Study group travel behaviour patterns from large-scale smart card data

• Main Authors: TIAN, Xiancai, ZHENG, Baihua
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: smart card data; spatial and temporal systems; group travel behaviour; bloom filter; Databases and Information Systems; Urban Studies
• Online Access: https://ink.library.smu.edu.sg/sis_research/4614; https://ink.library.smu.edu.sg/context/sis_research/article/5617/viewcontent/Study_Group_Travel_Behaviour_From_Smart_Card_Data__Camera_Ready_.pdf
• Institution: Singapore Management University

In this paper, we aim at studying the group travel behaviour (GTB) patterns from large-scale auto fare collection (AFC) data. GTB is defined as two or more commuters intentionally and regularly traveling together from an origin to a destination. We propose a method to identify GTB accurately and efficiently and apply our method to the Singapore AFC dataset to reveal the GTB patterns of Singapore commuters. The case study proves that our method is able to identify GTB patterns more accurately and efficiently than the state-of-the-art.