| Title |
Personalized routing for multitudes in smart cities |
| ID_Doc |
41246 |
| Authors |
De Domenico, M; Lima, A; González, MC; Arenas, A |
| Title |
Personalized routing for multitudes in smart cities |
| Year |
2015 |
| Published |
Epj Data Science, 4, 1 |
| DOI |
10.1140/epjds/s13688-015-0038-0 |
| Abstract |
Human mobility in a city represents a fascinating complex system that combines social interactions, daily constraints and random explorations. New collections of data that capture human mobility not only help us to understand their underlying patterns but also to design intelligent systems. Bringing us the opportunity to reduce traffic and to develop other applications that make cities more adaptable to human needs. In this paper, we propose an adaptive routing strategy which accounts for individual constraints to recommend personalized routes and, at the same time, for constraints imposed by the collectivity as a whole. Using big data sets recently released during the Telecom Italia Big Data Challenge, we show that our algorithm allows us to reduce the overall traffic in a smart city thanks to synergetic effects, with the participation of individuals in the system, playing a crucial role. |
| Author Keywords |
personalized routing; collective behavior; smart city; potential energy landscape; big data |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000368069900001 |
| WoS Category |
Mathematics, Interdisciplinary Applications; Social Sciences, Mathematical Methods |
| Research Area |
Mathematics; Mathematical Methods In Social Sciences |
| PDF |
https://epjdatascience.springeropen.com/counter/pdf/10.1140/epjds/s13688-015-0038-0
|