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Semantic Management of Urban Traffic Congestion

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dc.contributor.author Shakil, Arshad
dc.contributor.author Juric, Radmila
dc.date.accessioned 2020-01-04T07:21:56Z
dc.date.available 2020-01-04T07:21:56Z
dc.date.issued 2020-01-07
dc.identifier.isbn 978-0-9981331-3-3
dc.identifier.uri http://hdl.handle.net/10125/63873
dc.description.abstract Urban traffic congestion is a problem which affects the world and is related to the massive urbanization and excessive number of cars on our streets. This causes a variety of problems, from economical/financial and health-related, to environmental warnings caused by high CO2 and NO2 emissions. This paper proposes a novel software engineering solution, which generates a software application aimed at individual drivers on urban roads, in order to help and ease overall congestion. The novelty is twofold. We target individual drivers in order to motivate them to re-think the purpose and goals of each journey they take. Consequently, the proposed software application enables reasoning upon various options an individual driver may have and helps in choosing the best possible solution for an individual. Our software application utilizes reasoning with SWRL enabled OWL ontologies, which can be hosted by any software application we run in our cars, ready to assist in driving, and implemented in Android / iOS environments.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 53rd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Decision Support for Smart Cities
dc.subject owl
dc.subject reasoning
dc.subject swrl
dc.subject traffic congestion
dc.title Semantic Management of Urban Traffic Congestion
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2020.134
Appears in Collections: Decision Support for Smart Cities


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