| Title |
GIS-Based Commute Analysis Using Smart Card Data: A Case Study of Multi-Mode Public Transport for Smart City |
| ID_Doc |
37435 |
| Authors |
Zhou, YY; Yao, L; Jiang, Y; Chen, YY; Gong, Y |
| Title |
GIS-Based Commute Analysis Using Smart Card Data: A Case Study of Multi-Mode Public Transport for Smart City |
| Year |
2016 |
| Published |
|
| DOI |
10.1007/978-3-662-49155-3_8 |
| Abstract |
This paper utilized the one-week smart card data (SCD) and the control passenger flow survey to analyze the commute travel time and the passenger flow distribution in the multi-mode public transport. To research the commute pattern of the central business district (CBD), there were three large-scale residence communities selected for the survey areas. Based on SCD in the double ticket system, the average travel time and the passenger volume were estimated through clustering "the alighting time" and filling none value. As a result, the visualization of the station attraction and the travel time under multi-mode public transport was presented through the application of GIS. The analysis of the commute pattern is aimed to make a scientific guidance for commuters on the traffic model choice as well as provide a quantitative basis for the development of the smart city. |
| Author Keywords |
Smart card data; Multi-mode public transport; Travel time; Station attraction; Smart city |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000373275200008 |
| WoS Category |
Computer Science, Interdisciplinary Applications; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
https://doi.org/10.1007/978-3-662-49155-3_8
|