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Abstract
In recent years, to fix the shortcomings of traditional bus service and meet the diversified needs of passengers, a new type of transit system, the customized bus (CB), has been proposed. However, how to define and mine the CB’s demand is still less being addressed. Since the data of bus smart cards can provide more travel information, it makes the mining of potential CB’s demand spots more possible, which can be helpful in CB service design. In order to mine the demand spots more scientifically, this paper, for the first time, quantitatively defines the CB demand characteristics and criteria of selecting potential area, and develops a demand hotspots extraction methodology for CB. The methodology solves two issues primarily. One is how to organize massive smart card data and obtain the space-time pattern and mobility of passenger efficiently; the other is how to mix the CB demand characteristics into the method. This demand spots extraction method can generate multi-style maps, including the heat and origin-destination maps, for spatial cluster of CB’s demand spots in rational areas in terms of the CB demand characteristics based on geographic information system. By using the bus smart card data in Beijing, China, this paper carries out a case study to validate the method. The empirical data mining analysis shows that our proposed method can define demand spots ideally. Our work can provide a valuable reference for decision makers to design CB system.
Highlights
Customized Bus (CB) is a new and innovative demandresponsive transportation system (DRTS) that provides advanced, user-oriented transportation services to specific customers, especially commuters, by using online information platforms to aggregate similar travel demand patterns [1]
A common framework is provided, which facilitates the migration of the methodology on various cities which adopt the entry-exit charging system
In view of the good performance of proposed method in the case study of Beijing, four recommendations are proposed to the metropolitan public transportation (PT) planners
Summary
Customized Bus (CB) is a new and innovative demandresponsive transportation system (DRTS) that provides advanced, user-oriented transportation services to specific customers, especially commuters, by using online information platforms to aggregate similar travel demand patterns [1]. POTENTIAL PROBLEMS OF USING BUS SMART CARD DATA AND SOLUTIONS It is undeniable that at present, the smart card being the source of CB’s demand still has its limitations, which can be divided into three types: (1) the problems in the operation of the AFC system, including potential fare evasion and the erroneous data (missing data, illogical values and duplicate transactions) generated by the AFC; (2) the adoption the entry-only charging system, that is, only taping the smart card once during the whole ride; (3) the usage volume/rate of the smart card The existence of these problems will affect the study of subsequent bus cards, resulting in analytical errors. Aiming at above research limitations, this paper seeks to provide a general method for mining CB demand spots during the peak period based on bus smart card data.
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