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Traffic Intensity Inference and Forecasting for Congestion Prevention in Vehicular Ad Hoc Networks


K. Subramanian and Dr.T.S. Subashini
Abstract

Traffic intensity inference relies on vehicular ad hoc networks (VANETs) that facilitate many applications like traffic management, transportation planning, etc. By taking the vehicles count located in a certain area the traffic intensity is measured up. To combine vehicle spacing data that is gathered through vehicular system and calculates average spacing in a particular place within a lesser time. With received data on link instinct aspect, road side unit can estimate average number of vehicles that is travelled or connected to that particular RSU. The estimation mechanism proposed in here can utilize the historical information about the route like distance between the vehicles, speed of the vehicle, and received signal strength between the vehicles. The parametric such as distance, speed of the vehicle, loss rate and SNR are analysed for the proposed mechanism with respect to the traditional protocols.

Volume 12 | 03-Special Issue

Pages: 27-35

DOI: 10.5373/JARDCS/V12SP3/20201235