Abstract : 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.
? In existing studies, the factors considered in the model are mainly divided into three categories, that’s the public transport network, operation (e.g., network distance, density of bus route, density of station, time table), travel information (e.g., boarding time, boarding station, travel time, walking distance ) and land use (e.g., residential floor area, commercial floor area, cultural floor area).
? The proposed cards should be validated by the existing ETM in use. Normal Ticket is to be given by the conductor through ETM after deducting the required fare just by showing this card in front of ETM.
? The area where viewing, directing and monitoring the Smart travel card transactions.
? The analysis of the possible problems in present method can provide better advice for the future algorithm improvement. Problems may be generated at all stage of destination inferring.
? In order to prevent this problem from happening, cleaning the data according different rules is essential.
? The other possible problem is that many trips cannot be matched successfully.
? But in one study, validation have a significant impact on alight station estimation, especially in small sample size.
? The AFC system transaction data often has some potential problems during data collecting, which may be caused by software, erroneous data, faulty hardware or the users.
• The Proposed card should meets the specifications of the Common Mobility Cards for having required interoperability with the provisions to add Transport service operators in addition to MTC as and when required.
• EOI firms are requested to propose any suitable BOM & BOQ as per the table given above for CCH, Divisional, Regional, PoS data centers individually/ separately which may be appropriate for the Smart Travel Card project.
• EoI firms are requested to propose the suitable implementation plan from the data of award of LOA.
• Pre-EOI meeting is proposed at PTCS Office to clarify the queries. EOI Firms may attend the meeting.
? The data can be used in various fields such as analysis of transit riders’ travel patterns, behavior analysis, performance assessment of bus transport reform and planning of the public transportation system.
? In the process of model application, many researchers continue to revise these assumptions in order to obtain better inferring performance.
? When inferring the destination of alighting station using smart card, researchers considered different factors, to some extent, these factors affected the quality and performance of the model.
? However, these scholars used various methods and obtained different matching rate.
? These three basic assumptions especially the latter two hypotheses are widely used in research including bus-bus, bus-rail and rail-rail trips.
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