Road traffic congestion detection in VANET networks | Zendy

Badreddine Cherkaoui | Zendy; Abderrahim BeniHssane | Zendy; Mohamed El Fissaoui | Zendy; Mohammed Erritali | Zendy

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Road traffic congestion detection in VANET networks

Author(s) -

Badreddine Cherkaoui,

Abderrahim BeniHssane,

Mohamed El Fissaoui,

Mohammed Erritali

Publication year - 2019

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2019.04.165

Subject(s) - computer science , vehicular ad hoc network , traffic congestion , traffic congestion reconstruction with kerner's three phase theory , vehicle information and communication system , floating car data , state (computer science) , computer network , traffic optimization , road traffic , telecommunications , transport engineering , wireless ad hoc network , wireless , algorithm , engineering

In urban areas, the problem of congestion in road traffic presents itself as a very persistent problem which requires solutions. During a traffic jam, several resources are wasted, such as time, fuel and many other resources. Through the VANET networks, we can circulate useful information on the state of the traffic in order to guarantee fluidity and an easy circulation. The vehicle-to-vehicle (V2V) communication is a way of transmitting this information in a VANET network. In this paper, we present an approach to detect the state of road traffic in urban areas based on the Big Data tools.

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