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A Synthesis on Data Mining Methods and Applications for Automated Fare Collection (AFC) Data
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2021-05-01
[PDF-4.36 MB]
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Edition:Final report, January 2020 - May 2021
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Abstract:Automated Fare Collection (AFC) systems have been widely adopted by transit agencies around the world. AFC systems can provide a bias-free and low-cost approach to obtaining long-term continuous observations of transit passenger travel behavior. The availability of AFC data can help examine the behavior of passengers and the demand characteristics for public transportation services, which can be useful to support short-term planning and the development of long-term strategies. This research project provides a broad review of existing knowledge and experience in utilizing AFC data, from both the practice and research perspectives. After an extensive review of the literature, it is clear that there is a lot of research material in this area. However, there is still a need for an efficient, comprehensive, and user-friendly system to fully take advantage of the AFC data.
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