof. Karl Dörner, financed by OeAD
      • 2009-2010, Georgia Institute of Technology, Visiting Ph.D. Student, Supervised by Prof. Jorge Laval

    • Publications

      To download the papers, please go to my ResearchGate page: https://www.researchgate.net/profile/Zhengbing_He/contributions

       

        Accepted/Online
        • Hongsheng Qi, Zhengbing He*, Road Intersection Optimization Considering Spatial-temporal Interactions among Turning Movement Spillovers, IEEE Transactions on Intelligent Transportation Systems, 10.1109/TITS.2020.3043274
        • Ying Lv, Shanshan Wang, Ziyou Gao, Guanhui Cheng, Guohe Huang, Zhengbing He*, A sustainable road pricing oriented bilevel optimization approach under multiple environmental uncertainties, International Journal of Sustainable Transportation, 10.1080/15568318.2020.1858374
        • Fang Zong, Zhengbing He*, Meng Zeng*, Yixuan Liu, Dynamic lane changing trajectory planning for CAV: A multi-agent model with path preplanning, Transportmetrica B, 10.1080/21680566.2021.1989079
        • Yang Yu, Zhengbing He, Xiaobo Qu, On the impact of prior experiences in car following models model development, computational efficiency, comparative analyses and extensive applications, IEEE Transactions on Cybernetics, 10.1109/TCYB.2021.3095154
        • Bo Fan, Yuan Wu, Zhengbing He, Yanyan Chen, Tony Q.S. Quek, Cheng-Zhong Xu, Digital Twin Empowered Mobile Edge Computing for Intelligent Vehicular Lane-Changing, IEEE Network, 10.1109/MNET.201.2000768
        • Jincai Huang, Yunfei Zhang, Min Deng, Zhengbing He, Mining crowdsourced trajectory and geo-tagged data for spatial-semantic road map construction, Transactions in GIS
        • Renxin Zhong, Zhengbing He, Andy Chow, Victor Knoop, Methodological Advancements in Understanding and Managing Urban Traffic Congestion, Transportmetrica A, 10.1080/23249935.2021.1894266
        • 宗芳，石佩鑫，王猛，贺正冰*，考虑前后多车的网联自动驾驶车辆混流跟驰模型，中国公路学报
        • 宗芳，李宇暄，贺正冰*，曾梦，基于混行跟驰仿真的CAV专用进口道动态设置方法，中国公路学报 
        • 宗芳，王猛，贺正冰*，考虑多车影响的分子动力学智能网联跟驰模型，交通运输系统工程与信息
        • 潘守政，何佳，王英平，贺正冰*，环线对地铁网络弹性的影响研究，交通运输工程与信息学报
        • 潘守政，何佳，王凤淇，贺正冰*，双车道异质交通波同步机理解析，公路交通科技
        •  
        2021
        • Zhengbing He*, Peng Chen*, Shared mobility: Characteristics, impacts, and improvements, Transportation Research Part D, 97:102960, 2021
        • Zhengbing He*, Portraying ride-hailing mobility using multi-day trip order data: A case study of Beijing, China, Transportation Research Part A, 146:152-169, 2021 (Open Accessed)
        • Haiyang Yu, Rui Jiang, Zhengbing He*, Zuduo Zheng*, Li Li*, Runkun Liu, Xiqun Chen, Automated Vehicle-involved Traffic Flow Studies A Survey of Assumptions, Models, Speculations, and Perspectives, Transportation Research Part C, 127:103101, 2021
        • Jie Xiong, Biao Chen, Zhengbing He*, Wei Guan, Yanyan Chen, Optimal design of community shuttles with an adaptive-operator-selection-based genetic algorithm, Transportation Research Part C, 126:103109, 2021
        • Liang Zheng, Chuang Zhu, Zhengbing He*, Tian He, Safety rule-based cellular automaton modeling and simulation under V2V environment, Transportmetrica A, 17(1): 81-106, 2021
        • Lili Lu, Zhengbing He, Jian Wang, Jufeng Chen, Wei Wang, Estimation of lane-level travel time distributions under a connected environment, Journal of Intelligent Transportation Systems, 25(5): 501-512, 2021
        • Shu-Qing Li, Yan-Yan Qin, Zhengbing He*, String stability analysis of connected vehicular systems based on car-following model, ASCE Journal of Transportation Engineering, Part A: Systems, 147(8): 04021038, 2021
        • Kunpeng Zhang, Zhengbing He, Liang Zheng, and Liang Zhao, A Generative Adversarial Network for travel times imputation using trajectory data, Computer-Aided Civil and Infrastructure Engineering, 36(2):197-212, 2021
        • Jinlei Zhang, Hongshu Che, Feng Chen, Wei Ma, Zhengbing He, Short-term prediction of urban rail transit origin-destination flow: A channel-wise attentive split-convolutional neural network method, Transportation Research Part C, 124:102928, 2021
