FORECASTING THE REDISTRIBUTION OF TRAFFIC FLOWS UNDER INCIDENT CONDITIONS ON AN URBAN ROAD NETWORK
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Abstract
The article is devoted to the urgent problem of reducing the negative consequences of incidents on the urban road network. The problem of forecasting the redistribution of traffic flows arising from unforeseen traffic blockages is considered. The aim of the research is to develop a software package capable of simulating the development of the traffic situation in near-real-time and providing a forecast for making operational management decisions. To achieve this goal, an analysis of existing approaches to traffic demand modeling was carried out, based on which the method of dynamic non-equilibrium assignment was chosen as the one that most adequately describes driver behavior under incident conditions. The SUMO simulation micro-modeling environment was used as an instrumental platform. A simulation model of a representative section of the Minsk road network was developed and calibrated, with an error in traffic intensity at key intersections not exceeding 5%. A software package was created, consisting of a simulation model control module (in Python using the TraCI API) and a graphical user interface module (based on the PyQt5 library). An experimental study showed that using the developed package for forecasting and preventive changes in traffic signal control modes can reduce average transport delays in the incident zone by 21%. The estimated annual economic effect from the implementation of the proposed solution is 31,283 conventional units, with a payback period for capital investments of 1.85 years.
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References
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