Personalized routing for multitudes in smart cities
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s13688-015-0038-0.pdf
Size
1.89 MB
Format
Adobe PDF
Checksum (MD5)
49fa35ec34396f9438b6f33a70638cde
Author(s)
De Domenico, Manlio
Lima, Antonio
Arenas, Alex
Gonzalez, Marta C.
Date Issued
January 2015
Journal
EPJ Data Science
Publisher
Springer
Citation
De Domenico, Manlio, Antonio Lima, Marta C Gonzalez, and Alex Arenas. “Personalized Routing for Multitudes in Smart Cities.” EPJ Data Science 4, no. 1 (January 28, 2015).
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1140/epjds/s13688-015-0038-0