        • Jian Wang, Lili Lu, Srinivas Peeta, Zhengbing He, Optimal toll design problems under mixed traffic flow of human-driven vehicles and connected and autonomous vehicles, Transportation Research Part C, 125:102952, 2021
        • Shouzheng Pan, Hai Yan, Jia He*, Zhengbing He, Vulnerability and resilience of transportation systems A recent literature review, Physica A, 581:126235, 2021
        • 贺正冰*，徐瑞康，谢东繁，宗芳，钟任新，数据驱动跟驰模型综述，交通运输系统工程与信息（20周年纪念特刊），21(5): 102-113，2021.
        • 齐航，夏嘉祺，王光超，贾宁，贺正冰，考虑出行者习惯与利他性偏好的自动驾驶网约车，交通运输工程与信息学报，19(2): 1-10, 2021
        • 习金浩，孟峰*，朱凤华，贺正冰，李润梅，吕宜生，基于多核自适应网络的高速公路交通流预测方法，交通运输研究，7(4):1-9, 2021
        • 李斌，姚恩建，贺正冰，杨敏，刘冬梅，张晓亮，郭宇奇，郭忠，于帅，京津冀城市群多模式客运枢纽 一体化运行关键技术研究，中国基础科学，23(02):23-33，2021
        2020
        • Zhengbing He, Wenyi Zhang, Ning Jia, Estimating carbon dioxide emissions of freeway traffic: a spatiotemporal cell-based model, IEEE Transactions on Intelligent Transportation Systems, 21(5):1976-1986, 2020
        • Zhengbing He*, Spatial-temporal fractal of urban agglomeration travel demand, Physica A, 549:124503, 2020
        • Zhengbing He, Cooperative driving and a lane change-free road transportation system, Chapter of IET Book  Traffic Information and Control, 2020
        • Ruimin Li, Zhengbing He, Traffic Information and Control, IET Book, https://digital-library.theiet.org/content/books/tr/pbtr026e
        • Li Li, Rui Jiang, Zhengbing He*, Xiqun Chen*, Xuesong Zhou*, Trajectory data-based traffic flow studies: A revisit, Transportation Research Part C, 114:225-240, 2020
        • Dong-Fan Xie, Yong-Qi Wen, Xiao-Mei Zhao, Xin-Gang Li, Zhengbing He*, Cooperative Driving Strategies of Connected Vehicles for Stabilizing Traffic Flow, Transportmetrica B, 8(1):166-181, 2020
        • Jia He, Zhengbing He*, Bo Fan, Yanyan Chen, Optimal location of lane-changing warning point in a two-lane road considering different traffic flows, Physica A, 540:123000, 2020
        • Fang Zong, Meng Zeng, Zhengbing He*, Yixin Yuan, Bus-car mode identification: A traffic condition-based random forests method, ASCE Journal of Transportation Engineering, Part A: Systems, 146(10): 04020113, 2020
        • Bingfeng Si, Zhengbing He*, Di Liu, Xiaobao Yang, Ziyou Gao. A train operation diagram-based equilibrium model for an urban rail transit network with transfer constraint. ASCE Journal of Transportation Engineering, Part A: Systems, 146(11): 04020126, 2020
        • YP Huang, JH Xiong, A Sumalee, N Zheng, WHK Lam, Zhengbing He, RX Zhong, A dynamic user equilibrium model for multi-region macroscopic fundamental diagram systems with time-varying delays, Transportation Research Part B, 131:1-25, 2020
        • Ximing Chang, Jianjun Wu, Zhengbing He, Daqing Li, Huijun Sun, Weiping Wang, Understanding user’s travel behavior and city region functions from station-free shared bike usage data, Transportation Research Part F, 72:81-95, 2020
        • Bo Fan, Zhengbing He, Yuan Wu, Jia He, Yanyan Chen, Li Jiang, Deep Learning Empowered Traffic Offloading Intelligent Software Defined Cellular V2X Networks, IEEE Transactions on Vehicular Technology, 69(11): 13328-13340, 2020
        • Bo Fan, Zhengbing He, Hui Tian, Dewen Kong, Yanyan Chen, Energy-efficient resource allocation for dynamic priority-based in-vehicle mobile-health communications, IEEE Systems Journal, 14(2):2097-2108, 2020
        • Jie Xiong, Biao Chen, Xiangnan Li, Zhengbing He, Yanyan Chen, Demand responsive service-based optimization on flexible routes and departure time of community shuttles, Sustainability, 12, 897, 2020
        • Guangchao Wang, Hang Qi, Ning Jia, Zhengbing He, A mixed behavior equilibrium model with mode choice and its application to the endogenous ratio of automated vehicles, 2020 Annual Meeting of Transportation Research Board.Washington DC, US.
        • 陈旭，陆丽丽，曹祖平，陈晨，贺正冰，叶晓飞，道路阻抗函数研究综述，交通运输研究，6(2):30-39，2020
        • 陈艳艳, 李同飞, 何佳, 杨洋, 孙浩冬, 贺正冰，新技术时代城市交通管理与服务研究发展展望，北京工业大学学报，46(6):621-629，2020
