## 4 Results and Discussion
Scenario B involves an increase in the daily _PT_ capacity and higher numbers of new vehicles in the initial simulation phase. The supply and demand rates begin at 1.02 and close at 1.26. Figure 11 suggests the trend in supply and demand rates in _PT_. Figure 9: Trend in registered cars and supply and demand rates in _PCT_ (dimensionless-Dmnl). Figure 11: Trends in supply and demand in PT. Figure 10: Trend of selected submodel values ’number of \(PT\) vehicles’. Scenario C and scenario D show a similar trend in the supply and demand index in public transport, which is given by the demonstrative model parameter set in this way. The result of the model testing shows that it is appropriate to specify other variables in order to simulate the resulting values of the index based on the vehicle fleet's current state, the setting of the traffic rules and measures, as well as other factors related to the planning of transport capacity in public transport. The supply and demand for \(PT\) reflect regional infrastructure. The model for estimating its rates allows a simplified demonstration of how system dynamics tools work in the transport sector [40]. When the model expands into other specific variables, the model estimates the final supply and demand rates. Ratios below the limit indicate that the public transport sector cannot satisfy the demand for \(PT\), whereas rates above the ceiling, yet not reaching one, show that the \(PT\) system meets customer needs in certain situations. In rush hours or emergencies, the infrastructure suffers from deficiencies. Our model does not count factors behind heavy traffic, including everyday supply and demand. Supply and demand rates above 1 suggest that the \(PT\) network fully meets public demand. However, if the rates exceed the outer limit, we should consider optimizing and adjusting public transport processes. Cutting the excessive supply will prevent economic losses. The addressed index supply/demand ratio in public transport can be deemed as one of the indicators quantifying the state of a sustainable transport system. Different versions of potential indicators and their measures for describing a strategy or sub-system of sustainable mobility and sustainable transport system exist. An important criterion for these indicators is represented by the fact that they should define all connections with the goals of sustainable mobility as succinctly and clearly as possible. Indicators can be of different types; see them as follows:  
* quantitative and qualitative data;
* individual indicators (e.g., individual opinions within questionnaire surveys);
* ratio indicators;
* relative indicators. Based on the findings demonstrating the connections of various factors affecting the resulting transport demand and supply, the indicators can be used for further extensive research. In this case, it would be a matter of compiling indicators respecting the pillars of sustainable mobility, namely factors affecting traffic volumes on roads. In deeper considerations and perspectives, the transport system state is taken into account with the goals of strategic land use planning, with the goals of integrated transport modes aimed at increasing safety and reducing the negative impact on the environment so that costs are spent effectively (i.e., effective development of a sustainable urban environment). At the same time, we try to integrate as many indicators as possible, which could be of maximum help towards decision-making processes concerning sustainable development.