Modeling vehicle safety in vehicular networks using Markov chain model based on cooperative awareness

Main concern of many safety applications in emergency situations is determining the safety of a vehicle respect to the other ones. Consecutive packet losses reduce the overall performance of a safety application which using vehicular networks as its source of awareness. Thus, determining the impact of consecutive packet losses on safety and awareness seems critical. However, speed, acceleration and the other dynamic properties of the vehicles play an important role in determining number of tolerable packet losses and safety assessment process. In this paper, we model the safety and awareness values according to consecutive packet losses using Markov chain model. Our model serves a novel and promising framework for analyzing a vehicle safety based on the current situation of the network and the vehicle dynamical properties. This model gives us the channel situation as well as the vehicle risk value. In the proposed model, the uncertainty of the driver perception about an upcoming event due to the lack of information is also taken into account. Using this model, one can investigate the impact of distance and velocity on safety efficiently.