        2019
        • Zhengbing He, Geqi Qi, Lili Lu, Yanyan Chen, Network-wide identification of turn-level intersection congestion using only low-frequency probe vehicle data, Transportation Research Part C, 108:320-339, 2019
        • Dongfan Xie, Zhe-Zhe Fang, Bin Jia, Zhengbing He*, A data-driven lane-changing model based on deep learning, Transportation Research Part C, 106:41-60, 2019
        • Zhengbing He, Ying Lv, Lili Lu, Wei Guan, Constructing spatiotemporal speed contour diagrams: using rectangular or non-rectangular parallelogram cells, Transportmetrica B, 7(1):44-60, 2019
        • Zhengbing He, Jia Hu, Brian Park, Michael Levin, Vehicle Sensor Data-based Transportation Research: Modeling, Analysis, and Management, Journal of Intelligent Transportation Systems, 23(2):99-102, 2019
        • Dongfan Xie, Xiaomei Zhao, Zhengbing He*, Heterogeneous traffic mixing regular and connected vehicles: Modelling and stabilization, IEEE Transactions on Intelligent Transportation Systems, 20(6):2060-2071, 2019
        • Zhengbing He, Six Questions on Network-wide Traffic Prediction. DOI: 10.13140/RG.2.2.10498.63681, 2019.9 (Download)
        • Liang Zheng, Chuang Zhu, Zhengbing He*, Tian He, Sisi Liu, Empirical validation of vehicle type-dependent car-following heterogeneity from micro- and macro-viewpoints, Transportmetrica B, 7(1):765-787, 2019
        • Lishan Liu, Ning Jia, Lei Lin, Zhengbing He*, A cohesion-based heuristic feature selection for short-term traffic forecasting, IEEE Access, 7:3383-3389, 2019
        • Geqi Qi, Wei Guan, Zhengbing He, Ailing Huang, Adaptive kernel fuzzy C-Means clustering algorithm based on cluster structure, Journal of Intelligent and Fuzzy Systems, 37(2): 2453-2471, 2019
        • 马晓威，范博，何佳，陈艳艳，贺正冰，基于车路协同多业务优先级的车载通信退避算法，交通运输研究，5(4):76-88，2019
        • Ximing Chang, Jianjun Wu, Zhengbing He, Daqing Li, Huijun Sun, Kangli Zhu, Understanding user's travel behavior and city region functions from station-free sharing bike usage data (Outstanding Paper), The 7th International Conference on Transportation and Space-time Economics, Beijing, China, October 11-13, 2019
        2018
        • Lei Lin, Zhengbing He, Srinivas Peeta, Predicting Station-level Hourly Demand in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approach, Transportation Research Part C, 97:258-276, 2018
        • Zhengbing He, Liang Zheng, Lili Lu, Wei Guan, Erasing lane changes from roads: A design of future intersections, IEEE Transactions on Intelligent Vehicles, 3(2):173-184, 2018
        • Lili Lu, Jian Wang, Zhengbing He*, Ching-yao Chan, Real-time estimation of freeway travel time with recurrent congestion based on sparse detector data. IET Intelligent Transport Systems. 12(1):2-11, 2018
        • Wenyi Zhang, Zhengbing He*, Wei Guan, Geqi Qi, Day-to-day rerouting modeling and analysis with absolute and relative bounded rationalities, Transportmetrica A. 14(3):256-273, 2018
        • Liu Yang, Zhengbing He, Wei Guan*, Shixiong Jiang, Exploring the relationship between EGG and ordinary driving behavior: A simulated driving study. Journal of Transportation Research Board, 2018
        • Jianmei Liu, Zhengbing He*, Shuaiqi Ma, An N-path logit-based stochastic user equilibrium model, IEEE Access, 6(1):20971-20986, 2018
        • Shixiong Jiang, Wei Guan, Zhengbing He, Liu Yang, Exploring the inter-modal relationship between taxi and subway in Beijing, China, Journal of Advanced Transportation, 3981845, 2018
        • Shixiong Jiang, Wei Guan, Zhengbing He, Liu Yang, Measuring Taxi Accessibility Using Grid-based Method with Trajectory, Sustainability,10, 3187, 2018
        • 金盛，沈莉潇 ，贺正冰*，基于多源数据融合的城市道路网络宏观基本图模型，交通运输系统工程与信息，18(2):108-115，2018
        • Jingyi Hao, Zhengbing He*. A day-to-day invariant macroscopic fundamental diagrams for probe vehicles, 2018 International Conference on Traffic Engineering and Transportation System. Shenzhen, China, 2018
