Parking occupancy map layer
to help your users cover the last mile
Location-based services are more important today than ever before. Billions of people rely on mobile apps to plan trips, where to eat or how to spend time. Add value to your app by integrating high-quality parking suggestions to improve user experience and to create new USPs.
Traffic data, weather, places, events and certain social indicators – the predictive API considers more than 80 parameters to analyze the parking situation. We deliver the chance of finding parking for street segments and off-street facilities – nationwide. This makes it possible for drivers to make informed decisions where to navigate.
Built for developers
Our predictive API has client libraries for:
- Swift (iOS, OS X, tvOS, watchOS)
- Python (on request)
Authentication is easy and results are returned in GeoJSON format.
Learn more about how to get started by checking our our documentation.
Works with any Map
The predictive API integrates seamlessly with all standard Mobile & Web map frameworks such as Google MapView, Apple Mapkit, Mapbox and others.
Predictive API is already running on top of:
The realtime API offers information on parking occupancy for millions of POIs. Where your users are – not just in the major cities. Currently the service is available within the following specifications. More on accuracy can be found here.
DB Park+Ride is a multimodal service for trip planning by Deutsche Bahn that includes the private car as part of a public transport itinerary. They use AIPARKs predictive API to compute change points and change times between modal switches.
Many cities were approaching us asking for advice and insights on their parking traffic. That’s why we decided to build a new analytics role in our AIPARK studio application for them, aggregating data from the predictive API to provide insights on parking down to the level of individual streets and segments of streets.
UMA (Urban Mobility Assistance) is an intelligent traffic avoidance assistant for every day travel. It relies on an unique algorithm distributing drivers equally on the road network rather than sending them all the same way. UMA has integrated AIPARKs predictive API in their app using the SDKs for Android and iOS to provide their users with a seamless parking experience. UMA is operated by a subsidiary of Volkswagen AG.
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