GIS-Based Commute Analysis Using Smart Card Data: A Case Study of Multi-Mode Public Transport for Smart City

This paper utilized the one-week smart card data (SCD) and the control passenger flow survey to analyze the commute travel time and the passenger flow distribution in the multi-mode public transport. To research the commute pattern of the central business district (CBD), there were three large-scale residence communities selected for the survey areas. Based on SCD in the double ticket system, the average travel time and the passenger volume were estimated through clustering “the alighting time” and filling none value. As a result, the visualization of the station attraction and the travel time under multi-mode public transport was presented through the application of GIS. The analysis of the commute pattern is aimed to make a scientific guidance for commuters on the traffic model choice as well as provide a quantitative basis for the development of the smart city.

[1]  Liang Fan,et al.  Color Image Watermarking Adaptively in DC Coefficients , 2010 .

[2]  Zhou Xuemei.  Research on Travel Mode Choice Behavior Under Integrated Multi-modal Transit Information Service , 2009 .

[3]  Carlos Fernández-Valdivielso,et al.  Analysis Matrix for Smart Cities , 2014, Future Internet.

[4]  Li Dere.  Big Data in Smart City , 2014 .

[5]  Yasuo Asakura,et al.  Behavioural data mining of transit smart card data: A data fusion approach , 2014 .

[6]  David M Levinson,et al.  Modeling the commute mode share of transit using continuous accessibility to jobs , 2015 .

[7]  Bian Zheng-fu.  Study on Distribution Patterns of Settlements Based on GIS-SDA , 2008 .

[8]  Zhen Sean Qian,et al.  Modeling Multi-Modal Morning Commute in a One-to-One Corridor Network , 2011 .

[9]  Marcela Munizaga,et al.  Estimation of a disaggregate multimodal public transport Origin-Destination matrix from passive smartcard data from Santiago, Chile , 2012 .

[10]  Zhao Yibin.  An Analytical Framework for Travel-activity Pattern Analysis-A GIS Approach , 2010 .

[11]  H M Smith.  THE INTERNATIONAL FISHERY CONGRESS, 1908. , 1906, Science.

[12]  Timothy F Welch,et al.  Performance indicators for public transit connectivity in multi-modal transportation networks , 2012 .

[13]  Fu Xiaoli.  Travel Time Reliability Appraisal for Urban Multi-modal Public Transport Network , 2010 .

[14]  Lai Jianhui.  An Approach on Station ID and Trade Record Match Based on GPS and IC Card Data , 2012 .

[15]  Cui Chengyin,et al.  Identifying Commuting Pattern of Beijing Using Bus Smart Card Data , 2012 .