        • Liu Yang, Zhengbing He, Wei Guan, Shixiong Jiang, Exploring the relationship between EEG and ordinary driving behavior: A simulated driving study. 2018 Annual Meeting of Transportation Research Board, Washington DC, US.
        2017
        • Zhengbing He, Zheng Liang, Peng Chen, Wei Guan, Mapping to cells: a simple method to extract traffic dynamics from probe vehicle data, Computer-Aided Civil and Infrastructure Engineering. 32(3):252-267, 2017
        • Zhengbing He, Liang Zheng, Liying Song, Ning Zhu, A jam-absorption driving strategy for mitigating traffic oscillations, IEEE Transactions on Intelligent Transportation Systems, 18(4):802-813, 2017
        • Liang Zheng, Zhengbing He*, Tian He, A flexible traffic stream model and its three representations of traffic flow, Transportation Research Part C, 75:136-167, 2017
        • Ning Jia, Yidan Zhao, Zhengbing He*, Geng Li, Commuters' acceptance of and behavior reactions to license plate restriction policy: A case study of Tianjin, China, Transportation Research Part D. 52:428–440, 2017
        • Zhengbing He, Liang Zheng, Visualizing traffic dynamics based on floating car data, ASCE Journal of Transportation Engineering, 143:5, 2017
        • Zhengbing He, Research based on high-fidelity NGSIM vehicle trajectory datasets: A review. DOI: 10.13140/RG.2.2.11429.60643, 2017 (Download)
        • Liang Zheng, Zhengbing He*, An anisotropic continuum model and its calibration with an improved monkey algorithm, Transportmetrica A, 13(6):519-543, 2017
        • Bingfeng Si, Zhengbing He*, Xiaobao Yang, Ziyou Gao, Data-based sorting algorithm for variable message sign location, Journal of Transportation Research Board, 2645:86-93, 2017
        • Zhihao Zhang, Yunpeng Wang, Peng Chen, Zhengbing He, Guizhen Yu, Probe data-driven travel time forecasting for urban expressways by matching similar spatiotemporal traffic patterns. Transportation Research Part C. 85:476-493, 2017
        • Ailing Huang, Guangzhi Zang, Zhengbing He*, Wei Guan, Comparative empirical analysis of five-weighted transit route network in R-space and evolution modeling, International Journal of Modern Physics B. 31(12):1750087, 2017
        • Xiaolei Ma, Zhuang Dai, Zhengbing He, Jihui Ma, Yong Wang, Yunpeng Wang. Learning traffic as images: A deep convolutional neural network for large-scale transportation network speed prediction, Sensors, 17(4):818, 2017
        • Wenyi Zhang, Zhengbing He*, Wei Guan, Rui Ma, Selfish routing equilibrium in stochastic traffic network: A probability-dominant description, PLoS ONE, 12(8): e0183135, 2017
        • Sai Shao, Wei Guan, Bin Ran, Zhengbing He, Jun Bi, Electric Vehicle Routing Problem with Charging Time and Variable Travel Time, Mathematical Problems in Engineering, 5098183, 2017
        • Lili Lu, Jian Wang, Zhengbing He*, Ching-Yao Chan, Real-time estimation of freeway travel time with sparse detector data, 2017 Annual Meeting of Transportation Research Board, Washington DC, US.
        • Zhihao Zhang, Yunpeng Wang, Peng Chen, Zhengbing He, Guizhen Yu, Prediction of Urban Expressway Travel Time through Matching Similar Spatiotemporal Traffic Patterns, 2017 Annual Meeting of Transportation Research Board, Washington DC, US.
        2016
        • Zhengbing He, Liang Zheng, Wei Guan, Baohua Mao. A self-regulation traffic-condition-based route guidance strategy with realistic considerations: overlapping routes, stochastic traffic and signalized intersections, Journal of Intelligent Transportation Systems, 20 (6): 545-558, 2016
        • Zhengbing He, Wei Guan, Wenyi Zhang, Effectiveness of GRIPs in alleviating traffic congestion, Proceedings of ICE-Transport, 169 (TR3):125-137, 2016
        • Dongfang Ma, Fengjie Fu, Sheng Jin, Zhengbing He, Fujian Wang, Weiming Zhao, Dianhai Wang, Gating control for a single bottleneck link based on traffic load equilibrium, International Journal of Civil Engineering, 14(5), 2016
