Node, place, ridership, and time model for rail-transit stations: a case study

• Published in: Scientific reports Vol. 12; no. 1; pp. 16120 - 16
• Main Authors: Amini Pishro, Ahad, Yang, Qihong, Zhang, Shiquan, Amini Pishro, Mojdeh, Zhang, Zhengrui, Zhao, Yana, Postel, Victor, Huang, Dengshi, Li, WeiYu
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 27.09.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 639/166/986; 639/705/1041; 639/705/1042; 639/705/1046; 639/705/531; 704/844/685; Case studies; Development projects; High speed rail; Humanities and Social Sciences; Land use; multidisciplinary; Neighborhoods; Public transportation; Science; Science (multidisciplinary); Traffic congestion
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-20209-4

Nowadays, Transit-Oriented Development (TOD) plays a vital role for public transport planners in developing potential city facilities. Knowing the necessity of this concept indicates that TOD effective parameters such as network accessibility (node value) and station-area land use (place value) should be considered in city development projects. To manage the coordination between these two factors, we need to consider ridership and peak and off-peak hours as essential enablers in our investigations. To aim this, we conducted our research on Chengdu rail-transit stations as a case study to propose our Node-Place-Ridership-Time (NPRT) model. We applied the Multiple Linear Regression (MLR) to examine the impacts of node value and place value on ridership. Finally, K-Means and Cube Methods were used to classify the stations based on the NPRT model results. This research indicates that our NPRT model could provide accurate results compared with the previous models to evaluate rail-transit stations.