Based on the analysis of the current literature, mathematical modelling of the studied phenomenon was carried out. It was conducted according to the graph theory for vehicles transporting dangerous, oversized, and valuable cargo, moving within a transport network. The mapping of the parking areas included organisational, technical, and security aspects. The main algorithm determines the driving routes based on the parkings that meet the requirements specified by the carrier. These routes can ultimately be analysed and evaluated based on the parameters resulting from the formulated criterion functions. To verify the performance of the algorithm, its implementation was carried out in a computer environment using the Neo4j graph database. The transport network, consisting of 462 transport nodes and 602 transport links, was mapped based on the real national road network of the province in Poland. Data from 113 parking locations in the study area were included in the analysis. The research covered a total of three case studies, one for each vehicle type requiring specific parking conditions, for various input data. The results obtained allowed us to assess the validity of selecting particular routes and evaluating the scalability of the solution. The result of this work is a method, which, on the one hand, fits the current transportation requirements. On the other hand, it lends itself to scaling, extension by additional logical constraints, and is compatible with modern parking systems.

The issue related to parking lots has a multidimensional nature. For the purposes of the article, the analysis covered 113 parking lots located directly next to national roads in the Mazovian Voivodeship (Poland), which is similar in terms of economic development and conditions of the linear infrastructure to other countries in Central Europe. The conducted research included analyzing the correlation of parameters in individual parking lots and those related to nearby roads (traffic volume, technical quality) and the type of area in which they occurred (population density). In addition, the presented results describe the capacity of parking in the analyzed region in terms of the number of available parking slots for heavy goods vehicles, the size of the additional operating area, and the presence of security-related elements (fencing, lighting, physical protection, monitoring). The analysis demonstrated a correlation between some parameters (type of nearby road and security r_s = 0.35, area size and number of slots r_s = 0.35) and significant differences in results between private and public parking lots (average number of slots 18 versus 34, percent of most secured parkings 45% versus 69%). The obtained innovative results can be used by public institutions and entities providing parking services to reorganize the space at parking places and to conduct more effective analyses from the point of view of future investments in infrastructure accompanying the public road network.