Analysis of alert message propagation on the highway in VANET assuming Markovian vehicle arrival process

Abstract

SummaryVehicular ad hoc networks (VANETs) provide the infrastructure for the intelligent transportation system (ITS). The number of vehicles that are capable of communicating with each other through VANET is increasing. In this paper, we provide several analytical results regarding the message propagation on the highway in VANET. In our scenario, there is a stationary message source (i.e., alert messages are generated at an accident). Vehicles can receive the message and get informed when they reach the radio transmission range of the message source or another informed vehicle. Most papers published on the analysis of message propagation assume that the inter arrival times between vehicles follow a Poisson process; there are very few results available with more general traffic model. In this paper, we show that the Poisson process is not always suitable for modeling vehicle traffic. Instead of the Poisson process, we propose to use the more general Markovian arrival process (MAP) to model the vehicle headway times and derive the probability that the message propagates beyond a certain distance from the accident under this traffic assumption. Through several numerical examples, we demonstrate how much the statistics of the vehicle arrival process impacts the message propagation distance.