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The development of the Vehicle to Everything (V2X) communication technology can provide crucial data for traffic analysis on the microscopic level. Real-time data from Connected Vehicles (CVs) opens new research possibilities providing detailed insight into the actual traffic state. Speed Transition Matrices (STMs) can be used for this insight and can be created within a fully observable traffic environment. By introducing CVs into the traffic network, it is possible to obtain a partial observation of the traffic environment. This paper explores how the data collected from CVs can be used for the creation of STMs at an isolated intersection in a simulated environment. An emphasis is given on how the CVs penetration rate impacts the accuracy of the created STM. The results show that by increasing the CVs penetration rate, the STM estimate accuracy is also increased, although the relation between estimate accuracy and the penetration rate is not linear. Obtained results show that the error of STM estimation rapidly decreases in the lower CVs penetration rate range.

The rapid increase in the number of vehicles on the roads is attracting the attention of many researchers around the world. The consequences of the increased number of vehicles are numerous, firstly increased congestion and negative climate effects, and secondly, many countries and companies are encouraged to research traffic behavior and collect historical data from traffic sensors. Simulations are gaining a significant role in researching traffic characteristics, as not all scenarios are feasible in the reality. Observing traffic in simulation environments provides a significant number of parameters that can be obtained and analyzed. In this paper, we provide an overview of the process of creating traffic simulations in the SUMO simulator. In addition, we have managed to automate part of the process of preparing the simulation.