        • Liying Song, Dong Yang, Anthony Theng Heng Chin, Guangzhi Zhang, Zhengbing He, Wei Guan, Baohua Mao, A game-theoretical approach for modeling competitions in a maritime supply chain, Maritime Policy & Management, 43(8):976991, 2016
        2015
        • Zhengbing He, Liang Zheng, Wei Guan, A simple nonparametric car-following model driven by field data. Transportation Research Part B, 80:185-201, 2015
        • Liang Zheng, Zhengbing He*, A new car-following model from the perspective of visual imaging. International Journal of Modern Physics C, 26(8), 1550090, 2015
        • Jie Xiong, Zhengbing He, Wei Guan, Bin Ran, Optimal timetable development for community shuttle network with metro stations. Transportation Research Part C, 60:540-565, 2015
        • Zhengbing He, Shuyan He, Wei Guan, A figure-eight hysteresis pattern in macroscopic fundamental diagrams and its microscopic causes. Transportation Letters, 7(3):133-142, 2015
        • Zhengbing He, Liang Zheng, Liying Song, Wei Guan, Jam-absorption driving strategy for mitigating traffic oscillations, 2016 Annual Meeting of Transportation Research Board, Washington DC.
        • Zhengbing He, Ailing Huang, Dongfang Ma, Ning Zhu. A discrete-flow form of the point-queue model, IEEE International Transportation Conference, 2015, Spain.
        2014
        • Zhengbing He, Bokui Chen, Wei Guan, et al., Route guidance strategies revisited: Comparison and evaluation in an asymmetric two-route traffic system. International Journal of Modern Physics C, 25(4):1450005, 2014
        • Ning Zhu, Yang Liu, Shoufeng Ma, Zhengbing He, Mobile traffic sensor routing in dynamic transportation systems. IEEE Transactions on Intelligent Transportation Systems, 15(5):2273-2285, 2014
        • 贺正冰, 关伟*, 樊玲玲, 关积珍，北京市快速环路宏观基本图特征研究，交通运输系统工程与信息，14(2):199-205，2014
        • Zhengbing He, Liu Yang, Wei Guan. A day-to-day route choice model based on travelers' behavioral characteristics, 9th International Conference of Traffic and Transportation Studies, Shaoxing, 2014.
        2013
        • Zhengbing He, Wei Guan, Shoufeng Ma. A traffic-condition-based route guidance strategy for a single destination road network. Transportation Research Part C, 32: 89-102, 2013
        • Zhengbing He, Soufeng Ma, Wei Guan, Delays caused by motorized vehicles unable to clear intersections in China: Graphical analysis. Journal of Central South University, 20(9):2614-2624, 2013
        • 贺正冰, 关伟，面向长周期的交通状态反馈诱导策略，控制与决策，28(7):1046-1050，2013
        • 贺正冰, 关伟，考虑信号交叉口影响的分散路径诱导策略，北京工业大学学报，39(10):1539-1544，2013
        • Weiyi Zhang, Zhengbing He, Wei Guan. Nonlinear pairwise adjustment dynamic model accounting for traveler's bounded rationality. 18th International Conference of Hong Kong Society for Transportation Studies (HKSTS), 2013, Hong Kong
        • Zhengbing He, Shuyan He, Wei Guan, A figure-eight hysteresis pattern in macroscopic fundamental diagrams for an urban freeway network in Beijing, China, 92nd Annual Meeting of Transportation Research Board. 2013.
        < 2012
        • Jorge Laval, Zhengbing He, Felipe Castrillon. A stochastic extension of Newell’s “three-detector method". Journal of Transportation Research Board, 2315: 73-80, 2012
        • Zhengbing He, Shoufeng Ma, Xiting Tang. Empirical study on the influence of learning ability to individual travel Behavior, Journal of Transportation Systems Engineering and Information Technology, 9(2):75-80, 2009
        • 贺正冰, 马寿峰, 贺国光，基于仿真实验的城市交通系统宏观现象研究，物理学报，59(1):171-177，2010
        • 马寿峰, 贺正冰*, 张思伟，基于风险的交通网络可靠性分析方法，系统工程理论与实践，30(3):550-556，2010
        • 刘建美, 马寿峰, 贺正冰, 贾宁，控制与诱导的协调中路网拥堵状态识别方法，管理科学学报，13(11):35-40，2010
        • Zhengbing He, Ailing Huang. Approximating the minimum distribution of two normally distributed variables each with the same mean and variance. Fifth International Joint Conference on Computational Sciences and Optimization, 2012
        • Zhengbing He, Shoufeng Ma, Introduction to applications of swarm in transportation research, Fourth International Joint Conference on Computational Sciences and Optimization, 2011

