个人简历

教育经历\r
1992.9 -- 1996.7 哈尔滨工业大学 内燃机 本科 学士学位\r
1998.9 -- 2004.3 吉林大学 载运工具运用工程 硕士研究生毕业 硕士学位\r
2001.9 -- 2004.6 吉林大学 载运工具运用工程 博士研究生毕业 博士学位\r
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工作经历\r
2006.9 -- 至今 北京航空航天大学 交通科学与工程学院 讲师、副教授、教授\r
2004.10 -- 2006.9 清华大学 汽车工程系 博士后\r
1996.7 -- 2006.5 昆明理工大学 交通工程学院 助教、讲师、副教授

研究领域

"不断改善安全、提高出行效率、节约能源消耗、降低交通对环境的影响是交通科学与工程技术发展的动力。从信息化到智能化是解决一系列交通问题的有效途径。我们重点围绕交通安全改善与效率提升这两大主题，以深入的数据分析和智能化技术为手段，在驾驶行为、车路协同等方面开展深入研究。\r
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一、驾驶行为建模\r
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以风险动态平衡理论和行为补偿理论为基础，研究驾驶人的驾驶行为特征及行为建模。主要的学术贡献包括：提出了一个描述驾驶人跟驰过程的主观危险感量化指标（安全裕度，SM）并建立了基于主观危险感行为补充的跟驰模型（期望安全裕度模型，DSM），可用于异质性、随机性跟驰行为的量化分析，拟人化（个性化）的ACC控制等；提出了一种行车过程的风险场统一量化方法，可以用于不同行车场景下的风险统一量化，行车安全预警与自动驾驶轨迹规划等；发现了交叉口闯黄灯数量与交通量的非线性关系；发现了交叉口冲突车辆先行/让行的主要影响因素及让行/先行决策规律；解释了信号交叉口通行黄灯决策的心理机制。\r
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二、协同控制优化\r
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对智能网联汽车的通行控制，在国内最早在实车上实现了基于车车通信的车辆运动协同控制（2013年），提出了一种从单交叉口到路网的智能网联汽车协同控制方法。\r
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三、自动驾驶接管\r
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针对L3级自动驾驶汽车接管过程，从接管的安全性、稳定性、及时性方面开展研究。主要的学术成果包括：把信任问题引入接管过程分析，系统分析了接管行为特征及信任度对接管行为的影响；对影响接管安全性、稳定性、及时性的因素进行了系统分析；系统分析了自动驾驶专用车道对临近车道车辆行为的影响。\r
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四、交通安全、交通状态与交通可靠性\r
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对交通安全状态、交通运行状态和交通可靠性的预测开展了研究。主要的学术成果包括：提出了交通冲突和交通事故的非线性关系模型；提出了考虑上下游交通状态关联性的交通状态预测方法；提出了不同服务水平交互作用下的城市主干路出行时间可靠性计算模型。\r
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五、科技发展战略"

