Name
Abstract | ||
|---|---|---|
This study evaluated transit service performance in Seoul using data collected from the Automatic Fare Collection (AFC) system in Seoul. The distance-based fare system in Seoul allows a maximum of four transfers with no additional charges to encourage transit ridership. In order to analyze the transit transfers, this study developed quantitative indicators for public transportation evaluations differentiated from those of previous studies by the fact that it utilizes data mining techniques which incorporate massive amounts of data (over 10 million transits per day) derived from the smart card system. This study not only carried out an evaluation to improve public transportation quality but provided comparative analysis of the mobility handicapped and an evaluation of public transportation users’ regional equity. This evaluative analysis of Level of Services (LOS) for various items is expected to be adopted for analyzing LOS status and generating improvement priorities and to be utilized as an objective database for public transportation policy decisions. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.procs.2015.05.053 | Procedia Computer Science |
Keywords | Field | DocType |
Evaluarion indicators,Level of service,Transit smart card data,K-means clustering | k-means clustering,Data mining,Level of service,Computer science,Computer security,Transport engineering,Smart card,Public transport,Performance measurement,Equity (finance) | Conference |
Volume | ISSN | Citations |
52 | 1877-0509 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ji-Young Song | 1 | 0 | 0.34 |
| Jin Ki Eom | 2 | 0 | 2.03 |
| Kwang Sub Lee | 3 | 0 | 2.03 |
| Jae Hong Min | 4 | 3 | 3.27 |
| Keun Yul Yang | 5 | 0 | 0.68 |