      • 重要成果简介

        大数据：网约车出行特征

        Zhengbing He, Portraying ride-hailing mobility using multi-day trip order data: A case study of Beijing, China, Transportation Research Part A, 146:152-169, 2021

        基于多天数据的网约车画像：以北京为例，深度挖掘多天网约车订单数据，从区域出行需求以及网约车司机服务选择两个角度对网约车出行进行画像，发现了一系列重要的特征与规律，包括城市使用网约车的时空韵律、网约车出行分布、网约车司机提供服务的时空特征、网约车司机分类等。成果对理解基于网约车的出行活动、预测网约车需求、网约策司机特征建模、网约车管理等具有重要意义。

                

        大数据：城市路网监测

        Zhengbing He, Geqi Qi, Lili Lu, Yanyan Chen, Network-wide Identification of Turn-level Intersection Congestion Using Only Low-frequency Probe Vehicle Data, Transportation Research Part C, 108 (2019) 320-339, 2019

        基于浮动车大数据的路网交叉口状态快速检测：首先将城市空间分格，利用道路交叉口前通常存在大量走走停停交通流的特征，通过空间聚类，重构易发生拥堵的道路交叉口。通过浮动车轨迹与网格的映射（与交叉口的匹配），识别转弯方向车辆轨迹，并提取交通状态信息，实现路网交叉口转弯方向交通拥堵的快速诊断，辅助城市交通管理部门进行堵点定位。该方法具有简单、快速、无须GIS地图等特点，适用于大数据条件下对交通拥堵的快速识别需求，以及信控公司、交管部门等的前期市场调研。

                

        大数据：高速公路监测

        Zhengbing He, Zheng Liang, Peng Chen, Wei Guan, Mapping to cells: a simple method to extract traffic dynamics from probe vehicle data, Computer-Aided Civil and Infrastructure Engineering. 32(3):252–267, 2017

        基于浮动车大数据的快速路网状态快速检测：首先将城市空间分格，然后通过浮动车轨迹选取、构造对应于实际快速路/高速公路网络的格子网络，并据此构造交通拥堵时空图，进而识别拥堵的时空特征。该方法具有简单、快速、无须GIS地图等特点，适用于大数据条件下对交通拥堵的快速识别需求。

                

        大数据：交通时空图

        Zhengbing He, Ying Lv, Lili Lu, Wei Guan, Constructing spatiotemporal speed contour diagrams: using rectangular or non-rectangular parallelogram cells? Transportmetrica B: Transport Dynamics, 7(1):44-60, 2019

        考虑交通波速度的交通时空图构造方法：交通（速度）时空图是进行拥堵分析与瓶颈识别时基础且重要的可视化工具。一般以矩形格子为基本单元进行时空图的构造。该研究通过一系列实证分析发现：以平行于交通波方向的平行四边形为基本单元构造交通时空图，可以更准确地还原交通流时空动态特征。由于交通时空图的重要性，该成果的实际应用前景及影响非常可观。

                

        数据驱动交通流：跟驰

        Zhengbing He, Liang Zheng, Wei Guan, A simple nonparametric car-following model driven by field data. Transportation Research Part B. 80:185-201, 2015

        非参数跟驰模型：传统交通流模型，均使用数学公式描述车辆的行驶过程。本研究，创造性地直接从车辆轨迹数据库中提取典型驾驶行为，通过搜索历史数据库、匹配相似驾驶场景，得到最可能的驾驶行为，作为模型输出；最终构造完全由数据驱动的车辆跟驰模型。该模型的特点如下：

        • 简单，没有数学公式，只有一个参数 k 
        • 无需要任何标定（基本图或者驾驶行为参数）
        • 离散的输入和输出，适合仿真应用
        • 可以还原数据库中包括的主要宏观交通特征，如：走走停停波、基本图

                

        数据驱动交通流：换道

        Dongfan Xie, Zhe-Zhe Fang, Bin Jia, Zhengbing He*, A data-driven lane-changing model based on deep learning, Transportation Research Part C, 106(2019): 41-60, 2019

        深度学习换道模型：换道是最基础、最重要的车辆行为之一。因此，车辆换道模型也是最重要的交通流模型之一。传统基于数学的方法较难准确刻画涉及变量众多的车辆换道过程。因此，本文应用深度学习技术，分别构造了基于Deep Belief Network和Long Short-Term Memory的车辆换道决策模型与车辆换道过程模型。实验结果不但说明了该模型的高准确性，同时发现了：“目标车道上前车的位置”是影响车辆换道决策的最重要变量。

                

        自动驾驶与车联网：无换道交通系统

        Zhengbing He, Lili Lu, Liang Zheng, Wei Guan, Erasing lane changes from roads: A design of future intersections, IEEE Transactions on Intelligent Vehicles, 3(2):173-184, 2018

        无换道协同交叉口：在未来，当无人驾驶实现后，信号灯将不再是交叉口控制的主要方式；取而代之的可能是车辆间自行协调路权，实现交叉口内的完美“擦肩而过”，即自动交叉口。本文创新性地提出了一种不带转向车道的自动交叉口，即车辆在左转车道上亦可进行右转。未来车辆在这样的路网中行驶，不需要任何换道行为，便可到达目的地。提高效率与安全的同时，有可能（因为不再需要自动换道模型）大大简化自动驾驶技术。 论文不只有苟且，还有诗和远方。致敬《星球大战》！

