
The paper provides a closed-form probability distribution for the length of time taken to achieve shared situation awareness among a group of connected vehicles.


coremsg

analyzing-the-latency-for-achieving-shared-situation-awareness-among-connected-vehicles


Analyzing the Latency for Achieving Shared Situation Awareness among Connected Vehicles


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This article presents a model-free machine learning framework for cooperative localization in dense urban vehicular networks, addressing key challenges such as model dependence, adaptive interactions, heterogeneous connectivity, and time-varying mobility.


cooperative-localization-in-dense-urban-environments-leveraging-machine-learning


Cooperative Localization in Dense Urban Environments Leveraging Machine Learning



Dynamic allocation of 5G User Plane Functions at the network edge can significantly reduce latency for latency-critical vehicular sensing applications compared to static or centralized deployments.


optimizing-5g-user-plane-function-allocation-to-reduce-latency-in-vehicular-sensing-applications


Optimizing 5G User Plane Function Allocation to Reduce Latency in Vehicular Sensing Applications
