Impact of Planned Shutdown of Suburban Rail Transit on Travel Transfer of Frequent Passengers

Passenger travel in rail transit networks is affected by changes in network structure and operating conditions, and individual travel preferences respond differently to these changes. In order to analyze the impact of a planned shutdown of a suburban rail line on the travel transfer of frequent passengers, a passenger travel feature characterization method considering transfer types and transfer ratios was proposed, and the passenger's feature-temporal (F-T) matrix was generated by combining time period attributes. The similarity between F-T matrices was calculated by an improved Euclidean distance to achieve the similarity measurement of F-T matrices. A two-step clustering method of K-Means clustering and hierarchical clustering (KMHC) based on the similarity matrix was proposed to partition the affected passenger groups, and the factors affecting passenger transfer were analyzed. The Kunshan section of Shanghai Rail Transit Line 11 during COVID-19 was taken as an example to verify the method. The research results show that after the shutdown of the Kunshan section, there are five main groups of travel transfer impacts of frequent passengers, accounting for 94.4% of the total number of frequent passengers. The transfer distance, commuting time and travel frequency of the affected groups are obviously different, which are important factors influencing the travel choices of frequent passengers after the section shutdown. The method can serve as a reference for other planned shutdown scenarios, and can also provide support for predicting changes in network passenger flow, and optimizing driving and passenger transportation organization plans after the section shutdown. © 2024 Science Press. All rights reserved.