  A reliable estimation of the communication chan-nel which connects automated
vehicles is an important steptowards the safety of connected and automated
vehicles. The communication channel is usually modeled as Markov chain with
slowly time-varying transition rates and is identifiedthrough statistics on the
observed state transitions. However, the classical identification approach
lacks a measure on how reliable the identification results, and thus the
channel, are. In this work, we propose an identification method, based onthe
subjective logic theory, which features such a reliability measure in terms of
statistical uncertainty. We demonstrate through simulations that the proposed
method is capable of quickly responding to parameter changes. Furthermore, it
is shown that the transition rates of the Markov chain are tracked with high
accuracy. Finally, we validate our results by a real-world experiment.
