The Road to Smart Parking
Recently, we posted about the Copenhagen Smart Parking API being available to partners. What we didn’t tell you, was how we arrived at the solution with an API when so many others have gone down the road of hardware based solutions such as cameras and sensors.
Finding the nearest available parking space
An increasing demand on parking spaces in Copenhagen means more search traffic, which means higher emission of CO2 and air pollution. In 2016, the City Council decided to finance a smart parking solution, with the purpose of making it easier to find an available parking space.
Cities around the world have invested in smart parking solutions based on sensors and/or camera technology. An early stage pilot in Copenhagen’s urban testbed, Street Lab, made it clear that the right solution for Copenhagen would not be smart parking sensors, but instead a machine learning solution that would crunch the data already available through digital parking payment and other sources.
Tests and market dialogue showed the way
Copenhagen Solutions Lab supported The Technical and Environmental Administration in conducting a market consultation with technology providers and universities. At the same time, the city took a thorough look at the urban infrastructure for smart parking. Factors such as no street lamp poles, heritage buildings, non-marked parking booths and lots of trees. introduced an extra layer of complexity to a sensor-based solution. This, as well as the market consultation, pointed in the direction of machine learning with several advantages:
- Lower investment costs, as the solution is not dependent on a large scale hardware and network deployment
- Shorter implementation time, as the solution does not require physical installation of several thousand units around the city
- No further requirements for establishing network connections, configurations of software, or ensuring the necessary power to the hardware
- Lower maintenance costs, as there is no need for a large amount of technical equipment in the urban area
Further, it was now possible to offer a solution that covers the entire city and not just individual neighbourhoods within the initial budget frame.
The solution, which was released in 2018, is based on a collaboration between the City of Copenhagen and private companies. The city has released an API with predictions of available parking spaces that providers of digital parking payment, navigation systems etc. can integrate freely into their existing or new applications for the benefit of the citizens of Copenhagen.
One of the expected outcomes is less congestion on the roads and thus less air pollution due to less search traffic. This is an example of the benefits of doing early stage testing in small scale and in a real urban environment. The result is better decision-making and responsible investments.
Do you want access to the API or more info, then take a look at this flyer.