@inproceedings{3c2d71ed911b4d02b175e03cbd8166c9,
title = "Spatio-Temporal Ridership Characteristics of Nanjing Rail Transit Based on Smart Card Data",
abstract = "Smart card data (SCD) has received increasing interest as a new source of data for investigating passengers{\textquoteright} spatio-temporal mobility patterns. A total of 22.84 million SCD records during two weeks in 2017 were collected by Nanjing rail transit. The temporal distribution of ridership and passenger travel time distribution was discussed. The spatial distribution of ridership was analyzed under three levels: region, sub-district, and station. The results show that the ridership fluctuation in weekdays follows a bimodal pattern, and the average travel time per passenger is about 30 min. The inbound and outbound ridership in each region district is symmetrical, but the spatial distribution of ridership varies greatly in different sub-district areas. The inbound ridership in the morning and evening peak hours on station level is mainly concentrated in residential and business areas, respectively. The research conclusions can provide technical support for Nanjing rail transit operation organization and ridership forecast analysis.",
author = "Min Ma and Dawei Hu and Steven Chien and Xing Yang and Yiheng Shao and Zhuanglin Ma",
note = "Publisher Copyright: {\textcopyright} ASCE.; 23rd COTA International Conference of Transportation Professionals: Innovation-Empowered Technology for Sustainable, Intelligent, Decarbonized, and Connected Transportation, CICTP 2023 ; Conference date: 14-07-2023 Through 17-07-2023",
year = "2023",
doi = "10.1061/9780784484869.057",
language = "English (US)",
series = "CICTP 2023: Innovation-Empowered Technology for Sustainable, Intelligent, Decarbonized, and Connected Transportation - Proceedings of the 23rd COTA International Conference of Transportation Professionals",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "585--595",
editor = "Yanyan Chen and Jianming Ma and Guohui Zhang and Haizhong Wang and Lijun Sun and Zhengbing He",
booktitle = "CICTP 2023",
address = "United States",
}