# Modeling of Vessel Traffic Flow for Waterway Design-Port of Swinoujscie Case Study
## 4 Conclusions and Discussion  
The researchers present AIS data analysis for the approach to Swinoujscie to gain better insights into the behaviour and manoeuvring of ships. The defined distribution of the ship's position, speed, courses, dimensions of vessels, and the relationship between these factors form the basis for the mathematical model of traffic flow. Some simple regression models describing the behaviour of the vessels have been presented. The significant predictor of vessel traffic flow parameters in the model was vessel draught \(T\). For GC vessels, 80% of the variation in the variable \"mean\" distance to the centre of the track was explained by the model: 68% for OPT; 27% for PAS ships. However, in this case, the predictor was not significant. For the dependent variable \"standard deviation\", the model explained 23% of the variation for GC ships, 61% for PAS ships, and 0% for OPT ships. The width of ship \(B\) was significant only in regard to the parameter GC and OPT ships, where 40% and 45% of the variation using this variable was explained. For the standard deviation, it was not significant. These results suggest that further investigation is necessary in even more restricted (narrower) areas, where the vessel width should have a significant impact. Figure 12: (a) Scatterplot of distance from centre versus draught \(T\). (b) Scatterplot of COG versus draught \(T\). Figure 13: (a) Scatterplot of distance from centre versus draught \(T\). (b) Scatterplot of a vessel’s width versus COG. The authors created two important models for mean and standard deviation of different classes of ship position variability of waterway leg length. This was inspired by [PERSON] [5] and Japanese studies [1; 3; 10; 26; 27]. The validated regression model in the form of \(SD=0.0852+0.0287\times Ltr\) shows a difference from these studies, but the analysed area also differs. Moreover, the authors found that the mean position of ships on the waterway also changed on long waterway legs, which was never discussed before. Regression was used to compare the standard deviation of vessel position with the length of the track (section). The model explains 42% of the variation for GC and OPT vessels. It is suggested that further studies consider [PERSON]'s studies [5] and the results obtained. Since the distance to the hazard is a significant factor for the safety of a vessel in traffic, the distance to safe isobaths \(D_{10m}\) was analysed using the parameters of vessel traffic flow. The model created explained 63% of the variance for the mean and 63% of the standard deviation. The predictor was significant, with \(p<0.02\). The authors also studied the influence of ship width and generally ship size on their positions on the waterway. The results turned out to be consistent with previous hypotheses, i.e., larger ships keep closer to the centre of the track but the regression models allowed this to be quantified, which is very important for building general navigation safety models. Similar results were obtained by examining the draught of ships in relation to the safe isobaths. There are additional factors that contribute to vessel traffic flow that were not considered. These factors include wind, current, visibility, the human factor, and ship interaction. Small vessels of L < 50 m were not considered. In addition, the accuracy of data from AIS should be investigated, and the impact on the model considered. All waterborne activities lead to changes in the characteristics of vessel traffic flows at sea. In order to calculate the impact on traffic flows, a model of marine traffic flow is required. The developed model enables the design of maritime routes in the development of spatial planning on the seas. Conceptualization, A.N. and L.G. ; methodology, A.N., L.G., K.L., A.A., M.P. and J.S. ; data collection, A.N. and L.G. ; formal analysis, A.N., L.G. and K.L. ; investigation, A.N., L.G. and K.L. ; data curation, A.N. and L.G. ; visualization, A.N. and L.G.