        入匝道

        出匝道

                

        自动驾驶与车联网：缓堵

        Zhengbing He, Liang Zheng, Liying Song, Ning Zhu, A jam-absorption driving strategy for mitigating traffic oscillations, IEEE Transactions on Intelligent Transportation Systems

        吸收交通波驾驶策略：传统缓解交通拥堵的手段主要有匝道控制、交通诱导、可变限速以及需求管理，鲜有新技术与新方法的突破。本研究为了缓解交通拥堵，让车辆反其道而行之，即有目的的引导车辆在到达拥堵点前，慢速行驶，以阻止高密度交通波的传播，为缓解交通拥堵，提供了全新的思路。

                

        自动驾驶与车联网：混合交通流

        Dongfan Xie, Xiaomei Zhao, Zhengbing He*, Heterogeneous Traffic Mixing Regular and Connected Vehicles: Modelling and Stabilization, IEEE Transactions on Intelligent Transportation Systems, 20(6):2060-2071, 2019

        人驾/机驾混合交通流稳定性与驾驶策略：不难想象，未来几年，装有辅助驾驶系统的智能车辆或者辆联网车辆将大量出现在我们的身边。在这样的背景下，本文首先根据联网车辆的特点建立了联网车辆与常规车辆统一跟驰模型，随后通过系统的模型分析，研究联网车辆对交通流稳定性和系统效率的影响。在此基础上，设计了自动控制器（辅助驾驶系统ADAS），通过应用控制器，有效地保持了交通流的快速稳定。

                

        路径诱导策略

        Zhengbing He, Wei Guan, Shoufeng Ma. A traffic-condition-based route guidance strategy for a single destination road network. Transportation Research Part C, 32:89-102, 2013


        Zhengbing He, Liang Zheng, Wei Guan, Baohua Mao. A self-regulation traffic-condition-based route guidance strategy with realistic considerations: overlapping routes, stochastic traffic and signalized intersections, Journal of Intelligent Transportation Systems, 20 (6):545-558, 2016.

        基于交通状态的路径诱导策略：可变交通信息板是发布路况信息的重要渠道。但受限于城市道路的复杂的拓扑结构，目前的信息发布策略仍无法有效准确的传递令人满意的交通信息。针对该现状，本研究提出了基于交通状态（拥堵程度，而非行驶时间）的路径诱导策略，以满足目前只能发布有限种路段交通状态的可变交通诱导信息板的实际需求。

                

        可持续发展交通：排放模型

        Zhengbing He, Wenyi Zhang, Ning Jia, Estimating Carbon Dioxide Emissions of Freeway Traffic: A Spatiotemporal Cell-based Model, IEEE Transactions on Intelligent Transportation Systems, Accepted 2019

        中观交通排放模型：现有交通排放估计模型主要分为两类：基于车的微观排放模型（对数据精度要求高，数据采集难度大）及基于交通指数的宏观模型（未考虑细节交通动态，所以估计精度差）。因此，本研究提出了一种介于两者之间的基于交通时空图的中观交通（二氧化碳）排放估计模型。该模型可以给出交通时空图对应的交通二氧化碳排放，不但很好的考虑了交通流动态性而且具有输入数据易获得的优点。由于各种数据（如路侧检测器、浮动车数据）均可用于交通时空图的构造，因此，可以说：本研究提出的基于交通时空图的交通排放估计模型打开了一扇从各种数据去估计交通排放的“门”，具有重要的实践意义。

                

        可持续发展交通：车辆尾号限号

        Ning Jia, Yidan Zhao, Zhengbing He*, Geng Li, Commuters' acceptance of and behavior reactions to license plate restriction policy: A case study of Tianjin, China, Transportation Research Part D, 52:428–440, 2017

        居民对车辆尾号限号政策态度：以天津市为例，在实行限号措施数月后，发放1000份问卷，调查市民对该措施的态度。通过实证分析，说明了公众接受度对限号政策效果的重要作用，发现了影响该接受度的重要因素，为政策制定者和设计者提供了重要的实证依据与建议

