Recognizing metro-bus transfers from smart card data

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.

KEYWORDS:

• Transit
• metro-to-bus transfer
• association rules
• cluster analysis
• smart card data
• case study

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

De Zhao http://orcid.org/0000-0002-3995-4878

Yanjie Ji http://orcid.org/0000-0002-7172-3818

Additional information

Funding

This research is supported by the National Natural Science Foundation of China [grant numbers 71701047 and 51478112].