Transit smart card data mining for passenger origin information extraction

The automated fare collection(AFC) system,also known as the transit smart card(SC) system,has gained more and more popularity among transit agencies worldwide.Compared with the conventional manual fare collection system,an AFC system has its inherent advantages in low labor cost and high efficiency for fare collection and transaction data archival.Although it is possible to collect highly valuable data from transit SC transactions,substantial efforts and methodologies are needed for extracting such data because most AFC systems are not initially designed for data collection.This is true especially for the Beijing AFC system,where a passenger’s boarding stop(origin) on a flat-rate bus is not recorded on the check-in scan.To extract passengers’ origin data from recorded SC transaction information,a Markov chain based Bayesian decision tree algorithm is developed in this study.Using the time invariance property of the Markov chain,the algorithm is further optimized and simplified to have a linear computational complexity.This algorithm is verified with transit vehicles equipped with global positioning system(GPS) data loggers.Our verification results demonstrated that the proposed algorithm is effective in extracting transit passengers’ origin information from SC transactions with a relatively high accuracy.Such transit origin data are highly valuable for transit system planning and route optimization.     

Transit smart card data mining for passenger origin information extraction

The automated fare collection (AFC) system,also known as the transit smart card (SC) system,has gained more and more popularity among transit agencies worldwide.Compared with the conventional manual fa...     

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开天窗中部槽天窗型式的选择

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一种平衡设计压控振荡器和自动频率校准的快速锁定宽带频率综合器

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Two types of a passive safety containment for a near future BWR with active and passive safety systems

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Aeroelastic analysis of smart composite structures in hygro-thermal environment

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