Detecting Traffic Conditions Model Based On Clustering Nodes Situations In VANET

Abufanas, A. and Peytchev, E. ORCID: 0000-0001-5256-4383, 2015. Detecting Traffic Conditions Model Based On Clustering Nodes Situations In VANET. In: V.M. Mladenov, G. Spasov, P. Georgieva and G. Petrova, eds., Proceedings of the 29th European Conference on Modelling and Simulation, Albena, Varna, Bulgaria, 26-29 May 2015. European Council for Modelling and Simulation, pp. 511-515. ISBN 9780993244001

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Abstract

In the last decade, cooperative vehicular network has been one of the most studied areas for developing the intelligent transportation systems (ITS). It is considered as an important approach to share the periodic traffic situations over vehicular ad hoc networks (VANETs) to improve efficiency and safety over the road. However, there are a number of issues in exchanging traffic data over high mobility of VANET, such as broadcast storms, hidden nodes and network instability.
This paper proposes a new model to detect the traffic conditions using clustering traffic situations that are gathered from the nodes (vehicles) in VANET. The model designs new principles of multi-level clustering to detect the traffic condition for road users. Our model (a) divides the situations of vehicles into clusters, (b) designs a set of metrics to get the correlations among vehicles and (c) detects the traffic condition in certain areas. These metrics are simulated using the network simulator environment (NS-3) to study the effectiveness of the model.

Item Type: Chapter in book
Creators: Abufanas, A. and Peytchev, E.
Publisher: European Council for Modelling and Simulation
Date: 2015
Identifiers:
NumberType
10.7148/2015-0511DOI
Divisions: Schools > School of Science and Technology
Depositing User: Jill Tomkinson
Date Added: 25 Nov 2015 16:29
Last Modified: 09 Jun 2017 13:57
URI: http://irep.ntu.ac.uk/id/eprint/26497

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