Issue: № 6, 2024
Doi: https://doi.org/10.37634/efp.2024.6.27
The paper presents a critical analysis of current approaches to reorganizing urban transportation routes. It proposes addressing the problem of optimizing traffic flows as a multidimensional issue encompassing social and economic aspects. An economic-information model for continuous monitoring and optimization of urban traffic flow configurations based on the criterion of congestion wait time has been developed. The calculation of the economic consequences of such waiting time is proposed. The developed system has practical significance and can be applied in managing traffic flows as an economic subsystem of the city within its socio-economic system. Urban transportation infrastructure in Ukraine faces significant challenges due to social changes, including increasing passenger flow, extended waiting times, and the need to adhere to modern urban planning standards. Current trends involve redistributing street and road space based on principles of equal access and safety. This includes pilot actions, intermediate reconstruction, and comprehensive reorganization of urban space and transportation routes. Proposed methods for enhancing transportation infrastructure include improving government management, implementing proactive management strategies, executing investment projects, establishing public-private partnerships, temporarily reducing tax burdens, developing comprehensive solutions for consumers, and optimizing transportation pricing. These strategies aim to address the pressing problems in Ukraine's transport sector and facilitate sustainable development and growth. The study focuses on the financing of infrastructural projects in Dnipro city through the municipal budget. It proposes integrating economic-mathematical models into a unified economic-information system for optimizing traffic flows, allowing for continuous monitoring and improvement. This system emphasizes minimizing congestion wait times and can adapt to dynamic changes in traffic patterns, ensuring efficient and effective urban traffic management. By implementing this system, the city can enhance its transportation network, contributing to overall economic efficiency and better quality of life for its residents.
Keywords : simulation modeling, traffic flows, optimization, waiting time, economic-information system
References:
1. Hasenko L. et al. Principles of street and road space redistribution in accordance with modern urban planning trends. Automobile Roads and Road Construction. 2022. № 111. pp. 45-54. URL: https://doi.org/10.33744/0365-8171-2022-111-045-054 (in Ukrainian).
2. Radchenko O. et al. Transport and transport infrastructure of Ukraine in the pre-war period (2010-2021). Prace Komisji Geografii Komunikacji PTG. 2022. № 25(2). pp. 7-17. URL: https://doi.org/10.4467/2543859xpkg.22.009.16267
3. Gretskaya N.A. The assessment of the state and problems of the transport and logistics infrastructure of Ukraine using the SWOT analysis method. Agrarnaâ èkonomika. 2022. pp. 69-83. URL: https://doi.org/10.29235/1818-9806-2022-1-69-83
4. Gintaras Stauskis., Vaiva Deveikienė. Assessing Quality of City Development by the Acquired Criteria of Landscape Urbanism. 2016. № 12(1). pp. 37-43. URL: https://doi.org/10.1515/AUP-2016-0012
5. Patricia Jaramillo-Álvarez et al. Route optimization of urban public transportation. Dyna. 2013. № 80(180). pp. 41-49.
6. Dolia K. et al. Management of Freight Transport Projects in Cities in Assessing Their Effectiveness. Software Engineering. 2018. № 6(2). pp. 63-68. URL: https://doi.org/10.11648/j.se.20180602.15
7. Heh Y. Cities for People. Kyiv, 2018. (in Ukrainian).
8. Bivina G.R. et al. Socio Economic Valuation of Traffic Delays. Transportation research procedia. 2016. № 17: pp. 513-520. URL: https://doi.org/10.1016/J.TRPRO.2016.11.104
9. Goodwin P. The economic costs of road traffic congestion. 2004.
10. Eremia M. et al. The smart city concept in the 21st century. Procedia Engineering. 2017. № 181. pp. 12-19.
11. Ayushi C. et al. A Hybrid Univariate Traffic Congestion Prediction Model for IoT-Enabled Smart City. Information. 2023. № 14(5). pp. 268-268. URL: https://doi.org/10.3390/info14050268