Parking is not just an annoying part of the driving experience; it is also a source of approximately 30% of congestion in cities. That’s why there’s so much opportunity for parking apps—designed for commercial fleets as well as individual consumers—that make it easier to find parking, pay for it, and keep track of usage. In this post, I’ll describe how parking app developers can create much more powerful experiences by integrating car data into their apps.
Parking App Functionality Requires Both Aggregate and Personal Data
From a developer’s perspective, parking apps are unique in that they require both crowdsourced data on parking spot availability as well as personal data on the driver.
Today, this data typically comes from different sources:
- Crowdsourced data comes from sensors embedded in parking spots and/ or security cameras
- Personal data (including the vehicle’s location) comes from drivers’ cell phones
Car data, generated by sensors in connected cars, provides for better accuracy, more convenience for drivers, and relatively simple integration. Car data can help parking apps:
- Guide drivers to available parking spots, with real-time information on which spaces are open and predictive algorithms based on historical data
- Give drivers richer information about the spots that are available, so they can find parking that suits their vehicle size and preferences
- Offer a personalized experience based on the location of the car
- Enable fleet operators to monitor and optimize their parking costs
Integrating Data on Parking Spot Availability
In the past, parking applications have relied on embedded sensors and/or security cameras to determine where spaces are available. These sources lack consistency across cities and across public and private parking facilities. Today, developers can use data generated by connected cars’ ultrasonic sensors to gain continuous visibility into on-street parking spaces. The Otonomo Platform makes this parking data available for more than 90 cities in Europe and North America. The data is de-identified and provided in aggregate form, to protect driver privacy. Developers can access the data via a POST API request.
The basic request looks like this:
Integrating Data to Define Parking Spot Preferences
Car data also enables parking app developers to characterize available parking spots by length, depth, angle, and other attributes. With this unique data, drivers can define detailed requirements and preferences that help them find the best parking spots for their needs, for example:
- Lowest cost versus closest
- Parking with specific payment methods available
- On-street parking versus garage parking
- Only parking spaces above a certain length
- No parallel parking spaces
Parking spot preferences are a way to increase user engagement with your app and make it a valuable companion for every city trip.
Vehicle Location Data
Vehicle location data gives developers a way to guide drivers to available parking spots close to their destinations. While smartphones also provide location data, getting vehicle location data directly from the car will make it simpler to integrate your parking app into an OEM’s infotainment system. Furthermore, you can use vehicle location information from car data to guide the driver back to his or her parked car, a feature that is not possible if the app relies solely on cell phone location data.
Otonomo is one of the only automotive data service platforms that provides access to personal data from leading OEMs as well as crowdsourced parking data. Our platform helps all parties address the consent management flows needed to access personal data while staying in compliance with privacy regulations.
Real-Time Data Availability
Minimal data latency is critical for parking applications, since on-street parking in cities is often reoccupied within a minute of being empty. With the Otonomo Platform, parking data is available in near real time through our API.
Get Our Parking Datasheet
Want to learn more about how to integrate parking data into your application? Our datasheet provides detailed information about the data parameters available through the Otonomo Platform.
