As transportation becomes more demanding in modern communities, the challenges involved such as congestion and emissions grow more concerns. Intelligent transportation system (ITS) is one of the most recognizable solution to resolve the problem. One of the components of an ITS is intelligent intersections that use vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications to reduce the waiting time and consequently the idling time and emission of the vehicles. To implement different control strategies to reach the aforementioned objectives, a validated platform is required to simulate the real-world traffic flow. To this end, Simulation of Urban Mobility (SUMO) software along with real data are utilized for developing two control strategies: Single Vehicle Speed Advisory Algorithm (SVSAA) and Platoon Speed Advisory Algorithm (PSAA). The results of real-world simulation demonstrate that the proposed schemes are able to reduce the waiting time, fuel consumption, and emissions significantly compared with the baseline strategy. Moreover, it turns out that PSAA scheme implementation via model predictive controller may totally eliminate the congestion at the intersection.