Recognizing metro-bus transfers from smart card data |
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| Authors: | De Zhao Wei Wang Chenyang Li Yanjie Ji Xiaojian Hu Wenfu Wang |
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| Institution: | 1. Department of Civil and Environmental Engineering, National University of Singapore, Singapore;2. Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing, People’s Republic of China;3. Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing, People’s Republic of China;4. School of Civil and Environmental Engineering, University of New South Wales, Kingsford, NSW, Australia;5. Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, Canada |
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| Abstract: | Transfer points between metro and bus services remain an elusive, yet critical junction for transportation practitioners. Based on massive Smart Card (SC) data, previous studies apply a one-size-fits-all criterion to discriminate between transfers. However, this is not sufficiently convincing for different transfer pairs. To counter this problem, this study applies an association rules algorithm and cluster analysis to recognize metro-to-bus transfers using SC data, and demonstrates transfer recognition in a case study based on SC data collected during a week in Nanjing, China. It is shown that 85% of the transfer-recognition results are quite stable through the whole week, and the median transfer time between metro and bus is below 20?min. The method proposed in this study can be used to identify the busiest transfer points and to obtain average transfer times, which facilitates a smarter and more efficient public transit network. |
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| Keywords: | Transit metro-to-bus transfer association rules cluster analysis smart card data case study |
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