## 6 Discussion
Afterward, the traffic flow speed estimated for interrupted traffic stream conditions becomes higher than the speed estimated for continuous traffic stream conditions. On the other hand, an alternative version of [PERSON] and [PERSON]'s model with six parameters produces very similar results to [PERSON]'s three-parameter sigmoid model, whereby the difference in traffic flow speed estimated for continuous and interrupted traffic stream conditions decreases from 6.8 kph at free-flow speed to 1.76 kph at critical density, and it then reaches 0 at jam density. [PERSON]'s logarithmic-potential form of the \"speed-density\" model generates very high differences, up to 42.5 kph, betweencontinuous and interrupted traffic flow speeds in a free-flow regime. This difference is gradually reduced to 6.3 kph at saturation density, and it comes close to 0 at jam density. According to [PERSON]'s model, the difference in the traffic flow speed produced for continuous and interrupted traffic stream conditions amounts to 21.34 kph in a free-flow regime and 6.7 kph at critical density. After reaching saturation density, the speeds estimated for continuous and interrupted traffic stream conditions become approximately equal. If we consider the fact that, in a free-flow regime, the drivers are not restricted by the movements of other vehicles in the traffic flow, and therefore, they can drive at their desired speed, together with the fact that, in interrupted traffic stream conditions, vehicles are periodically slowed down and stopped due to the presence of signalized intersections along the road, it is logical to conclude that there must be a noticeable difference in the mean speed of continuous and interrupted traffic flow in a free-flow regime. Following this reasoning, we argue that the \"speed-density\" regression functions obtained by fitting [PERSON]'s, [PERSON]'s and [PERSON]'s models do not produce logical results. By taking into account the fact that [PERSON] model oversimplifies the speed-density relationship and therefore cannot be used for realistic representation of real traffic flow characteristics, which are non-linear in nature, we can come to the conclusion that only eight of the twelve traffic flow models considered are based on sound logical assumptions and are therefore practically applicable for describing the differences in mean traffic flow speed representative of continuous and interrupted traffic stream conditions. However, it is also important to emphasize here that the remaining models also have their limitations. For example, the mean traffic flow speed estimated by [PERSON]'s sigmoid models, [PERSON]'s, [PERSON]'s and [PERSON]'s models does not reach zero at jam density. If we also consider the fact that [PERSON] and [PERSON]'s five-parameter model produces somewhat unexpected results in a saturated and congested traffic flow regime, we can conclude that only modified [PERSON]'s and [PERSON]'s six-parameter models satisfy all logical assumptions based on the traffic flow theory. Discussion on the Comparative Analysis of Selected \"Flow-Density\" Models Fitted to Empirical Data Collected under Continuous and Interrupted Traffic Stream Conditions  
Based on the comparative analysis of fundamental traffic flow diagrams of the traffic flow models considered, we determined that the practical road capacity values representative of continuous and interrupted traffic stream conditions vary significantly depending on the selected model. The maximum practical capacity values, both for continuous and interrupted traffic stream conditions, are obtained using Fosu's model. According to Fosu's negative asymmetric \"flow-density\" curve, the practical road capacity of the observed regional road is reached at saturation densities of 96 and 116 veh/km/lane under continuous and interrupted traffic stream conditions, respectively. The practical road capacity (\(q_{max}\)) is equal to 2333 veh/h/lane and 1793 veh/h/lane in continuous and interrupted traffic flow, respectively.