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Daniel Febrian Sengkey, Widyawan Widyawan and I Wayan Mustika, "Vehicle Classification in Traffic Density Estimation Using Vehicular Ad Hoc Network," Proceedings of 10th International Forum on Strategic Technology (IFOST 2015), Bali, Indonesia, June 2015, pp. 387–392.


Technological advancement enables information technology support for myriad aspects of human life including transportation. The Intelligent Transportation System (ITS) is a widely known field where technological supports are added to enhance the transport network. The applications of ITS are broad, one of them is to estimate the vehicular traffic density. Several methods have been developed in this field e.g. using inductive loop and traffic surveillance camera. Vehicular Ad Hoc Network (VANET) is an emerging technology which allows inter-vehicle information exchange. Utilisation of the exchanged information as a source to estimate traffic density has been studied by several researches. However, most of their concerns are the algorithm used to estimate the density based on the number of vehicles. In this paper we proposed a simple application model to incorporate vehicle classification in traffic density estimation using VANET. The goal was achieved by adding certain data in broadcasted beacons. Validation of the model was done via computer simulation. Simulation result shows that vehicle in broadcast domain was able to identify its neighbours with their types respectively.

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Daniel Febrian Sengkey
Widyawan Widyawan
I Wayan Mustika

BibTeX reference

    address = {Bali, Indonesia},
    author = {Sengkey, Daniel Febrian and Widyawan, Widyawan and Mustika, I Wayan},
    booktitle = {10th International Forum on Strategic Technology (IFOST 2015)},
    month = {6},
    pages = {387--392},
    title = {{Vehicle Classification in Traffic Density Estimation Using Vehicular Ad Hoc Network}},
    year = {2015},

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