Analysing existing parking areas and structures has proven to carry a great amount of data on mobility dynamics and user behaviour that can be only revealed through appropriate survey methods. For this reason, appropriately devised survey methods for informing the forecasting and design process is becoming increasingly important for mapping parking occupancy, traffic distribution patterns, parking places desirability index, on the basis of parking layout and desire lines.
User behaviour surveys done for the existing surface parking at the Curno shopping centre in the Province of Bergamo (Italy) represents a very good example in terms of method and results. In addition to inbound and outbound traffic counts during the 2 peak hours of the day, a license-plate survey was carried out for a significant sample size comprising cyclical and periodic registrations of license plates of predefined rows of parking places for recording average duration of stay and parking places choice preference. The survey allows to map the preferred parking places and define a score for each of them, calculated on the basis of the stall occupancy throughout the overall shopping centre opening hours. A GIS-based spatial analysis is then developed, to estimate the coefficient for pedestrian and vehicular distances, through statistical inference. The produced maps combine a wide set of data regarding each single stall into a single analytical framework. Results are often surprising as the symmetric building and parking configurations show asymmetrical behaviour, comfort levels and attractiveness scores, often influenced by external factors, such as road connections, adjacent functions, etc. and internal factors related to functional distribution inside the Shopping buildings.
Curno Parking Occupancy Rate Map and Curno Parking Isometric Map.
Mapping existing complex phenomena can only be detected through advanced static and dynamic surveying and modelling instruments and are significantly informative during the design process. This allows to empirically calibrate assumption factors and indices taken in design exercises, validate modelling results and fine tune design principles through reverse engineering. In conclusion, empirical data extraction and analysis together with modelling and projection platforms act complementarily and reciprocally to feed into one another and enhance analytical and design processes for improving comfort levels, attractiveness of parking places and overall functionality of parking areas.