The Impact of a New Urban Rail Transit Line on the Travel Patterns of High-Stability Passengers

Le résumé fourni par la source

Using the smart card data of Nanjing Metro during the corresponding periods in 2016 and 2017, this paper employs an improved k-means algorithm to categorize passengers into five clusters based on spatiotemporal indicators representing the level of travel modes stability. The clustering outcomes reveal a notable increase in the number of passengers at each stability level in 2017 compared to 2016, with the largest surge observed among high-stability passengers. Additionally, various factors, including degree centrality, node-center distance coefficient of the station, and distance to Xinjiekou station, exert a significant positive influence on the rate of travel volume growth at a station and the disparity in the share rate before and after the inception of the new line. These findings indicate that the new line not only attracts new passengers but also effectively redistributes high-stability passengers from adjacent lines, thereby facilitating the alleviation of congestion on existing lines and stations.

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