A numerical study of a Kalman filtering based strategy for platooning with lossy communication

In this article, we consider homogeneous platoons where vehicles communicate through lossy links. We assume a predecessor following topology in where each vehicle sends its position to the immediate follower agent, and the transmission is subject to random data loss modeled as a Bernoulli process. A Kalman filtering based strategy is proposed to estimate the missing data. Such approach is compared with one where the missing data is replaced by a linear extrapolation based on previous data. The performance of each strategy is studied through numerical simulations for different data loss probabilities. The simulation results show that the Kalman filter-based strategy achieves a considerably better performance compared to the linear extrapolation case considering both, the tracking and the estimation errors.