      • 科研项目

        • 国家重点研发计划课题，2018YFB1601302，基于移动互联和广域大数据的城市群客运出行辨识与枢纽群布局技术，2019/03-2021/12，748万，在研，主持
        • 国家重点研发计划子课题，2018YFB1600505-1，车路协同环境下面向仿真的通用驾驶人模型，2019/03-2022/12，64万，在研，主持
        • 国家自然科学基金“面上”项目，71871010，数据驱动的城市路网交通状态时空自推演模型，2019/01-2022/12，48万，在研，主持
        • 国家自然科学基金“青年”项目，71501009，基于宏观基本图的大城市区域路径诱导策略研究，2016/01-2018/12，17.4万，已结题，主持
        • 北京工业大学高层次人才（优秀人才）项目，2018-2022，100万，在研，主持
        • 中央高校基本科研（国际合作类），数据驱动的交通系统建模，2019/04-2019/12，6万，在研，主持
        • 广东省智能交通系统重点实验室开放课题，201807001，城市交通拥堵复杂性理论研究，2019/01-2019/12，5万，在研，主持
        • 公安部重点实验室开放课题，2017KFKT06，基于浮动车大数据的城市道路交叉口重构与拥堵识别方法，2018/01-2018/12，2万，在研，主持
        • 中央高校基本科研业务费，T17JB00090，数据驱动的城市路网交通流建模，2017/01-2018/6，7.5万，已结题，主持
        • 北京交通大学人才基金，T15RC00020，主辅路交通系统中出入口信号协同控制研究，2015/01-2016/12，10万，已结题，主持
        • 中央高校基本科研业务费，2012JBM064，宏观基本图理论研究－以北京市为例，2012/01-2013/12，8万，已结题，主持
        • 重大研究计划“重点支持”项目，91746201，大数据驱动的城市群交通状态感知、态势推演与智慧决策，2018/01-2020/12，240万，在研，参加
        • 国家自然科学基金“创新群体”项目，71621001，城市交通管理理论与方法，2017/01-2022/12，700万，在研，参加
        • 国家自然科学基金“面上”项目，71671014，基于多源数据的区域化交通拥堵演化规律及其影响机理研究，2017/01-2020/12，48万，在研，参加
        • 国家自然科学基金“面上”项目，71471014，融入驾驶人感知的交通流建模方法研究，2015/01-2018/12，64万，已结题，参加
        • 北京市科委项目，Z131110002813118，基于大数据的交通计算若干问题研究，2013/11-2014/10，50万，已结题，参加
        • 科技部"863"计划主题项目，2011AA110303，大城市区域交通协同联动控制关键技术，2011/01-2013/12，5400万，已结题，参加
        • 等等

        教学工作

        • 本科生：交通流理论（双语），交通运输自动控制原理，系统工程，交通信息服务系统设计与开发，智能运输专业认知实习
        • 研究生：专业外语，交通系统分析（教育部课程试点精品课程项目）

        发明专利

        • 贺正冰、陆丽丽、奇格奇、陈艳艳，基于浮动车数据网格映射的城市路网交叉口拥堵识别方法，专利号：ZL 2018 1 0484715.7
        • 陆丽丽、贺正冰、郑彭军，基于车联网的城市干道车辆行程时间实时预测方法，专利号：ZL 2016 1 0984806.8

        奖励

        • 2021年，中国智能交通协会-优秀科技创新领军人才
        • 2020年，交通运输部-青年科技英才
        • 2020年，中国公路学会-科学技术奖，多模式交通出行行为全息感知与一体化服务引导关键技术及应用，二等奖，排名：2/10
        • 2019年，中国智能交通协会-科学技术奖，数据碎片化环境下的综合交通运输服务集成与协同优化关键技术，二等奖，排名：9/10
        • 2018年，中国智能交通协会-科学技术奖，大数据驱动的多层级需求主动引导关键技术，二等奖，排名：2/15
        • 北京工业大学 高层次人才（优秀人才）
        • 2017年，“城市交通管理理论与方法” 国家自然科学基金创新群体（71621001）优秀个人
        • 2014年，北京交通大学交通运输学院，系统工程与控制研究所，优秀教师
        • Outstanding Associate Editor (前5%), IEEE Access
        • Outstanding Reviewer (前10%), Transportation Research Part A
        • Outstanding Reviewer (前10%), Transportation Research Part C
        • Outstanding Reviewer (前10%), Transportation Research Part D
        • Outstanding Reviewer (每年推荐3人), ASCE Journal of Transportation Engineering

        写在最后

        我的研究方向比较多元和交叉，大体可以概括为：站在交通流理论上，交通流理论是我工作的重要基础，保证了各种研究的理论性与正统出身；以城市拥堵为研究对象，主要关注与城市拥堵直接关联的问题，比如瓶颈、出行时间、交通流特征等，偶尔扯一下间接相关的环境污染与驾驶安全等；左手做智能网联与无人驾驶，入行之初，重点关注的就是车、驾驶行为以及交通流特征，自然向新技术靠拢，也在这个方向上已经取得了一定成果，这是持续关注的研究方向；右手做交通大数据与城市活动性，现今丰富的数据资源也触动了我的神经，2015年以来，做了不少浮动车数据相关的研究，也积累的一定的经验，期望在未来一段时间，通过引入复杂网络等方法与理论走向更综合的研究领域。

      京公网安备 11010502041811号 | 京ICP备20024789号

      京ICP备20024789号-1
        Cookie的使用
        我们使用cookies来确保流畅的浏览体验。若继续，我们认为你接受使用cookies。
        了解更多