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A trajectory restoration algorithm for low-sampling-rate floating car data and complex urban road networks / Bozhao Li in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 4 (April 2021) . - pp 717 - 740 Titre : A trajectory restoration algorithm for low-sampling-rate floating car data and complex urban road networks Type de document : Article/Communication Auteurs : Bozhao Li, Auteur ; Zhongliang Cai, Auteur ; Mengjun Kang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 717 - 740 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] appariement de cartes [Termes IGN] chemin le plus court, algorithme du [Termes IGN] Pékin (Chine) [Termes IGN] réseau routier [Termes IGN] taux d'échantillonnage [Termes IGN] trafic routier [Termes IGN] trajectoire (véhicule non spatial) [Termes IGN] zone urbaine Résumé : (auteur) Low-sampling-rate floating car data (FCD) are more challenging than those with high-sampling-rate FCD for map matching (MM) algorithms. Some MM algorithms for low-sampling-rate FCD lack sufficient efficiency nor accuracy, especially related to complex urban road networks. This paper proposes a new method named the trajectory restoration algorithm, which is based on geometry MM algorithms to ensure efficiency and accuracy. The proposed algorithm adopts the modified A* shortest path algorithm to reduce the number of function calls and fully considers road network topology and historical matched points to improve its accuracy. We test the efficiency and accuracy of the trajectory restoration algorithm with FCD data for the complex urban road networks in Beijing. The results have strong continuity which greatly improves the utilization of FCD. We show that the proposed algorithm outperforms related MM methods in efficiency and accuracy and its robustness to restore trajectories of both high and low sampling rates in complex urban road networks. Numéro de notice : A2021-269 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2020.1825721 Date de publication en ligne : 20/10/2020 En ligne : https://doi.org/10.1080/13658816.2020.1825721 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97326 [article]