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Bus arrival time calculation model based on smart card data.

Authors :
Zhou, Yuyang
Yao, Lin
Chen, Yanyan
Gong, Yi
Lai, Jianhui
Source :
Transportation Research Part C: Emerging Technologies. Jan2017, Vol. 74, p81-96. 16p.
Publication Year :
2017

Abstract

Bus arrival time is usually estimated using the boarding time of the first passenger at each station. However, boarding time data are not recorded in certain double-ticket smart card systems. As many passengers usually swipe the card much before their alighting, the first or the average alighting time cannot represent the actual bus arrival time, either. This lack of data creates difficulties in correcting bus arrival times. This paper focused on developing a model to calculate bus arrival time that combined the alighting swiping time from smart card data with the actual bus arrival time by the manual survey data. The model was built on the basis of the frequency distribution and the regression analysis. The swiping time distribution, the occupancy and the seating capacity were considered as the key factors in creating a method to calculate bus arrival times. With 1011 groups of smart card data and 360 corresponding records from a manual survey of bus arrival times, the research data were divided into two parts stochastically, a training set and a test set. The training set was used for the parameter determination, and the test set was used to verify the model’s precision. Furthermore, the regularity of the time differences between the bus arrival times and the card swiping times was analyzed using the “trend line” of the last swiping time distribution. Results from the test set achieved mean and standard error rate deviations of 0.6% and 3.8%, respectively. The proposed model established in this study can improve bus arrival time calculations and potentially support state prediction and service level evaluations for bus operations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0968090X
Volume :
74
Database :
Academic Search Index
Journal :
Transportation Research Part C: Emerging Technologies
Publication Type :
Academic Journal
Accession number :
120411522
Full Text :
https://doi.org/10.1016/j.trc.2016.11.014