In many cities area-wide short-term parking zones were introduced to reduce traffic in search of a parking place and to enhance the life quality. Nevertheless, in many cities with parking restrictions the volume of traffic is still high and parking search traffic is one reason for this problem. Previous attempts aim to overcome this issue by guiding drivers to the next available parking space. These systems are expensive and politically controversial, because they indirectly encourage car use. On the other hand, a pre-trip information service informing road users prior to departure about the occupancy of parking spaces at the destination could have a higher steering effect and encourage people to use alternative transport means. Based on these assumptions a real-time information system for the occupancy of short-term parking zones was developed and tested in two areas in Vienna (Austria). Instead of relying on roadside infrastructure this system uses position data of the mobile phone parking service as an indicator of the occupancy of parking zones. In addition, the potential of two more data sources to improve the reliability of forecasts was tested: model-estimated traffic flow data and counts of short-term parking customers in parking garages. The prediction model was developed and validated with an empirical parking survey. This novel technology helps to administer the scarce resource of parking space in urban environments more effectively and supports people in choosing sustainable transport modes.
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