DEVELOPMENT OF A METHOD FOR RAPID ANALYSIS OF THE IMPACT OF NEW OXS BEING BUILT ON ADJACENT AREAS OF MAC

Borovskoy, A.; Smirnova, A.; Berdnikov, M. · 2025 · Crossref

DOI: 10.34031/2071-7318-2025-10-7-83-93

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Summary

This paper addresses the critical need for rapid assessment methods to evaluate the impact of new capital construction projects (OCS) on adjacent street and road networks (SRN). The authors argue that urban planning and transport systems are inextricably linked, yet existing macro- and meso-models require extensive data collection and calibration, making them inefficient for timely decision-making. With rising motorization in Russia, there is a gap in systematic transport planning tools that can objectively analyze traffic flows and pedestrian connectivity for new developments. The study aims to develop an express analysis methodology using Geographic Information Systems (GIS) to predict traffic loads, parking functionality, and public transport accessibility before construction begins. The methodology was developed and tested in Belgorod, Russia, using the NextGIS QGIS platform. The process involves seven steps: first, analyzing the master plan of the new development to determine resident counts and parking requirements. Second, calculating parking space functionality based on three scenarios: current motorization levels (345 cars/1,000 people), prospective levels (480 cars/1,000 people), and regulatory minimums (75% of apartments). Third, dividing the territory into transport zones and determining the distribution of workplaces using data from cellular operator surveys (InfoNet Mobil LLC) to estimate population density and movement patterns. Fourth, identifying geometric centers of these zones and calculating shortest paths using the city’s road graph. Fifth, constructing a transport interaction matrix (correspondence matrix) to quantify traffic flows between the new development and other city zones. Finally, assessing public transport accessibility based on distance to stops and connectivity. Applied to a residential complex on Donetskaya and Volchanskaya streets, the results indicated a significant increase in traffic load on adjacent SRN nodes. The analysis revealed that the new development would exacerbate congestion and increase travel times for residents. Consequently, the study identified specific infrastructure deficits, necessitating the creation of new transport corridors to ensure connectivity with other city zones. The authors proposed specific interventions, including constructing a new road section across the Seversky Donets River, improving signalization at key intersections (Kostyukova and Gubkina streets), building a bypass at the Kostyukova and Donetskaya intersection, and reconstructing the Volchanskaya and Mikhailovskoye Highway intersection. These proposals were validated using meso-modeling software such as Aimsun, PTV, and Sumo. The significance of this work lies in providing a practical, data-driven tool for urban planners to integrate transport considerations into early-stage architectural design. By leveraging accessible GIS tools and cellular data, the method allows for the rapid calculation of existing and projected traffic loads without the high costs and time delays associated with traditional modeling. This approach supports the development of Intelligent Transport Systems (ITS) and helps mitigate urban conflicts by ensuring that new constructions are accompanied by adequate transport infrastructure, thereby improving overall urban mobility and resident quality of life.

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