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Digital Library

of the European Council for Modelling and Simulation

 

Title:

Detecting Traffic Conditions Model Based On Clustering Nodes Situations In VANET

Authors:

Ayman Abufanas, Evtim Peytchev

Published in:

 

 

(2015).ECMS 2015 Proceedings edited by: Valeri M. Mladenov, Grisha Spasov, Petia Georgieva, Galidiya Petrova, European Council for Modeling and Simulation. doi:10.7148/2015

 

 

ISBN: 978-0-9932440-0-1

 

29th European Conference on Modelling and Simulation,

Albena (Varna), Bulgaria, May 26th – 29th, 2015

 

Citation format:

Ayman Abufanas, Evtim Peytchev (2015). Detecting Traffic Conditions Model Based On Clustering Nodes Situations In VANET, ECMS 2015 Proceedings edited by: Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova  European Council for Modeling and Simulation. doi:10.7148/2015-0511

DOI:

http://dx.doi.org/10.7148/2015-0511

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.

 

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