
This study was aimed at assessing the effectiveness of design solutions for the development of Kyiv’s transport infrastructure based on transport modelling and analysis of possible socio-economic effects. To do this, a four-step algorithm for modelling transport demand was used, based on data from sociological surveys, territory plans, and forecasts for 2030. The results of the study showed significant changes in the functioning of the Kyiv transport network as a result of the implementation of the proposed design solutions. The transport modelling helped to estimate quantitative indicators such as traffic volumes on major highways, as well as qualitative changes such as reduced congestion, shorter travel times, and cost savings. One of the key results was that the opening of new exits and entrances to the Darnytskyi Bridge on the left bank contributed to a slight increase in bridge capacity, but the biggest effect was seen on the approaches to the bridge. The additional approaches have increased traffic volumes, which indicates improved transport accessibility for drivers using this transport hub. The results related to environmental performance were also important. The reduction in congestion resulted in a reduction in CO2 emissions, which is a significant contribution to improving the environmental situation in the city. In terms of cost-effectiveness, the results demonstrated significant savings in transport losses, confirming that the implementation of the proposed measures has a positive impact on transport infrastructure, as well as reducing financial losses associated with travel. Thus, the results of the study confirmed that the proposed design solutions have a positive impact on the development of the transport network, increasing capacity and reducing negative environmental impact, which opens up opportunities for creating a more efficient transport system that meets the requirements of sustainable development and improves the overall quality of life of Kyiv residents
social impacts, transport modelling, infrastructure development scenarios, traffic capacity, Architecture, Architectural engineering. Structural engineering of buildings, TH845-895, node congestion, street and road network, NA1-9428
social impacts, transport modelling, infrastructure development scenarios, traffic capacity, Architecture, Architectural engineering. Structural engineering of buildings, TH845-895, node congestion, street and road network, NA1-9428
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
