教师队伍

李大韦

时间:2023-11-14浏览:10


基本信息:

李大韦,博士,教授,博士生导师,东南大学交通工程系副主任,东南大学应急交通研究中心副主任

所属团队:应急交通研究中心

办公地点:东南大学九龙湖校区交通学院大楼1109

联系方式:lidawei@seu.edu.cn

 

   李大韦,男,198710月出生,教授,博士生导师。现任东南大学交通工程系副主任,东南大学应急交通研究中心副主任。

本硕毕业于东南大学交通学院,博士毕业于日本名古屋大学, 2014 年起任职于东南大学,曾在日本名古屋大学、新加坡-麻省理工联合研发中心(SMART)、香港理工大学从事科研工作。担任中国交通教育研究会高教分会理事、中国公路学会自动驾驶工作委员会委员、世界交通运输大会(WTC) 交通工程学部秘书、多模式交通网络规划技术委员会主席、面向未来的城市综合交通系统技术委员会主席、 交通运输工程学报(英文版)青年学术编辑、交通部公交都市建设示范工程验收专家等学术与行业兼职。

先后主持国家自然科学基金项目 2 项(青年+面上)、国家重点研发计划青年科学家课题课题 1 项、国家重点研发项目子课题 2 项、国家自然科学基金国合重点项目子课题 1 项、江苏省自然科学基金项目 1 项(验收评价为优秀),参与国家及省部级项目10 余项, 发表 SCI&SSCI 论文近 50 篇,授权发明专利 8 项、软著 3 项,分别在日本(与米其林、丰田公司合作项目)、新加坡(麻省理工 SimMobility 项目)、中国(独立开发 SimTrend多模式交通仿真软件)参与 3 项多模式交通系统建模与仿真软件开发。与携程、腾讯、华设、莱斯、交通部公路院、交通部科研院、智加、东软等国内外企业与行业单位有合作关系。

承担《交通工程基础》 等 5 门课程的教学工作。作为课程组负责人,建设东南大学交通工程专业基础课《交通行为分析基础》, 主持各类 4 项,参与国家级教改项目 1 项,省部级教改项目 1 项, 参与制作国家级在线精品课程《交通规划》。

指导学生获省优本科毕业设计、华为ICT大赛一等奖、交科赛国赛、省赛一等奖。

荣获中国公路学会科学技术奖一等奖(排 1/15),江苏省科学技术奖二等奖(排 2/11),中国运输协会科技进步一等奖(排 5/15),中国交通教育优秀中青年教师奖、国家级教学成果二等奖、江苏省教学成果特等奖、东南大学教学成果奖特等奖。



研究方向:

  • 交通行为分析与政策评价

  • AI+多模式交通系统建模与仿真

  • 智慧出行服务

  • 自动驾驶与自主式交通系统等



教育经历

2004-2008,东南大学,交通工程专业,学士学位;

2009-2011,东南大学,交通运输规划与管理专业,硕士学位;

2011-2014,名古屋大学(日本),城市环境专业,博士学位。


工作经历

2023年至今,东南大学, 交通学院, 教授, 东南大学交通工程系副主任, 东南大学应急交通研究中心副主任

2018-2020, 香港理工大学, CEE, 香江学者

2019, 名古屋大学 Institute of Materials and Systems for Sustainability (IMaSS),特任准教授

2017-2023,东南大学, 交通学院, 副教授、博导,城市智能交通省重点实验室秘书(曾任),交通工程研究所副所长(曾任),交通工程系副主任(现任)

2014-2017, 东南大学, 交通学院, 讲师

2014,名古屋大学 Green Mobility Collaborative Research Center,博士后研究员

2013 Singapore-MIT Alliance for Research and Technology,研究助理 (合作导师: Moshe Ben-Akiva 教授,麻省理工学院)

2008-2009,内蒙古准格尔旗第一中学,支教志愿者


学术兼职

[1] 中国交通教育研究会高教研究分会理事,2020

[2] 中国公路学会自动驾驶工作委员会委员,2019

[3] 世界交通运输大会(WTC

 交通工程学部秘书,2019

 多模式交通网络规划技术委员会主席,2019

 面向未来的城市综合交通系统技术委员会主席,2017

[4] 交通运输工程学报(英文版)青年学术编辑,2020

[5] 交通运输部公交都市建设示范工程验收专家,2019

[6] 腾讯犀牛鸟精英人才培养计划专家组成员,2019

[7] Frontier in Built Environment,审稿编辑,2022

[8] 《交通运输工程学报》交通需求响应机制设计与系统优化专刊组稿专家,2021

[9] 《清华大学学报(自然科学版)》城市综合交通专刊组稿专家,2021

[10]《交通运输工程与信息学报》专栏编委:新时代出行选择理论与方法,2021

[11]《交通运输系统工程与信息》城市多模式交通网运行仿真专栏组稿专家,2021

[12]《中国公路学报》优秀审稿人,2022


代表性科研项目

[1] 国家重点研发计划,交通载运装备与智能交通技术专项, 自主式交通系统运行及环境状态全息感知技术(指南 2.1), 2022/12-2026/11 3000 万元, 青年科学家课题自主式交通系统超视距全息感知与信息传输共享技术负责人(负责经费 485 万元);

