Citizen Commuting Analysis Using Mobile Trajectory Data

  Objectives  Citizen commuting analysis is useful for solving jobs-housing imbalance and traffic congestion. Mobile trajectory data, strengthening the observation of citizen commuting in data types, data volume, sampling frequency, and information content, is helpful for exploring jobs-housing patterns and citizen commuting distribution.

  Methods  We have investigated the research progress of citizen commuting and mobile trajectory analysis, and have worked out relevant concepts, indexes, metrics, models and theoretical methods of commuting activity analysis. The representative results of spatial interaction model, transportation planning model, linear programming model, and micro-physical model are compared, and the characteristics of their application in the analysis of citizen commuting activities are discussed from a multidisciplinary perspective.

  Results  Four types of trajectory data characteristics of citizen commuting activities are summarized. From the perspectives of citizen commuting behaviors pattern and its jobs-housing restrictions, we have proposed the architecture of exploring the relationships between citizen commuting and jobs-housing from mobile trajectory data.

  Conclusions  The technology of multidisciplinary development of citizen commuting analysis is addressed, and the comprehensive method of analyzing trajectory big data, multi-source data fusion, and commuting activity prediction are the focus of future research.