Name
Abstract | ||
|---|---|---|
Identifying the urban transportation corridor is very crucial in transportation planning, since planning with insufficient data verification often leads to wrong estimation of actual demand. In the era of big data, the pervasive penetration of mobile phones enables us to collect large-scale trajectory data of urban residents every day. These big data bring new opportunity to the data-driven and user-oriented transportation planning. Inspired by eigen-line concepts, this paper uses mobile phone users' record to identify transportation corridors in Shanghai. First, the transportation eigen-lines are identified by OD cluster method based on influence between OD links. Then, the obtained eigen-lines are testified by comparing with the real road network and population flow map to testify. Finally, the transportation corridors are drawn according to the determined eigen-lines and priori knowledge. The identified corridors reveal the spatial travel patterns of urban residents. These results help us understand the city transportation structure and travel demand features better. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ISC2.2015.7366203 | 2015 IEEE First International Smart Cities Conference (ISC2) |
Keywords | Field | DocType |
Eigen-line,mobile phone data,OD projection,transportation corridor | Population,Data verification,Advanced Traffic Management System,Computer science,Computer security,Transport engineering,Decision support system,Flow map,Mobile phone,Big data,Transportation planning | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wang Yanwei | 1 | 0 | 0.34 |
| Li Li | 2 | 581 | 109.68 |
| Yu Juntang | 3 | 0 | 0.34 |
| Li Zhiheng | 4 | 77 | 13.27 |
| Wang Shuofeng | 5 | 4 | 2.13 |
| Ke Ruimin | 6 | 89 | 6.69 |