The idea of connected autonomous vehicles, which can share information among themselves, offers the potential to enhance traffic efficiency. However, putting this technology into practice comes with c..
The idea of connected autonomous vehicles, which can share information among themselves, offers the potential to enhance traffic efficiency. However, putting this technology into practice comes with challenges. Real-world challenges such as data throughput limitations can make it hard for vehicles to share information smoothly. Consequently, it becomes crucial to identify critical vehicle connectivity, which specifies the minimum number of connected vehicles required to maintain stable traffic flow. This paper proposes an information-theoretic metric that uses information flow among connected vehicles to identify critical vehicle connectivity. The model-free nature of information-theoretic tools eliminates the need for closed-form expressions of the model, which are necessary for stability analysis methods to identify critical connectivity. We demonstrate our proposed approach using a recent connected vehicles model. To the best of our knowledge, this paper presents the first application of information theory for analyzing critical vehicle connectivity in the context of connected autonomous vehicles.
