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Information 2018, 9(1), 18;

Smart Card Data Mining of Public Transport Destination: A Literature Review

1,2,3,* , 1
School of Automobile and Traffic Engineering, Jiangsu University, Jiangsu 212013, China
School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 264209, China
College of Engineering, Texas A&M University, Kingsville, TX 77843-0100, USA
School of Vehicle Engineering, Xi’an Aeronautical University, Xi’an 710077, China
Author to whom correspondence should be addressed.
Received: 30 November 2017 / Revised: 5 January 2018 / Accepted: 10 January 2018 / Published: 13 January 2018
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Smart card data is increasingly used to investigate passenger behavior and the demand characteristics of public transport. The destination estimation of public transport is one of the major concerns for the implementation of smart card data. In recent years, numerous studies concerning destination estimation have been carried out—most automatic fare collection (AFC) systems only record boarding information but not passenger alighting information. This study provides a comprehensive review of the practice of using smart card data for destination estimation. The results show that the land use factor is not discussed in more than three quarters of papers and sensitivity analysis is not applied in two thirds of papers. In addition, the results are not validated in half the relevant studies. In the future, more research should be done to improve the current model, such as considering additional factors or making sensitivity analysis of parameters as well as validating the results with multi-source data and new methods. View Full-Text
Keywords: destination estimation; smart card; quality assessment; destination estimation model destination estimation; smart card; quality assessment; destination estimation model

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Li, T.; Sun, D.; Jing, P.; Yang, K. Smart Card Data Mining of Public Transport Destination: A Literature Review. Information 2018, 9, 18.

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