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 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.