[2] 国家自然科学基金项目(面上) , MaaS 背景下考虑复杂异质性的路径选择建模与网络混合需求分配, 2020/01-2023/12 50 万元,主持;

[3] 国家自然科学基金青年项目,考虑活动日程的多模式交通网络广义路径选择建模,2017/01-2019/12 20 万元,主持;

[4] 江苏省自然基金项目,考虑全天活动链的多模式交通网络下路径选择建模研究,2015/07-2018/06 20 万元,主持,结题,验收结果为优秀

[5] 国家重点研发计划,综合交通运输与智能交通专项,城市多模式交通网运行仿真系统平台开发(指南 2.1), 2020/02-2022/12 2200 万元, 子课题负责人(负责经费 175 万元);

[6] 国家重点研发计划,综合交通运输与智能交通专项,城市多模式交通供需平衡机理与仿真系统(指南 6.1), 2019/02-2021/12 2438 万元, 子课题负责人(负责经费 30 万元);

[7] 国家自然科学基金国际合作与交流重点项目, 515110143,低碳化进程中城市多模式交通系统运营关键问题研究, 2015/09-2018/08 300 万元,子课题负责人(负责经费 25万元);

[8] 江苏省政策引导类计划(省重点研发系列,以色列国合项目) ,基于车路协同(V2X)的智慧移动即服务的公交优先系统联合研发, 2020/06-2022/06,100 万元, 技术负责人(企业牵头) ;


代表论著

[1]李大韦; 冯思齐; 曹奇; 宋玉晨; 赖信君; 任刚 ; 大数据背景下的路径选择行为建模, 中国公路学报, 2021, 34(12): 161-174

[2] Yuchen Song; Dawei Li; Qi Cao; Min Yang; Gang Ren ; The whole day path planning problem incorporating mode chains modeling in the era of mobility as a service, Transportation Research Part C: Emerging Technologies, 2021, 132: 0-103360

[3] Yuchen Song; Dawei Li; Dongjie Liu; Qi Cao; Junlan Chen; Gang Ren; Xiaoyong Tang ; Modeling activity-travel behavior under a dynamic discrete choice framework with unobserved heterogeneity, Transportation Research Part E: logistics and Transportation Review, 2022, 167:102914-102914

[4]Dawei Li; Min Yang; Cheng-Jie Jin; Gang Ren; Xianglong Liu; Haode Liu ; Multi-Modal Combined Route Choice Modeling in the MaaS Age Considering Generalized Path Overlapping Problem, IEEE Transactions on Intelligent Transportation Systems, 2020, 22(4): 2430-2441

[5]Dawei Li; Tomio Miwa; Takayuki Morikawa; Pan Liu ; Incorporating observed and unobserved heterogeneity in route choice analysis with sampled choice sets, Transportation Research Part C:

Emerging Technologies, 2016, 67: 31-46


学术成果:

  • 专著与章节

交通强国建设首本推荐教材《综合交通运输导论》(交通运输部交通强国建设首本推荐教材,编委会委员)

  • 国内国际期刊论文

[1] Wang, J, Miwa, T, Ma, X, Li, D., & Morikawa, T. (2023). Recovering Real Demand for Free-Floating BikeSharing System Considering Demand Truncation Migration, and Spatial Correlation. IEEE Transactions on Intelligent Transportation Systems. Accepted.

[2] Liu, D., Li, D., Sze, N. N., Ding, H., & Song, Y. (2023). An integrated data-and theory-driven crash severity model. Accident Analysis & Prevention, 193, 107282.

[3] Cao, Q., Deng, Y., Ren, G., Liu, Y., Li, D., Song, Y., & Qu, X. (2023). Jointly estimating the most likely driving paths and destination locations with incomplete vehicular trajectory data. Transportation Research Part C: Emerging Technologies, 155, 104283.

[4] Jin, C. J., Shi, K. D., Jiang, R., Li, D., & Fang, S. (2023). Simulation of bi-directional pedestrian flow under high densities using a modified social force model. Chaos, Solitons & Fractals, 172, 113559.

