RADS: a smart Road Anomalies Detection System using Vehicle-2-Vehicle network and cluster features (S)

Abstract

Vehicle-2-Vehicle is an emerging and interesting field of research area due to the several possible application in IoT and self-driving vehicles. It allows communication between vehicles, allowing them to share information about traffic and road conditions. Road accidents are nowadays one of the major causes of casualties worldwide, and therefore increasing road safety is very important. In this paper we present RADS: a smart Road Anomalies Detection System using Vehicle-2-Vehicle network and cluster features, a methodology which uses V2V and car distances in order to warn users of incoming dangers on the road, such as road blocks or existing accidents.

Identification of mobile vehicle through multilayer intercommunication

“…In such case, the intimidation to the road safety officers can be made in order to ensure the elimination of such vehicle that may later lead to any mis happening. In the reference [2], the work provided a road anomalies detection system using Vehicle to Vehicle (V2V) network and cluster features with the utilization of cars distance to warn the nearby vehicles of incoming dangers including road block or any accidents. The work considered a modified k-means algorithm in order to count the dynamic clusters based on number of nodes.…”