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  • 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

    Research Interests

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

    Academic Service

    • Transportation Research Part C: Emerging Technologies, Editorial Advisory Board member
    • IET Intelligent Transport Systems, Associate Editor
    • IEEE Access, Associate Editor (2017.10-2019.10), Outstanding Award (top 5%)
    • IEEE, Senior Member
    • 2020 IEEE 5th International Conference on Intelligent Transportation Engineering, Beijing, China, Award Chair
    • 2020 Forum on Integrated and Sustainable Transportation Systems, Delft, The Netherlands, Associate Editor
    • 2020, 23rd IEEE Intelligent Transportation Systems Conference, Rhodes, Greece, Associate Editor
    • 2019, 22nd IEEE Intelligent Transportation Systems Conference, Auckland, New Zeland, Associate Editor
    • 2018, 21st IEEE Intelligent Transportation Systems Conference, Hawaii, United States, Session Chair, Special Session on Fighting Traffic Congestion: China's Experience and Lessons in ITS
    • 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
    • 《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
    • 《交通与数据科学丛书》,编委
    • 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
    • 第十三届中国智能交通年会,天津,2018.11,学术委员会委员
    • 第十一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/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

    • 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
    • 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
    • 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 B,
    • Transportation Research Part C, 
    • 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,
    • IEEE Access,
    • Physica A: Statistical Mechanics and its Applications,
    • International Journal of Modern Physics B,
    • International Journal of Modern Physics C, 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

     

    Papers not Intended to Publish in Journals

    • Zhengbing He, Six Questions on Network-wide Traffic Prediction. DOI: 10.13140/RG.2.2.10498.63681, 2019.9 (Download)
    • Zhengbing He, Research based on high-fidelity NGSIM vehicle trajectory datasets: A review. DOI: 10.13140/RG.2.2.11429.60643, 2017 (Download)
    Online
    • Zhengbing He, Portraying ride-hailing mobility using multi-day trip order data: A case study of Beijing, China, arXiv:2006.12937
    • Liang Zheng, Chuang Zhu, Zhengbing He*, Tian He, Safety rule-based cellular automaton modeling and simulation under V2V environment, Transportmetrica A
    • 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
    • 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
    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
    • Li Li, Rui Jiang, Zhengbing He*, Xiqun Chen, Xuesong Zhou, Trajectory data-based traffic flow studies: A revisit, Transportation Research Part C, 114 (2020):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
    • 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, 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, 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 (2019) 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(2019): 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
    • 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),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, 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, 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
    • 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: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》!
     

            

    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,2018YFB1600500-5,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

    • 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,申请/专利号:ZL 2016 1 0984806.8
    • 陆丽丽、贺正冰、郑彭军,基于稀疏检测器的行程时间实施估计方法,申请/专利号:201610984806.8
    • 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,申请/专利号:201810484715.7

    奖励

    • 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

    最近(2019年)连续搞了三个Special Issues,着实火了一把。不过也有人问我:“你究竟是做什么方向的?”
    其实吧,我想做的是:以城市拥堵为研究对象,站在交通流理论上,左手做智能网联与无人驾驶,右手做交通大数据与城市活动性。
    因此,这三个Special Issues和我的研究方向都紧密相关。具体如

    • 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。所以有了这个Special Issue: Methodological Advancements in Understanding and Managing Urban Traffic Congestion (Transportmetrica A)
    • 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,现在也算有稳定的伙伴一起搞(比如郑亮、谢东繁、陆丽丽)。所以有了这个Special Issue:智能网联交通流专刊 (中国公路学报)
    • 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,但是还期望在未来一段时间,自己的工作中心在这上,并且通过引入复杂网络等方法与理论走向更一般的领域。目前每天搞的就是这些,天天拽着孙立君和闫小勇问问题 ;) 聊着聊着,就有了这个Special Issue:Emerging Methods for Data-driven Urban Transportation and Mobility Modeling: Machine Learning and Complexity Approaches (Transportation Research Part C)