[5] Li, D., Song, Y., Liu, D., Cao, Q., & Chen, J. (2023). How carpool drivers choose their passengers in Nanjing, China: effects of facial attractiveness and credit. Transportation, 50(3), 929-958.

[6] Li, D., Feng, S., Song, Y., Lai, X., & Bekhor, S. (2023). Asymmetric closed-form route choice models: Formulations and comparative applications. Transportation research part A: policy and practice, 171, 103627.

[7] Li, D., Dai, Q., Zhang, T., & Shi, X. (2023). Long-Term Individual Trip Pattern Prediction of Bus Passengers Using Smart Card Data: A Bayesian Method Based on Feature Selection.

[8] Chen, Q., Zhang, H., Song, Y., Huang, D., Li, D., & Wang, H. (2022). Analysis of Perception Variance in Regret Choice Modeling Based on GPS Data Considering Building Environment Effects. Journal of Advanced Transportation, 2022.

[9] Shi, X., Xue, S., Shiwakoti, N., Li, D., & Ye, Z. (2022). Examining the effects of exit layout designs on children pedestrians’ exit choice. Physica A: statistical mechanics and its applications, 602, 127654.

[10] Li, D., Al-Mahamda, M. F., Song, Y., Feng, S., & Sze, N. N. (2022). An alternate crash severity multicategory modeling approach with asymmetric property. Analytic methods in accident research, 35, 100218.

[11] Li, D., Liu, Y., Song, Y., Ye, Z., & Liu, D. (2022). A Framework for Assessing Resilience in Urban Mobility: Incorporating Impact of Ridesharing. International Journal of Environmental Research and Public Health, 19(17), 10801.

[12] 梁顺利;李香红;李大韦;郑兰兰;宋晖颖. (2022) 疫情下安装共享电动车头盔消毒装置博弈. 交通科技与经济, 24(4), 23.

[13] Wang, Y., Ren, G., & Li, D. (2022). Activity-Travel Demand Modeling Based on Multi-Agent Simulation. In CICTP 2022 (pp. 1492-1502).

[14] 李大韦;冯思齐;曹奇;宋玉晨;赖信君;任刚.(2021) 大数据背景下的路径选择行为建模,中国公路学报2021, 34(12): 161-174

[15] Song, Y., Li, D., Cao, Q., Yang, M., Ren, G. (2021) The whole day path planning problem incorporating mode chains modeling in the era of mobility as a service. Transportation

Research Part C: Emerging Technologies 132, 103360.

[16] Li, D., Song, Y., Sze, N., Li, Y., Miwa, T., Yamamoto, T. (2021) An alternative closedform crash severity model with the non-identical, heavy-tailed, and asymmetric properties. Accident Analysis & Prevention 158, 106192.

[17] Ma, J., Li, D., Tu, Q., Du, M., Jiang, J. (2021) Finding optimal reconstruction plans for separating trucks and passenger vehicles systems at urban intersections considering environmental impacts. Sustainable Cities and Society 70, 102888.

[18] Yuan, Y., Yang, M., Feng, T., Rasouli, S., Li, D., Ruan, X. (2021) Heterogeneity in passenger satisfaction with air-rail integration services: Results of a finite mixture partial least squares model. Transportation Research Part A: Policy and Practice 147, 133-158.

[19] Jin, C.-J., Jiang, R., Liu, T., Li, D., Wang, H., Liu, X. (2021) Pedestrian dynamics with different corridor widths: Investigation on a series of uni-directional and bi-directional experiments. Physica A: Statistical Mechanics and its Applications 581, 126229.

[20] Shi, X., Xue, S., Feliciani, C., Shiwakoti, N., Lin, J., Li, D., Ye, Z. (2021) Verifying the applicability of a pedestrian simulation model to reproduce the effect of exit design on egress flow under normal and emergency conditions. Physica A: Statistical Mechanics and its Applications 562, 125347.

[21] Jin, C.-J., Shi, X., Hui, T., Li, D., Ma, K. (2021) The automatic detection of pedestrians under the high-density conditions by deep learning techniques. Journal of advanced transportation 2021.

[22] Xue, S., Shi, X., Jiang, R., Feliciani, C., Liu, Y., Shiwakoti, N., Li, D. (2021) Incentivebased experiments to characterize pedestrians’ evacuation behaviors under limited visibility. Safety Science 133, 105013.

[23] Cao, Q., Ren, G., Li, D., Li, H., Ma, J. (2021) Map Matching for Sparse Automatic Vehicle Identification Data. IEEE Transactions on Intelligent Transportation Systems.

