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Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data / Lulian Tang in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)  

Public [article]  inCartography and Geographic Information Science > vol 43 n° 5 (November 2016) . - pp 417 - 426 Titre : Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data Type de document : Article/Communication Auteurs : Lulian Tang, Auteur ; Zihan Kan, Auteur ; Xia Zhang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 417 - 426 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] carrefour [Termes descripteurs IGN] coordonnées GPS [Termes descripteurs IGN] dimension temporelle [Termes descripteurs IGN] données massives [Termes descripteurs IGN] fréquence [Termes descripteurs IGN] itinéraire [Termes descripteurs IGN] logique floue [Termes descripteurs IGN] taxi [Termes descripteurs IGN] temps de trajet [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] Wuhan (Chine) Résumé : (Auteur) Intersections are the critical parts where different traffic flows converge and change directions, forming “bottlenecks” and “clog points” in urban traffic. Intersection travel time is an important parameter for public route planning, traffic management, and engineering optimization. Based on low-frequency spatial-temporal Global Positioning System (GPS) trace data, this article presents a novel method for estimating intersection travel time. The proposed method first analyzes the different travel patterns of vehicles through an intersection, then determines the range of an intersection dynamically and reasonably, and obtains traffic flow speed and delay at the intersection under different travel patterns using a fuzzy fitting approach. Finally, the average intersection travel time is estimated from traffic flow speed and delay and intersection range in different travel patterns. Wuhan road network data and GPS trace data from taxicabs were tested in the experiments and the results show that the proposed method can improve the accuracy of travel time estimation at city intersections. Numéro de notice : A2016-692 Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1080/15230406.2015.1130649 En ligne : https://doi.org/10.1080/15230406.2015.1130649 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82029 [article]

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