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Monitoring outdoor urban parking areas has traditionally relied on either costly sensing technology, such as ground sensors, or manual inspections, which are both resource-intensive. The emergence of drones equipped with advanced visual sensors provide a comprehensive aerial perspective and versatile mobility, opening up new possibilities for efficient traffic monitoring. In this research, we demonstrate the efficient monitoring of usage levels in outdoor public parking lots using drones. We deployed a number of drones flying during the peak periods for two days over four major outdoor parking lots in Pully, Switzerland, while monitoring on-street parking in their proximity. Our proposed pipeline involves identifying parking areas through geo-referencing and an image feature matching approach, followed by vehicle detection using an innovative boosted pseudo-labeling method. Central to our pipeline is an innovative boosted pseudo-labeling technique that enhances detection accuracy by generating pseudo labels from stationary vehicles observed in multiple frames, thereby reducing the need for manual data annotations. From the video collected from our drone experiment, we automate the monitoring of the outdoor parking areas over time and days. We conduct a comprehensive analysis of the occupancy rate of each parking area, encompassing both off-street and on-street parking lots, as well as dynamic interactions between different locations, and also examined the turnover rate of individual parking spots. This research represents a significant innovation in the use of drones for parking studies, providing an effective, versatile, and insightful approach for studying urban mobility and traffic management.
Kim et al. (Fri,) studied this question.