Inferring individual daily activities from mobile phone traces: A Boston example
Joseph Ferreira and
Environment and Planning B, 2016, vol. 43, issue 5, 920-940
Understanding individual daily activity patterns is essential for travel demand management and urban planning. This research introduces a new method to infer individualsâ€™ activities from their mobile phone traces. Using Metro Boston as an example, we develop an activity detection model with travel diary surveys to reveal the common laws governing individualsâ€™ activity participation, and apply the modeling results to mobile phone traces to extract the embedded activity information. The proposed approach enables us to spatially and temporally quantify, visualize, and examine urban activity landscapes in a metropolitan area and provides real-time decision support for the city. This study also demonstrates the potential value of combining new â€œbig dataâ€ such as mobile phone traces and traditional travel surveys to improve transportation planning and urban planning and management.
Keywords: Individual activity detection; urban sensing; mobile phone traces; travel survey (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15) Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:43:y:2016:i:5:p:920-940
Access Statistics for this article
More articles in Environment and Planning B
Bibliographic data for series maintained by SAGE Publications ().