20.500.12556/RUNG-4386-26571330-0722-f33b-9fe2-22b8d20ceb74
A map-matching algorithm dealing with sparse cellular fingerprint observations
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.
Map-matching algorithm
trajectory
cellular fingerprint
Hidden Markov Model
true
true
false
Angleški jezik
Ni določen
Delo ni kategorizirano
2019-02-06 06:42:43
2019-06-11 13:45:38
2023-06-09 03:29:41
0000-00-00 00:00:00
2019
0
0
18
2
22
2019
0000-00-00
NiDoloceno
NiDoloceno
NiDoloceno
0000-00-00
0000-00-00
0000-00-00
5404411
10.1080/10095020.2019.1616933
URN:SI:UNG:REP:C5IDSXWZ
A_map_matching_algorithm_dealing_with_sparse_cellular_fingerprint_observations.pdf
A_map_matching_algorithm_dealing_with_sparse_cellular_fingerprint_observations.pdf
1
DE7EAC6618E2E82F887D344FE902A615
170d6932e4ed2118bfda0e954405a229731ed3c168c2c94b6440cc5d86c9781f
5ad5bf6f-05cf-11ee-9c48-5ef991fed68f
https://repozitorij.ung.si/Dokument.php?lang=slv&id=18373
Univerza v Novi Gorici
0
0
0