The purpose of the article is to assess the risks of a toll road operator arising in the event of traffic congestion at toll collection points. In the Russian Federation, in infrastructure projects, including toll road projects, the organizational and legal form of public-private partnership is often used. State authorities have the right to control the quality of the road management by the operator; the state can charge penalty points for low operational efficiency, leading to traffic congestion. The return on investment in infrastructure projects is of a long-term nature, therefore, the task of assessing the risks of possible losses by the toll road operator is quite relevant.Materials and methods. The main research tool is simulation modeling in the AnyLogic software environment, the analysis of the data obtained as a result of simulation was carried out in the environment of the statistical package R. The choice of tools is determined by a large number of subjective (sometimes technical) factors that significantly affect the road capacity at toll collection points, but do not lend themselves to strict formalization. Such factors include refusals to read electronic tolls, drivers changing lanes in the toll collection points, lack of money at the time of travel through the automatic toll lane, and others. All such factors are modeled in the AnyLogic environment as random variables with a rich choice of distribution functions and their parameters.Results. A simulation model of a toll collection point at an exit from a toll road has been created to analyze the throughput of a toll booth with various configurations of toll lanes, various levels of user behavior errors and the provision of drivers with electronic means of travel registration. Using the example of a toll collection point for the “Western High-Speed Diameter” motorway, the parameters of traffic congestion that occur when the number of operating toll lanes on the toll collection point decreases are estimated. In the event of congestion, for each configuration, estimates of the number of vehicles in the congestion, the length of the congestion, the waiting time in the queue at the entrance to the toll collection point at different times of the day, and the time of congestion are determined.Conclusion. Based on the results obtained, an assessment of the risks of non-compliance by the road operator with the standard for ensuring throughput can be carried out. To assess the risks of a toll road as a whole, it is advisable to use an individual simulation model for each toll collection point, taking into account the peculiarities of its geographical location, the composition of traffic at the facility, the regularity of user correspondence, as well as the impact of the surrounding transport, logistics and social infrastructure. In pronounced industrial and logistics areas of the city, in the border zones between the city and the region, an additional assessment of traffic intensity may be required to analyze the throughput of toll collection points, taking into account the daily, weekly and seasonal unevenness of the traffic flow.
Analytical Model to Estimate Ride Pooling Traffic Impacts by Using the Macroscopic Fundamental Diagram
