Repozitorij Univerze v Novi Gorici

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Naslov:A map-matching algorithm dealing with sparse cellular fingerprint observations
Avtorji:ID Dalla Torre, Andrea (Avtor)
ID Gallo, Paolo (Avtor)
ID Gubiani, Donatella (Avtor)
ID Marshall, Chris (Avtor)
ID Montanari, Angelo (Avtor)
ID Pittino, Federico (Avtor)
ID Viel, Andrea (Avtor)
Datoteke:.pdf A_map_matching_algorithm_dealing_with_sparse_cellular_fingerprint_observations.pdf (3,93 MB)
MD5: DE7EAC6618E2E82F887D344FE902A615
 
Jezik:Angleški jezik
Vrsta gradiva:Delo ni kategorizirano
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:UNG - Univerza v Novi Gorici
Opis:The widespread availability of mobile communication makes mobile devices a resource for the collection of data about mobile infrastructures and user mobility. In these contexts, the problem of reconstructing the most likely trajectory of a device on the road network on the basis of the sequence of observed locations (map-matching problem) turns out to be particularly relevant. Different contributions have demonstrated that the reconstruction of the trajectory of a device with good accuracy is technically feasible even when only a sparse set of GNSS positions is available. In this paper, we face the problem of coping with sparse sequences of cellular fingerprints. Compared to GNSS positions, cellular fingerprints provide coarser spatial information, but they work even when a device is missing GNSS positions or is operating in an energy saving mode. We devise a new map-matching algorithm, that exploits the well-known Hidden Markov Model and Random Forests to successfully deal with noisy and sparse cellular observations. The performance of the proposed solution has been tested over a medium-sized Italian city urban environment by varying both the sampling of the observations and the density of the fingerprint map as well as by including some GPS positions into the sequence of fingerprint observations.
Ključne besede:Map-matching algorithm, trajectory, cellular fingerprint, Hidden Markov Model
Leto izida:2019
Št. strani:18
Številčenje:22, 2
PID:20.500.12556/RUNG-4386-26571330-0722-f33b-9fe2-22b8d20ceb74 Novo okno
COBISS.SI-ID:5404411 Novo okno
DOI:10.1080/10095020.2019.1616933 Novo okno
NUK URN:URN:SI:UNG:REP:C5IDSXWZ
Datum objave v RUNG:11.06.2019
Število ogledov:4288
Število prenosov:101
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:Geo-spatial Information Science
Založnik:Taylor and Francis
Leto izida:2019
ISSN:1009-5020

Licence

Licenca:CC BY-NC 4.0, Creative Commons Priznanje avtorstva-Nekomercialno 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by-nc/4.0/deed.sl
Opis:Licenca Creative Commons, ki prepoveduje komercialno uporabo, vendar uporabniki ne rabijo upravljati materialnih avtorskih pravic na izpeljanih delih z enako licenco.
Začetek licenciranja:06.02.2019

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