以网络专车等共享交通模式为代表，大数据与移动互联网推动了交通运营组织与出行行为的革命性转变，同时造成交通管理与决策传统范式无力应对大数据环境下交通出行呈现的新特征。大数据及其挖掘技术的出现，正在重新定义交通行业的思维模式与分析手段，成为引导交通管理与决策范式转变的重要推动力。本项目以共享交通为典型研究对象，主要运用融合动态时空轨迹和社会网络分析的交通大数据理论与方法，探索共享交通网络、活动轨迹网络以及社会网络之间的协同演化机制：共享交通网络形成及其动态演化机理、基于社会网络的共享出行行为机理、基于活动轨迹网络的共享交通供需匹配机制。建立针对共享交通“精细化管理、全过程监管、高精度调控”的管理与决策理论和方法体系，旨在揭示大数据驱动下交通管理与决策范式转变的机理与理论，探索形成大数据驱动下交通领域管理与决策的基础理论与示范应用，为进一步探索应用大数据驱动提升综合交通治理能力奠定基础。

With sharing transport (e.g. Uber special cars) as the representative, the big data and mobile internet have promoted the revolutionary changes of transport organization and travel behavior patterns. As a result, the traditional paradigm of transport management and decision is unable to deal with the new travel characteristics under the big data environment. The arising of big data mining technology has redefined the thinking pattern and analyzing tools in transport area. Taking sharing transport as the research subject, this research incorporated the dynamic time-space trajectory and social network analysis into the theory and method of transport data mining. This research is to explore the synergetic evolution mechanism among sharing transport network, activity trajectory network and social network, which include three important research problems , i.e. sharing transport network formation and its evolution mechanism, mechanism of sharing travel behavior based on social network and mechanism of matching supply and demand of sharing transport based on activity trajectory network. Furthermore, this research is to build the theory and methodology of sharing transport management and decision for meticulous management, whole-process supervision and high-resolution control. Aiming at revealing the shifting mechanism and theory of the transport management and decision paradigm with big data driving, the project will build a demonstration application for big data driven transport industry, and provide a paragon for solving the key scientific issues of the major research plan.