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The performance of Vehicular Data Networks (VDNs) is highly dependent on vehicular traffic. Existing studies on VDNs consider custom-developed traffic models that mimic real-life vehicular traffic behavior and prepare the ground for accurate VDN performance evaluation. Traffic evolution is affected by numerous random events. Some developed models are microscopic. They independently consider some possible factors (e.g., weather, road geometry, and drivers' skills). These microscopic models are complex, and their implementations may be costly. Other models are macroscopic.
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