基于APTS大数据的城市公交出行多维分析模型和方法

智能公交系统(Advanced Public Transportation Systems，APTS)数据具有海量、类型多样等大数据的典型特征，对其进行分析和挖掘可能获得丰富的公交出行特征和规律.构建基于APTS大数据的公交出行多维分析框架，在计算乘客出行时空信息(上车、下车和换乘)的基础上，建立包含4个维度(乘客、时间、空间和行为)的公交出行数据模型，系统提出基于5种联机分析处理方法的公交出行分析内容.应用APTS大数据对模型和方法进行了实验和验证，研究结果表明，该方法能够便捷地分析不同维度、不同粒度的公交出行信息，不仅能够应用于公交乘客出行行为的研究，还能够为城市公交系统的规划和管理提供决策支持.

Public Transportation Travel Multi-dimensional Analysis Method Based on APTS Big Data

Advanced Public Transportation Systems (APTS) data have the typical characteristics of massive and diverse data. It is possible to obtain abundant transit travel characteristics and rules by analyzing and mining APTS data. The multi-dimensional analysis framework of bus travel based on APTS data is constructed. On the basis of calculating passenger travel time-space information (boarding, alighting and transferring), the multi-dimensional data model of transit travel with four dimensions (passenger, time, space and behavior) is established. Then, the content of public transportation travel multi- dimension analysis based on 5 kind of online analysis process operations is systematically presented. Finally, the model and the method are experimented and verified using APTS big data. The results show that this method can easily analyze different dimensions and granularities of transit travel information and can not only be applied to the study of transit travel behavior, but also provides decision-making support for the planning and management of urban public transportation system.