Subjective Logic-based Identification of Markov Chains and Its Application to CAV's Safety

TL;DR

This paper introduces a subjective logic-based method for identifying Markov chains in vehicle communication channels, providing reliability measures and demonstrating high accuracy and responsiveness through simulations and real-world experiments.

Contribution

It presents a novel identification approach using subjective logic that includes reliability measures, improving accuracy and responsiveness in modeling vehicle communication channels.

Findings

The method accurately tracks Markov chain transition rates.

It responds quickly to parameter changes.

High accuracy demonstrated in real-world experiments.

Abstract

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.