Abstract: Advanced research in 5G-enabled vehicular technologies has made the Internet of Vehicles (IoV) a promising research area in intelligent transportation systems (ITS). The high vehicular mobility causes frequent network topology changes, leading to unreliable emergency alert messaging (EAM) in real-time IoV applications. Due to the high volume of data propagation in such networks with limited bandwidth resources, topological dynamics can cause data congestion and data loss, which is not tolerable for delay-sensitive emergency messages (EMs). Unmanned Ariel vehicles (UAVs) as dynamic infrastructures can provide customized EAM services for IoVs. This paper proposes UFC3, a UAV-aided Fog Computing Congestion Control strategy for EM dissemination in 5G IoV. This study provides a practical method for EAM by reducing burst EM traffic to guarantee reliable messaging communication between an abnormal vehicle (AV) and the fog server (FS). In UFC3, various nodes capable of Wave protocol were considered as basic vehicles or 5G-enabled nodes regarded as intelligent vehicles or UAVs, and the authors propose a traffic-aware forward/backward link EAM strategy to handle any EM and the corresponding response between the AV and FS. Next, this paper suggests a mathematical analysis for EM propagation speed (EMPS) and propose closed-form EMPS equations for various traffic-aware forward/backward link EAM scenarios. Using OMNET?+??+?along with Veins and INET frameworks, the authors simulate UFC3 and compare it with previously published works regarding communication overhead, throughput, packet delivery ratio, average delay, packet loss ratio, channel utilization, and energy consumption.