**5. Discussion**

The results of the research presented in this article indicate that the application of Markov chains to forecast the bus occupancy level in public transport is entirely justified because it represents, to a reasonable degree, the features of the urban public transport system. Compared to the works mentioned in the literature review, which mostly refer to the problem of passenger flow forecasting in the transport network, the authors' research was strictly focused on forecasting the bus comfort level related to the vehicle occupancy, which can be directly used by travelers to optimize their trips and to change their travel patterns to more environmentally friendly ones. The obtained results can be useful not only for fleet managemen<sup>t</sup> in the public transport system but also for the development of passenger information systems and trip planning.

Nevertheless, this approach requires further research based on a larger data set sample from an automatic counting system over a longer time horizon. It would also be desirable to determine the influence of other factors on the forecasting effectiveness (season of the year, weather, and specificity of the analysed communication line). The calculated forecast errors are the most significant for interchanging stops, due to the high variability of passenger flows in these places. Therefore, it seems justified to carry out studies with the use of heterogeneous Markov chains, where the transition matrix would be variable depending on the time, type of bus stop or communication line. Such an analysis could be very useful for the practical application and further verification of the proposed approach.
