Name
Abstract | ||
|---|---|---|
This paper presents a data-driven method for transit network design that relies on a large sample of user location data available from mobile phone telecommunication networks. Such data provide opportunistic sensing and the means for transit operators to match supply with mobility demand inferred from mobile phone locations. In contrast to previous methods of transit network design, the proposed m... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TITS.2015.2496783 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | Field | DocType |
Mobile handsets,Trajectory,Data mining,Planning,Public transportation,Optimization,Antennas | Mobile identification number,Mobile phone signal,Telecommunications,Mobile phone tracking,Mobile station,Simulation,Computer network,Timing advance,GSM services,Engineering,Roaming,Radio access network | Journal |
Volume | Issue | ISSN |
17 | 6 | 1524-9050 |
Citations | PageRank | References |
10 | 0.60 | 16 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabio Pinelli | 1 | 972 | 50.96 |
| R. Nair | 2 | 58 | 7.69 |
| Francesco Calabrese | 3 | 242 | 15.93 |
| Michele Berlingerio | 4 | 510 | 28.92 |
| Giusy Di Lorenzo | 5 | 574 | 34.54 |
| Marco Luca Sbodio | 6 | 223 | 20.52 |