Traffic Congestion in Egypt roads is the same problem facing many cities around the world where traffic congestion is a
well-known economic and social problem generating significant costs and safety challenges, and increasing pollution in the cities. Current Conventional infrastructure based solutions to detect traffic congestion, such as surveillance cameras and road surface inductive loops, have the limitations of high deployment costs and limited coverage. This paper contributes towards the development of distributed and cooperative vehicular traffic congestion detection by proposing a new vehicle-to-vehicle (V2V) congestion detection algorithm based on the IEEE 802.11p standard. The new algorithm allows vehicles to be self-aware of the traffic in the city roads, performing congestion detection based on speed monitoring and exchanging traffic information with the surrounding vehicles. Exchanging is achieved using adaptive single-hop broadcasting which depends on the level of congestion. The paper presents the congestion detection algorithm and the cooperative communication in detail, and presents performance evaluation using large-scale simulation in Veins  framework based on OMNeT++ simulator and SUMO vehicular mobility simulator. Results show that precise congestion detection and quantification can be achieved using a significantly decreased number of exchanged messages allowing more vehicles to be aware of congestion and be able to avoid it.