Title:	Detecting anomalous trajectories and traffic services
Authors:	Ismael, Mazen
Citation:	STEINBERGER, Josef ed.; ZÍMA, Martin ed.; FIALA, Dalibor ed.; DOSTAL, Martin ed.; NYKL, Michal ed. Data a znalosti 2017: sborník konference, Plzeň, Hotel Angelo 5. - 6. října 2017. 1. vyd. Plzeň: Západočeská univerzita v Plzni, 2017, s. 192-197. ISBN 978-80-261-0720-0.
Issue Date:	2017
Publisher:	Západočeská univerzita v Plzni
Document type:	konferenční příspěvek conferenceObject
URI:	https://www.zcu.cz/export/sites/zcu/pracoviste/vyd/online/DataAZnalosti2017.pdf http://hdl.handle.net/11025/26362
ISBN:	978-80-261-0720-0
Keywords:	anomální trajektorie;sémantická poloha;doprava;iBAT/iBOAT
Keywords in different language:	anomalous trajectory;semantic location;traffic;iBAT/iBOAT
Abstract in different language:	Among the traffic studies; the importance of detecting anomalous trajectories of vehicles rises to support many services, starting from securing and safety services to the maps and navigation services. The combination of many methods and concepts could offer interesting advantages, and iBAT (Isolation-Based Anomalous Trajectory) is one of the advanced frameworks which detect anomalous traffic trajectories. iBOAT (Isolation Based Online Trajectory) came after that as a version of iBAT able to process online data. Be-side of that, using semantic locations could support the navigations studies, and increase the maps' accuracy. In fact, developing the iBOAT framework with use semantic ocation could bring out interesting results. The aim of this paper is to present the progress of detecting anomalous driving patterns from GPS trajecto-ries, which will be achieved by using the concept of semantic locations for improving the scene partitioning.
Rights:	© Západočeská univerzita v Plzni
Appears in Collections:	Data a znalosti 2017 Data a znalosti 2017

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