International Journal on Advanced Science, Engineering and Information Technology, Vol. 11 (2021) No. 5, pages: 1787-1793, DOI:10.18517/ijaseit.11.5.13067

Analysis of Vehicle-to-Vehicle Basic Safety Message Communication Using Connectivity Characteristic Matrix

Mahmoud Zaki Iskandarani

Abstract

This work investigates vehicular mobility and the main factors that impact Vehicle-to-Vehicle (V2V) connectivity using Basic Safety Message (BSM).  MATLAB simulation used for Vehicular mobility and connectivity characterization under specific road traffic conditions. The simulation covers connectivity between traveling vehicles and a selected target vehicle to monitor communication interaction and establish an envelope within which reliable communication and BSM messages can occur. Another objective of this work is to use BSM exchanges to indicate the level of connectivity used to estimate traffic density, thus enabling congestion prediction. The obtained data contain information describing many vehicles, distance, connectivity time, and traffic density. The simulation results indicate an increase in the number of connected vehicles (connectivity level) as a function of both traffic density and communication range. Extending communication over fixed duration showed increased connectivity levels, allowing more vehicles to interact and exchange BSMs. The rate of change of connectivity per communication range is an indication of the state of traffic. Continuous connectivity proved to be less than general connectivity as vehicles exits through ramps and move from one cluster of vehicles to another. Varying duration per fixed communication range produced evidence of spatial domain change, and cluster variation as threshold values separate vehicles clusters in time and space. This work presented a model to help analyze the impact of vehicular mobility as a function of BSM communication range variation and connectivity duration variation correlated to traffic density.  

Keywords:

V2V; congestion; wireless communication; routing; intelligent transportation systems; VANETs.

Viewed: 88 times (since abstract online)

cite this paper     download