Andrea Dalla Torre (Avtor), P. Gallo (Avtor), Donatella Gubiani (Avtor), Chris Marshall (Avtor), Angelo Montanari (Avtor), Federico Pittino (Avtor), Andrea Viel (Avtor)

Povzetek

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;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UNG - Univerza v Novi Gorici
UDK: 004.8
COBISS: 5404411 Povezava se bo odprla v novem oknu
ISSN: 1009-5020
Št. ogledov: 2694
Št. prenosov: 95
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

URN: URN:SI:UNG
Vrsta dela (COBISS): Delo ni kategorizirano
Strani: str. 89-106
Letnik: ǂVol. ǂ22
Zvezek: ǂno. ǂ2
Čas izdaje: 2019
DOI: 10.1080/10095020.2019.1616933
ID: 11156296