Profiling urban activity hubs using transit smart card data

Rachel Cardell-Oliver, Travis Povey

Research output: Chapter in Book/Conference paperConference paper

3 Citations (Scopus)

Abstract

Understanding why and where people travel by public transport is a key enabler for smart cities because it informs city planning, daily operations, and sustainable city growth. This article introduces a data-driven approach using transit smart card data to discover where activities are concentrated and why people travel to those regions. Our approach is based on the idea of stays between passenger trips. A stay has an arrival time and a period of time spent in a certain region. The regions where stays are concentrated are called hubs. Coherent clusters of stays indicate human activities such as going to work or short errands. An efficient and robust algorithm is proposed for learning hubs and their activities. Triangulation with points of interest and ticket data validates that activity stays and hub activities satisfy common sense expectations. The utility of the activity hub profiles for urban planners and transport managers is demonstrated by use cases for operational, tactical and strategic goals.

Original languageEnglish
Title of host publicationBuildSys 2018 - Proceedings of the 5th Conference on Systems for Built Environments
EditorsGowri Sankar Ramachandran, Nipun Batra
Place of PublicationUSA
PublisherAssociation for Computing Machinery (ACM)
Pages116-125
Number of pages10
ISBN (Electronic)9781450359511
DOIs
Publication statusPublished - 7 Nov 2018
Event5th ACM International Conference on Systems for Built Environments, BuildSys 2018 - Shenzen, China
Duration: 7 Nov 20188 Nov 2018

Conference

Conference5th ACM International Conference on Systems for Built Environments, BuildSys 2018
CountryChina
CityShenzen
Period7/11/188/11/18

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