科研项目与成果

【主持省部级以上项目及子课题】

Ø  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；

Ø  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；

Ø  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”；

Ø  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）；

Ø  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）；

Ø  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）；

Ø  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）；

Ø  江苏省“六大人才高峰” 项目，新能源公交系统可靠性分析与风险评估方法研究，2020/01-2022/12，主持。

【近五年代表性论文（JCR Q1期刊一作或通讯）】

[1]     （通讯作者）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.

[2]     （一作）Li, D., Song, Y., Sze, N., Li, Y., Miwa, T., Yamamoto, T. (2021) An alternative closed-form crash severity model with the non-identical, heavy-tailed, and asymmetric properties. Accident Analysis & Prevention 158, 106192.

[3]     （通讯）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.

[4]     （共同一作）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.

[5]     （一作）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.

[6]     （共同一作）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.

[7]     （一作）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.

[8]     （一作）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.

论文与知识产权清单

【论文清单（SCI&SSCI与中文顶刊）】

[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，已录用

[2]     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.

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

[4]     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.

[5]     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.

[6]     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.

[7]     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.

[8]     He, K., Cao, Q., Ren, G., Li, D., Zhang, S. (2021) Map Matching for Fixed Sensor Data Based on Utility Theory. Journal of Advanced Transportation 2021.

[9]     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.

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

[11]  Chen, Q., Zhang, H., Wang, J., Ye, H., Chu, Z., Lou, B., Li, D. (2021) Impact of Shared Bus on Campus Travel and Space Optimization Based on Activity Travel Behavior. Journal of Advanced Transportation 2021.

[12]  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.

[13]  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.

[14]  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.

[15]  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.

[16]  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.

[17]  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.

[18]  Li, D., Tang, Y., Chen, Q. (2020) Multi-mode traffic demand analysis based on multi-source transportation data. IEEE Access 8, 65005-65019.

[19]  Li, D., Song, Y., Chen, Q. (2020) Bilevel programming for traffic signal coordinated control considering pedestrian crossing. Journal of advanced transportation 2020.

[20]  Li, D., Wu, W., Song, Y. (2020) Comparative Study of Logit and Weibit Model in Travel Mode Choice. IEEE Access 8, 63452-63461.

[21]  Li, D., Song, Y. (2020) Route Choice Considering Hybrid Regret and Utility Modeling Under Big Data Context. IEEE Access 8, 7817-7828.

[22]  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.

[23]  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.

[24]  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.

[25]  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.

[26]  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.

[27]  Li, D., Li, C., Miwa, T., Morikawa, T. (2019) An exploration of factors affecting drivers’ daily fuel consumption efficiencies considering multi-level random effects. Sustainability 11, 393.

[28]  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.

[29]  Li, D., Zhang, Y., Li, C. (2019) Mining public opinion on transportation systems based on social media data. Sustainability 11, 4016.

[30]  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.

[31]  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.

[32]  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.

[33]  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.

[34]  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.

[35]  Tu, Q., Cheng, L., Li, D., Ma, J., Sun, C. (2018) Stochastic transportation network considering ATIS with the information of environmental cost. Sustainability 10, 3861.

[36]  Ma, J., Cheng, L., Li, D., Tu, Q. (2018) Stochastic electric vehicle network considering environmental costs. Sustainability 10, 2888.

[37]  Ma, J., Cheng, L., Li, D. (2018) Road maintenance optimization model based on dynamic programming in urban traffic network. Journal of Advanced Transportation 2018.

[38]  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.

[39]  Zhu, S., Guo, Y., Chen, J., Li, D., Cheng, L. (2017) Integrating optimal heterogeneous sensor deployment and operation strategies for dynamic origin-destination demand estimation. Sensors 17, 1767.

[40]  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.

[41]  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.

[42]  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.

[43]  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.

[44]  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.

[45]  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.

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

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

[48]  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.

[49]  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.

【授权专利与软著】

[1]  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.

[2]  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.

[3]  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.

[4]  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：ZL 201911165903.4,2020-06-26.

[5]  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.

[6]  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.

[7]  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.

[8]  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.

[9]  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.

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

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