An Efficient Scheme for Reliability Analysis and Optimization of V2V communication on the Highway

Vehicle-to-vehicle (V2V) communication operates in dynamic traffic environments, supporting various safety applications. As complex systems governed by multiple parameters, VANETs based on IEEE 802.11p/bd struggle to perform reliably with fixed settings. This paper proposes an analytical model to evaluate key reliability metrics: node-to-node packet reception probability (PRP), packet reception ratio (PRR), and packet delivery ratio (PDR), and derives a closed-form expression for throughput. Built on a marked point process, the model links reliability metrics to the signal-to-interference-and-noise ratio (SINR) distribution without requiring computationally intensive integrals. We further develop a multi-objective optimization scheme using the Bare Bones Particle Swarm Optimization (BBPSO) algorithm to maximize throughput while meeting reliability constraints by jointly tuning the packet generation rate and sensing range. In a highway scenario with a vehicle density of 0.12 vehicles/meter, our analytical model accurately predicts PRP, PRR, and PDR.