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Parking Lot Profiling Analysis: the City of Split Use Case

Urban areas are going through a digital transformation where they are embracing Information and Communication Technology (ICT) to improve the Quality of Living (QoL) for its citizens. In this process, new data sources emerge, such as ground parking sensors which have the role in monitoring parking space occupancy. It is highly beneficial to analyse ground parking sensors data and to conduct parking profiling analysis to discover new knowledge about drivers’ parking behaviour. This new knowledge can be used not only for understanding current parking patterns but as well as for creating prediction models that will have the ability to tell us how many parking spaces should be empty in the specific parking area and in the specific time slot. In this paper, the framework for parking profiling analysis will be presented, as well evaluated on the use case of parking spaces in the area of the City of Split, Croatia. The analysis shows that parking demand in Split is higher during the daily hours than the night hours, and that parking demand is the highest on Mondays and the lowest on Saturdays. For example, the profiling analysis for the most frequently used parking lot in Split shows that there is 18.67% of chance that parking lot will be fully occupied at midnight on Monday, and 20.66% chance that it will be fully occupied at noon on Monday.