Détail de l'auteur
Auteur Ge Cui |
Documents disponibles écrits par cet auteur (1)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externes
Hidden Markov map matching based on trajectory segmentation with heading homogeneity / Ge Cui in Geoinformatica, vol 25 n° 1 (January 2021)
[article]
Titre : Hidden Markov map matching based on trajectory segmentation with heading homogeneity Type de document : Article/Communication Auteurs : Ge Cui, Auteur ; Wentao Bian, Auteur ; Xin Wang, Auteur Année de publication : 2021 Article en page(s) : pp 179 - 206 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement de cartes
[Termes IGN] appariement de données localisées
[Termes IGN] modèle de Markov caché
[Termes IGN] réseau routier
[Termes IGN] segmentation
[Termes IGN] trajectographie par GPS
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Map matching is to locate GPS trajectories onto the road networks, which is an important preprocessing step for many applications based on GPS trajectories. Currently, hidden Markov model is one of the most widely used methods for map matching. However, both effectiveness and efficiency of conventional map matching methods based on hidden Markov model will decline in the dense road network, as the number of candidate road segments enormously increases around GPS point. To overcome the deficiency, this paper proposes a segment-based hidden Markov model for map matching. The proposed method first partitions GPS trajectory into several GPS sub-trajectories based on the heading homogeneity and length constraint; next, the candidate road segment sequences are searched out for each GPS sub-trajectory; last, GPS sub-trajectories and road segment sequences are matched in hidden Markov model, and the road segment sequences with the maximum probability is identified. A case study is conducted on a real GPS trajectory dataset, and the experiment result shows that the proposed method improves the effectiveness and efficiency of the conventional HMM map matching method. Numéro de notice : A2021-094 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00429-4 Date de publication en ligne : 02/01/2021 En ligne : https://doi.org/10.1007/s10707-020-00429-4 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96934
in Geoinformatica > vol 25 n° 1 (January 2021) . - pp 179 - 206[article]