近期论文

Effects of assignments of dedicated automated vehicle lanes and inter-vehicle distances of automated vehicle platoons on car-following performance of nearby manual vehicle drivers:ACCIDENT ANALYSIS AND PREVENTION,2022,177:106826\r
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Modeling and simulation of approaching behaviors to signalized intersections based on risk quantification:Transportation Research Part C,2022,142:103773\r
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Risk Field Model of Driving and Its Application in Modeling Car-Following Behavior.[期刊]:IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2021\r
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Modeling takeover behavior in level 3 automated driving via a structural equation model: Considering the mediating role of trust:Accident Analysis and Prevention,2021,157\r
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Measuring drivers’ takeover performance in varying levels of automation: Considering the influence of cognitive secondary task:Transportation Research Part F: Psychology and Behaviour,2021,82:96–110\r
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Are novice drivers competent to take over control from level 3 automated vehicles? A comparative study with experienced drivers:Transportation Research Part F,2021(81):65–81\r
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道路交通安全（教材）.北京:人民交通出版社,2018\r
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车车协同安全控制技术（专著）:科学出版社,2014\r
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车用安全通信-协议、安全及隐私（译著）.[专著]:北京理工大学出版社,2015\r
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城市交通系统运行可靠性分析方法（专著）.[专著].北京:人民交通出版社,2017\r
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智能交通技术概论（教材）.[专著]:清华大学出版社,2020\r
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交通运输系统的可靠性与安全性（译著）.[专著]:机械工业出版社,2018\r
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交通强国战略研究（第二卷）（参编）:人民交通出版社,2019\r
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中国工程科技2035发展战略研究——技术路线图卷（一）（参编）:中国工信出版集团、电子工业出版社,2020\r
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中国工程科技2035发展战略：机械与运载领域报告（参编）:科学出版社,2019\r
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中国工程科技2035发展战略：公共安全领域报告（参编）:科学出版社,2020\r
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Quantitative indicator of homeostatic risk perception in car following.:Safety science,2012,50(9):1898-1905\r
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Analysis of yellow-light running at signalized intersections using high-resolution traffic data.:Transportation research part A: policy and practic,2015,73:39-52\r
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Cooperative autonomous traffic organization method for connected automated vehicles in multi-intersection road networks.[期刊]:Transportation Research Part C-Emerging Technologies,2020,111:458-476\r
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Impact of heterogeneity of car-following behavior on rear-end crash risk.[期刊]:Accident Analysis and Prevention,2019,125:275-289\r
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Tunable and Transferable RBF Model for Short-Term Traffic Forecasting:IEEE Transactions on Intelligent Transportation Systems\r
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自动驾驶中视觉次任务对年轻驾驶人接管时间的影响.[期刊].中国：西安:中国公路学报,2018,31(4):165-171\r
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Influence of Driving Behaviors on the Stability in Car Following.[期刊]:IEEE Transactions on Intelligent Transportation Systems,2019,20(3):1081-1098\r
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A New Control Strategy Integrated into the Desired Safety Margin Car-Following Model Considering the Disturbance Level.[期刊]:Transportation Research Record,2018\r
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Extended Desired Safety Margin Car-Following Model That Considers Variation of Historical Perceived Risk and Acceptable Risk.[期刊]:Transportation Research Record,2018,2018(0361198118773884)\r
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A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting.:Transportation Research Part C: Emerging Technolog,2016,62:21-34\r
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Logit-based analysis of drivers’ crossing behavior at unsignalized intersections in china.:Human Factors,2015,57(7):1101-1114\r
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Percolation transition in dynamical traffic network with evolving critical bottlenecks.:Proceedings of the National Academy of Sciences,2015,112(3):669-672\r
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Logit-Based Merging Behavior Model for Uncontrolled Intersections in China.:Journal of Transportation Engineering,2015,140(12):04014059\r
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Analysis of road traffic network cascade failures with coupled map lattice method.:Mathematical Problems in Engineering,2015,2015:101059\r
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A travel time reliability model of urban expressways with varying levels of service.:Transportation Research Part C-Emerging Technologies,48:453-46\r
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Vehicle trajectory extraction by simple two-dimensional model matching at low camera angles in intersection.:IET Intelligent Transport Systems,2014,8(7):631-638\r
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Preempt or yield? An analysis of driver’s dynamic decision making at unsignalized intersections by classification tree.:Safety Science,2014,65:36-44\r
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Analyzing drivers’crossing decisions at unsignalized intersections in China.:Transportation research part F,2014,24:244-255\r
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A car-following model based on quantified homeostatic risk perception.:Mathematical Problems in Engineering,,2013,2013:408756\r
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Relationship between road traffic accidents and conflicts recorded by drive recorders.:Traffic injury prevention,2011,12(4):320-326\r
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An Optimal Schedule for Urban Road Network Repair Based on the Greedy Algorithm.:PloS one,2016,11(10):e0164780