[24] Li, D., Yang, M., Jin, C.-J., Ren, G., Liu, X., Liu, H. (2020) Multi-Modal Combined Route Choice Modeling in the MaaS Age Considering Generalized Path Overlapping Problem. IEEE Transactions on Intelligent Transportation Systems 22, 2430-2441.

[25] Li, D., Al-Mahamda, M.F. (2020) Collective risk ranking of highway segments on the basis of severity-weighted crash rates. Journal of advanced transportation 2020.

[26] Cao, Q., Ren, G., Li, D., Ma, J., Li, H. (2020) Semi-supervised route choice modeling with sparse Automatic vehicle identification data. Transportation Research Part C: Emerging Technologies 121, 102857.

[27] Li, D., Jin, C.-j., Yang, M., Chen, A. (2020) Incorporating multi-level taste heterogeneity in route choice modeling: From disaggregated behavior analysis to aggregated network loading. Travel Behaviour and Society 19, 36-44.

[28] Jin, C.-J., Jiang, R., Li, D.-W. (2020) Influence of bottleneck on single-file pedestrian flow: Findings from two experiments. Chinese Physics B 29, 088902.

[29] Li, D., Miwa, T., Xu, C., Li, Z. (2019) Non-linear fixed and multi-level random effects of origin–destination specific attributes on route choice behaviour. IET Intelligent Transport Systems 13, 654-660.

[30] Jin, C.-J., Jiang, R., Wong, S., Xie, S., Li, D., Guo, N., Wang, W. (2019) Observational characteristics of pedestrian flows under high-density conditions based on controlled experiments. Transportation research part C: emerging technologies 109, 137-154.

[31] Jin, C.-J., Jiang, R., Liang, H.-F., Li, D., Wang, H. (2019) The similarities and differences between the empirical and experimental data: investigation on the single-lane traffic. Transportmetrica B: transport dynamics.

[32] Jin, C.-J., Jiang, R., Li, R., Li, D. (2019) Single-file pedestrian flow experiments under high-density conditions. Physica A: Statistical Mechanics and its Applications 531, 121718.

[33] Tu, Q., Cheng, L., Li, D., Ma, J., Sun, C. (2019) Traffic paradox under different equilibrium conditions considering elastic demand. Promet-Traffic&Transportation 31, 1-9.

[34] Jin, C.-J., Knoop, V.L., Li, D., Meng, L.-Y., Wang, H. (2019) Discretionary lane-changing behavior: empirical validation for one realistic rule-based model. Transportmetrica A: transport science 15, 244-262.

[35] Jin, C.-J., Jiang, R., Wei, W., Li, D., Guo, N. (2018) Microscopic events under high-density condition in uni-directional pedestrian flow experiment. Physica A: Statistical Mechanics and its Applications 506, 237-247.

[36] Lou, X., Cheng, L., Li, D., Zhu, S., Zhou, J. (2018) Modeling Day-to-Day Dynamics of Travelers’ Risky Route Choices under the Influence of Predictive Traffic Information. Transp. Res. Record 2672, 12-23.

[37] Ma, J., Li, D., Cheng, L., Lou, X., Sun, C., Tang, W. (2018) Link restriction: Methods of testing and avoiding braess paradox in networks considering traffic demands. Journal of Transportation Engineering, Part A: Systems 144, 04017076.

[38] Xu, C., Li, D., Li, Z., Wang, W., Liu, P. (2018) Utilizing structural equation modeling and segmentation analysis in real-time crash risk assessment on freeways. KSCE Journal of Civil Engineering 22, 2569-2577.

[39] Li, Z., Xu, C., Li, D., Liu, P., Wang, W. (2018) Comparing the effects of ramp metering and variable speed limit on reducing travel time and crash risk at bottlenecks. IET Intelligent Transport Systems 12, 120-126.

[40] Yang, M., Wu, J., Rasouli, S., Cirillo, C., Li, D. (2017) Exploring the impact of residential relocation on modal shift in commute trips: Evidence from a quasi-longitudinal analysis. Transport Policy 59, 142-152.

[41] Li, D., Hu, X., Jin, C.-j., Zhou, J. (2017) Learning to detect traffic incidents from data based on tree augmented naive bayesian classifiers. Discrete Dynamics in Nature and Society

2017.

[42] Jin, C.-J., Jiang, R., Yin, J.-L., Dong, L.-Y., Li, D. (2017) Simulating bi-directional pedestrian flow in a cellular automaton model considering the body-turning behavior. Physica A: Statistical Mechanics and its Applications 482, 666-681.

