轨迹大数据：数据、应用与技术现状

移动互联技术的飞速发展催生了大量的移动对象轨迹数据。这些数据刻画了个体和群体的时空动态性，蕴含着人类、车辆、动物的行为信息，对交通导航、城市规划、车辆监控等应用具有重要的价值。为了实现有效的轨迹数据价值提取，近年来学术界和工业界针对轨迹管理问题开展了大量研究工作，包括轨迹数据预处理，以解决数据冗余高、精度差、不一致等问题；轨迹数据库技术，以支持有效的数据组织和高效的查询处理；轨迹数据仓库，支持大规模轨迹的统计、理解和分析；最后是知识提取，从数据中挖掘有价值的模式与规律。因此，综述轨迹大数据分析，从企业数据、企业应用、前沿技术这3个角度揭示该领域的现状。

Trajectory big data: data, applications and techniques

The fast development of mobile internet has given rise to an extremely large volume of moving objects trajectory data. These data not only reflect the spatio-temporal mobility of individuals and groups, but may also contain the behavior information of people, vehicles animals, and other objects of interest. They are invaluable for route planning, urban planning and vehicle monitoring, etc., and tremendous efforts have been made to support effective trajectory data management, including trajectory data pre-processing, which handles issues such as high redundancy, low precision and inconsistency of sampling; trajectory database technologies, concerning the efficient and effective storage of trajectory data and query processing; trajectory data warehousing, which supports the analytics on large-scale trajectory data; knowledge discovery, by which useful patterns can be extracted from trajectory data. A survey of trajectory big data analytics from three different aspects: data, applications and techniques is provided.