In the field of intelligent transportation systems, one important challenge consists of maintaining updated the electronic panels installed in roads with relevant information expressed in natural language. Currently, these messages are produced by human experts. However, the amount of data to analyze in real time and the number of available experts are imbalanced and new computational tools are required to assist them in this work. Moreover, the same problem appears when we deal with automatically generating linguistic reports to assist traffic managers that must take their decisions based on large amounts of quickly evolving information. In this paper, we contribute to solve this problem by designing a computational application based on our research in the field of computational theory of perceptions. Here, we present an application where we generate linguistic descriptions of the traffic behavior evolving in time and changing between different levels of service. We include some results obtained with both, simulated and real data.