Dwell Time Estimation Using Real-Time Train Operation and Smart Card-Based Passenger Data: A Case Study in Seoul, South Korea

Yoonseok Oh, Young-Ji Byon, Ji Young Song, Ho-Chan Kwak, Seungmo Kang
2020 Applied Sciences  
Dwell time is a critical factor in constructing and adjusting railway timetables for efficient and accurate operation of railways. This paper develops dwell time estimation models for a Shinbundang line (S line) in Seoul, South Korea using support vector regression (SVR), multiple linear regression (MLR), and random forest (RF) techniques utilizing archived real-time metro operation data along with smart card-based passenger information. In the first phase of this research, the collected data
more » ... he collected data are processed to extract boarding and alighting passenger counts and observed dwell times of each train at all stations of the S line under the current operational environment. In the second phase, we develop SVR, MLR, and RF-based dwell time estimation models. It is found that the SVR-based model successfully estimates the dwell times within 10 s of differences for 84.4% of observed data. The results of this paper are especially beneficial for autonomous railway operations that need constructing and maintaining dynamic railway timetables that require reliable dwell time predictions in real-time.
doi:10.3390/app10020476 fatcat:j7syrti5bnad3hhlcmfolgkv5e