Synchronized Multi-Point UAV-Based Traffic Monitoring for Urban Infrastructure Decision Support
This study presents a comprehensive methodology for urban traffic monitoring and infrastructure decision making, centered on synchronous, simultaneous aerial data collection through a distributed multi-point UAV deployment. Conducted in the GreenLine district of Astana, Kazakhstan, the research util...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/5/370 |
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| author | Igor Kabashkin Alua Kulmurzina Batyrlan Nadimov Gulnar Tlepiyeva Zura Sansyzbayeva Timur Sultanov |
| author_facet | Igor Kabashkin Alua Kulmurzina Batyrlan Nadimov Gulnar Tlepiyeva Zura Sansyzbayeva Timur Sultanov |
| author_sort | Igor Kabashkin |
| collection | DOAJ |
| description | This study presents a comprehensive methodology for urban traffic monitoring and infrastructure decision making, centered on synchronous, simultaneous aerial data collection through a distributed multi-point UAV deployment. Conducted in the GreenLine district of Astana, Kazakhstan, the research utilized a coordinated fleet of UAVs to capture real-time video footage at 30 critical observation points during peak traffic periods, enabling a network-wide view of traffic dynamics. The collected data were processed to extract key traffic parameters, such as flow rates, vehicle speeds, and delays, which informed the calibration of a detailed traffic simulation model. Based on this model, six infrastructure development scenarios were evaluated using a multi-criteria decision-making framework to identify the most effective intervention strategies. This study introduces a replicable, data-driven approach that links synchronized UAV sensing with simulation-based evaluation, offering a practical decision support tool for improving urban infrastructure performance within the context of smart and rapidly evolving cities. |
| format | Article |
| id | doaj-art-cbc2cf7617394a088f5f3fd42088e0ce |
| institution | OA Journals |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-cbc2cf7617394a088f5f3fd42088e0ce2025-08-20T01:56:16ZengMDPI AGDrones2504-446X2025-05-019537010.3390/drones9050370Synchronized Multi-Point UAV-Based Traffic Monitoring for Urban Infrastructure Decision SupportIgor Kabashkin0Alua Kulmurzina1Batyrlan Nadimov2Gulnar Tlepiyeva3Zura Sansyzbayeva4Timur Sultanov5Engineering Faculty, Transport and Telecommunication Institute, Lauvas 2, LV-1019 Riga, LatviaLLP “Universal Tech Decisions”, Kabanbay Batyr Ave 53/42, Astana KZ-10000, KazakhstanLLP “Universal Tech Decisions”, Kabanbay Batyr Ave 53/42, Astana KZ-10000, KazakhstanLLP “Universal Tech Decisions”, Kabanbay Batyr Ave 53/42, Astana KZ-10000, KazakhstanLLP “Universal Tech Decisions”, Kabanbay Batyr Ave 53/42, Astana KZ-10000, KazakhstanLLP “Universal Tech Decisions”, Kabanbay Batyr Ave 53/42, Astana KZ-10000, KazakhstanThis study presents a comprehensive methodology for urban traffic monitoring and infrastructure decision making, centered on synchronous, simultaneous aerial data collection through a distributed multi-point UAV deployment. Conducted in the GreenLine district of Astana, Kazakhstan, the research utilized a coordinated fleet of UAVs to capture real-time video footage at 30 critical observation points during peak traffic periods, enabling a network-wide view of traffic dynamics. The collected data were processed to extract key traffic parameters, such as flow rates, vehicle speeds, and delays, which informed the calibration of a detailed traffic simulation model. Based on this model, six infrastructure development scenarios were evaluated using a multi-criteria decision-making framework to identify the most effective intervention strategies. This study introduces a replicable, data-driven approach that links synchronized UAV sensing with simulation-based evaluation, offering a practical decision support tool for improving urban infrastructure performance within the context of smart and rapidly evolving cities.https://www.mdpi.com/2504-446X/9/5/370UAVaerial data processingtraffic monitoringtraffic simulationurban mobility planningsmart cities |
| spellingShingle | Igor Kabashkin Alua Kulmurzina Batyrlan Nadimov Gulnar Tlepiyeva Zura Sansyzbayeva Timur Sultanov Synchronized Multi-Point UAV-Based Traffic Monitoring for Urban Infrastructure Decision Support Drones UAV aerial data processing traffic monitoring traffic simulation urban mobility planning smart cities |
| title | Synchronized Multi-Point UAV-Based Traffic Monitoring for Urban Infrastructure Decision Support |
| title_full | Synchronized Multi-Point UAV-Based Traffic Monitoring for Urban Infrastructure Decision Support |
| title_fullStr | Synchronized Multi-Point UAV-Based Traffic Monitoring for Urban Infrastructure Decision Support |
| title_full_unstemmed | Synchronized Multi-Point UAV-Based Traffic Monitoring for Urban Infrastructure Decision Support |
| title_short | Synchronized Multi-Point UAV-Based Traffic Monitoring for Urban Infrastructure Decision Support |
| title_sort | synchronized multi point uav based traffic monitoring for urban infrastructure decision support |
| topic | UAV aerial data processing traffic monitoring traffic simulation urban mobility planning smart cities |
| url | https://www.mdpi.com/2504-446X/9/5/370 |
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