Analysis of Transfer Route Choice on Loop Line with Automatic Fare Collection Data

The loop line plays an important role in meeting the transfer demand and enhancing the accessibility of urban rail transit network. After operation of loop line, the actual effect on transfer flow and passengers’ route choice are crucial for metro management. Some factors may greatly affect route choice on loop line, which are helpful to estimate an individual’s decision-making and improve transfer service quality. The massive data in automated fare collection (AFC) systems opens up a new opportunity to understand the transfer effect on loop line. In this paper, an analysis framework is firstly developed to define typical transfer sub-network formed by secant lines and loop line. Then, a qualitative analysis is conducted to explore the potential impact of spatio-temporal information by passenger route choice in sub-networks. To analyze transfer route choice, a spatio-temporal route match model by mining AFC data is proposed. The case of a typical loop line in Chengdu Metro is applied to demonstrate the capability of the proposed model. Results shows that passengers’ transfer route choice behaviors on loop line could be estimated, which is useful to analyze spatio-temporal distribution of transfer flow, and evaluate the transfer service quality of loop line.