MetroWatch: A predictive system to estimate travel attributes using smart card data
In this demonstration, we present a fully data driven solution to retrieve passengers’ actual paths within a metro system that are not captured by an Automated Fare Collection (AFC) system. The majority of public transit systems employ AFC systems with smart cards, which record the exact origin, des...
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sg-smu-ink.sis_research-90332023-08-11T03:18:03Z MetroWatch: A predictive system to estimate travel attributes using smart card data BRAHMANAGE JANAKA CHATHURANGA THILAKARATHNA, KANDAPPU, Thivya ZHENG, Baihua In this demonstration, we present a fully data driven solution to retrieve passengers’ actual paths within a metro system that are not captured by an Automated Fare Collection (AFC) system. The majority of public transit systems employ AFC systems with smart cards, which record the exact origin, destination, admission time, and exit time of each passenger’s metro trip. Our solution uses AFC data to first infer travel times and route preferences and then estimates the passengers’ travel paths for all trips to provide a statistical view of passengers’ crowdedness inside a metro network over time. 2023-04-07T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/8030 info:doi/10.1109/ICDE55515.2023.00279 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Smart cards Estimation Data engineering Databases and Information Systems |
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Smart cards Estimation Data engineering Databases and Information Systems BRAHMANAGE JANAKA CHATHURANGA THILAKARATHNA, KANDAPPU, Thivya ZHENG, Baihua MetroWatch: A predictive system to estimate travel attributes using smart card data |
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In this demonstration, we present a fully data driven solution to retrieve passengers’ actual paths within a metro system that are not captured by an Automated Fare Collection (AFC) system. The majority of public transit systems employ AFC systems with smart cards, which record the exact origin, destination, admission time, and exit time of each passenger’s metro trip. Our solution uses AFC data to first infer travel times and route preferences and then estimates the passengers’ travel paths for all trips to provide a statistical view of passengers’ crowdedness inside a metro network over time. |
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BRAHMANAGE JANAKA CHATHURANGA THILAKARATHNA, KANDAPPU, Thivya ZHENG, Baihua |
author_facet |
BRAHMANAGE JANAKA CHATHURANGA THILAKARATHNA, KANDAPPU, Thivya ZHENG, Baihua |
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BRAHMANAGE JANAKA CHATHURANGA THILAKARATHNA, |
title |
MetroWatch: A predictive system to estimate travel attributes using smart card data |
title_short |
MetroWatch: A predictive system to estimate travel attributes using smart card data |
title_full |
MetroWatch: A predictive system to estimate travel attributes using smart card data |
title_fullStr |
MetroWatch: A predictive system to estimate travel attributes using smart card data |
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MetroWatch: A predictive system to estimate travel attributes using smart card data |
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metrowatch: a predictive system to estimate travel attributes using smart card data |
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Institutional Knowledge at Singapore Management University |
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2023 |
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https://ink.library.smu.edu.sg/sis_research/8030 |
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