干宏程教授可持续交通运输系统实验室

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实验室简介

可持续交通运输系统实验室（STSL，昵称GIANT）由干宏程教授于2006年建立，其人才培养和科学研究主要围绕交通运输工程、管理科学与工程、系统科学等一级学科。自成立以来，GIANT已使用多学科方法对可持续交通系统进行了基础理论、前沿科技和应用技术研究，其目前的主要研究领域为出行行为分析和需求建模、智能交通系统、城市物流。GIANT研发了各种可为可持续交通和物流系统的规划、设计和运营提供支持的各种技术。这些技术结合了计量经济学、离散选择模型、仿真、优化、统计和交通流理论等领域的方法。目前，GIANT成员包括干宏程教授、王可助理教授、多名硕博士生。

Sustainable Transport Systems Lab (STSL, or Nickname: GIANT) was established in 2006 by Professor Hongcheng Gan, and its teaching and research cover the disciplines of transportation, management science, and systems science. Since its inception, GIANT has conducted numerous studies of sustainable mobility systems using multidisciplinary methods, and currently its main areas of research include travel behavior analysis and demand modeling, intelligent transportation systems, and city logistics. GIANT develops various techniques to inform the planning, design and operations of sustainable transportation systems. The techniques combine ideas from the fields of econometrics, discrete choice models, simulation, optimization, statistics, and traffic flow theory. GIANT members currently include Professor Hongcheng Gan, Assistant Professor Ke Wang, and many master and PhD students.

成员

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干宏程

王可

王馨玉

陆欢

黄玥

孙永明

刘蒙

温金鹏

新闻博客

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GIANT成员黄玥获国家留学基金委联合培养博士项目资助

2023年7月，国家留基委公布了2023年国家建设高水平大学公派研究生项目（联合培养博士研究生）评审结果，GIANT成员2020级博士研究生黄玥获该项目资助，将赴意大利博洛尼亚大学进行一年联合培养。

GIANT成员陆欢参加第23届COTA国际交通科技年会（CICTP 2023）

2023年7月14至17日，第23届COTA国际交通科技年会（CICTP 2023）在北京工业大学举行。会议以“智能，低碳，互联：技术创新赋能可持续交通”为主题。GIANT成员2019级博士研究生陆欢参加年会，做论文《Exploring Direct and Indirect Effects of Psychological Factors on Urban Residents’ Green Travel Behavior: A case study in China》海报演讲，拓宽了学术视野。

GIANT成员尤梦婷入选赴德交换生项目

近日，上海理工大学交换生项目（2023年秋季）名单出炉，GIANT成员21级工程管理专业硕士研究生尤梦婷成功入选，预计将于今年9月前往德国富特旺根应用科学大学（Hochschule Furtwangen University），开启跨国学习之旅。

此次交换计划为期6个月，同学们将在德国高校学习相关专业课程，与当地师生一起学习和探讨，并参与各类文化交流活动，体验不同的生活方式和文化风情。

GIANT一直致力于提升课题组成员的国际视野和综合素质，希望通过与海外高校的交流，让成员更好地了解不同文化和教育体系，提升其跨文化交际能力和全球竞争力，培养更具有国际视野和竞争力的人才。

希望尤梦婷同学珍惜此次难得的学习机会，充分利用好德国高校的教育资源，提高自身的学术水平和综合素质。同时，也期待其能够积极发挥“文化大使”的作用，让世界更好地了解和认识中国文化。

研究

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近五年代表性SCI/SSCI论文

[1] Huang Y, Gan H, Postorino M N, Wang K, & Wang W. Does the information provider choose to promote public transport use or protect public health? A case study in China[J]. Journal of Transport & Health, 2023, 32: 101678.

[2] Huang Y, Gan H, Lu H, Wang X, & Wang W. Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model[J]. IET Intelligent Transport Systems, 2023.

[3] Wang K, Ye X, Shi C, & Gan H. Probit-based discrete-continuous choice model to explore the relationship between car ownership and commuters' non-work activity durations in Xiaoshan District of Hangzhou, China[J]. Transportation Research Record, 2023, 03611981231152252.

[4] Yin P, Ji D, Yan H, Gan H, & Zhang J. Multimodal deep collaborative filtering recommendation based on dual attention[J]. Neural Computing and Applications, 2023, 35(12): 8693-8706.

[5] Wang K, Bhat C R, Ye X. A multinomial probit analysis of Shanghai commute mode choice[J].Transportation, 2022: 1-25.

[6] Wang K, Ye X, Gan H. Mixed multinomial probit model accommodating flexible covariance structure and random taste variation: An application to commute mode choice behavior[J]. Journal of Advanced Transportation, 2022, 8686584.

[7] Ji D, Gan H. Effects of providing total cost of ownership information on below-40 young consumers' intent to purchase an electric vehicle: A case study in China[J]. Energy Policy, 2022, 165: 112954.

[8] Wang W, Gan H, Wang X, Lu H, & Huang Y. Initiatives and challenges in using gamification in transportation: a systematic mapping[J]. European Transport Research Review, 2022, 14(1): 1-19.

[9] Huang Y, Gan H, Jing P, & Wang X. Analysis of park and ride mode choice behavior under multimodal travel information service[J]. Transportation Letters, 2022, 14(10): 1080-1090.

[10] Lu H, Gan H. Evaluation and prevention and control measures of urban public transport exposure risk under the influence of COVID-19—Taking Wuhan as an example[J]. PloS One, 2022, 17(6): e0267878.

[11] Yin P, Wang J, Zhao J, Wang H, & Gan H. Deep collaborative filtering: A recommendation method for crowdfunding project based on the integration of deep neural network and collaborative filtering[J]. Mathematical Problems in Engineering, 2022, 4655030.

[12] Yin P, Chen Y, Wang H, Gan H, & Zhou Y. Recommending crowdfunding project: a graph kernel-based link prediction method for extremely sparse implicit feedback[J]. Computational Intelligence and Neuroscience, 2022, 5126140.

[13] Wang K, Ye X. Development of alternative stochastic frontier models for estimating time-space prism vertices[J].Transportation, 2021, 48(2): 773-807.

[14] Gan H, Wei J, Wang G. A generic work zone evaluation tool driven by a macroscopic traffic simulation model[J]. International Journal of Mobile Communications, 2021, 19(1): 1-21.

[15] Lu H, Gan H C. How to Formulate Urban Public Transport Management Measures Under the Influence of COVID-19?--Taking Wuhan as an Example. Transportation Research Board, 2021.

[16] Gan H, Ye X. Will commute drivers switch to park-and-ride under the influence of multimodal traveler information? A stated preference investigation[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2018, 56: 354-361.

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