[43] Li, D., Miwa, T., Morikawa, T. (2016) Modeling time-of-day car use behavior: A Bayesian network approach. Transportation research part D: transport and environment 47, 54-66.

[44] Li, D., Miwa, T., Morikawa, T., Liu, P. (2016) Incorporating observed and unobserved heterogeneity in route choice analysis with sampled choice sets. Transportation research part C: emerging technologies 67, 31-46.

[45] Li, D., Miwa, T., Morikawa, T. (2015) Analysis of Vehicles' Daily Fuel Consumption Frontiers with Long-Term Controller Area Network Data. Transp. Res. Record 2503, 100-109.

[46] Li, D., Miwa, T., Morikawa, T. (2014) Analysis of car usage time frontiers incorporating both inter-and intra-individual variation with GPS data. Transp. Res. Record 2413, 13-23.

[47] Li, D., Miwa, T., Morikawa, T. (2014) Considering en-route choices in utility-based route choice modelling. Networks and Spatial Economics 14, 581-604.

[48] Li, D., Miwa, T., Morikawa, T. (2013) Dynamic route choice behavior analysis considering en-route learning and choices. Transp. Res. Record 2383, 1-9.

[49] Li, D., Miwa, T., Morikawa, T. (2013) Use of Private Probe Data in Route Choice Analysis to Explore Heterogeneity in Drivers' Familiarity with Origin–Destination Pairs. Transp. Res. Record 2338, 20-28.

[50] Li, D., Cheng, L., Ma, J. (2011) Incident duration prediction based on latent Gaussian naïve Bayesian classifier. International Journal of Computational Intelligence Systems 4, 345-352.

  • 授权发明专利与软著

[1] 李大韦;邱树荣;任刚;白桦;宋玉晨.一种 MaaS 背景下考虑路径选择权的平台混合均衡定价方法[P]. 江苏省: CN114862439A,2022-08-05.

[2] 李大韦,宋玉晨,任刚,杨敏,刘向龙. 一种组合出行方式下考虑用户感知差异性的路径选择方法[P]. 江苏省: ZL202010513555.1,2021-03-09.

[3] 王立超,杨敏,李斌,徐铖铖,李大韦. 高速公路常发性瓶颈路段协作车队冲突避险自主决策方法[P]. 江苏省: ZL201911115220.8,2020-11-27.

[4] 蒯陈辰,李大韦. 考虑太阳高度角差异的沥青路面反射率测试装置及方法[P]. 江苏省: ZL201911165882.6,2020-10-27.

[5] 李大韦,张雨嘉. 一种基于不完备人口信息的交通模式选择分析方法[P]. 江苏省: ZL201911165903.4,2020-06-26.

[6] 李大韦,曹奇,任刚,武文通. 一种基于浮动车检测器数据的固定检测器数据匹配新算法[P]. 江苏省: ZL201811158230.5,2020-04-21.

[7] 李大韦,武文通,李成. 一种基于网络承载力的电动公交网络可靠性评价方法[P]. 江苏省: ZL201911167071.X,2020-02-28.

[8] 程琳,马捷,李大韦. 一种考虑交通需求和道路网络运行效率的路段检测方法[P]. 江苏省: ZL201711128732.9,2020-02-18.

[9] 李大韦,汤宇翔,李成. 多个个体车辆使用行为短时预测的深度学习方法[P]. 江苏省:ZL201910457968.X,2019-09-06.

[10] 李大韦,邵洁,宋玉晨. 基于多智能体的联程出行仿真平台 SimTrend V1.0.2021SR1183879,2021-07-26.

[11]李大韦. 多模式交通系统仿真软件. 2020SR0352376,2019-12-30.

[12]李大韦. 微博舆情交通事件检测分析软件 V1.0. 2019SR0531639,2019-05-19.


奖励及荣誉

[1] 中国公路学会科学技术奖一等奖(2022 年度,排 1/15

[2] 江苏省科学技术奖二等奖(2022 年度,排 2/11

[3] 中国运输协会科技进步一等奖(2021 年度,排 5/15

[4] 入选香江学者计划

[5] 东南大学至善学者A 类)

[6] WTC 最佳论文奖(2 次)

[7] 腾讯犀牛鸟精英人才培养计划专家组成员

[8] 参与国家级一流在线课程《交通规划》建设

[9] 国家级教学成果二等奖

[10] 江苏省教学成果奖特等奖

[11] 荣获中国交通教育优秀中青年教师称号

[12] 中国交通教育研究会高校研究分会理事

[13] 培养学生获华为ICT大赛一等奖、交科赛国赛、省赛一等奖

[14] 省优本科毕业设计指导老师






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