The parking industry has for long tried to solve the issue of detecting how many people are parking, where and when, and how many spaces are unoccupied at any given time. Crowdsourcing offers a solution that is both cost-effective and accurate compared to previous attempts.
Curbside parking is monitored with sensors to detect occupancy rates, but the process is problematic.
Monitoring parking space occupancy has been a challenge in the industry for a long time. Information about occupancy rates helps motorists to find parking easier and parking providers to gather information about parking patterns, so there’s a clear incentive for solving the problem.
This has been especially a question of curbside parking, because closed entities such as parking garages are able to monitor parking through gate sensors at entrance and exit. When it comes to on-street parking, the procedure is much harder because streets are open environments that basically need a separate sensor for each parking space.
San Francisco’s sensor program proves the need for parking data.
The most famous example of street sensors is probably San Francisco. They introduced SFPark pilot project in 2010 and in the following years, the city installed magnetic sensors underneath over 8000 parking spaces in order to obtain parking data and manage dynamic pricing. The process of starting the program was inarguably huge with the installing of sensors, and it was only in parts of one single city.
The SFPark program has indeed improved the city traffic in many ways, and it’s clear that communicating available parking does help both motorists and parking providers through easier parking and lesser emissions. The price tag of the program, however, ends up somewhere around $20 million, which is very high when it’s considered that the monetary return of the investment cannot be predicted: How much does the economy grow simply because people find parking better? Are there sustainable effects? The cumulative results can be seen in 5-10 years, so such investments definitely have an unknown factor.
Maintenance, re-installing and adding new parking spaces to the system are also all consuming tasks that take the costs higher indefinitely.
Crowdsourcing is an alternative way of gathering data, and it has a lot of benefits.
Now, let’s take a look at another way of collecting data. Crowdsourcing is a method of gathering information directly from users for users. It works by allowing users themselves to enter information into the given service in real time, and in return being able to make use of information others provide. To demonstrate the benefits of crowdsourcing in comparison to sensors, we’ll use an example from the mapping industry.
Google Maps is the dominant provider when it comes to street navigation. Google uses high-tech “sensors” such as satellites to receive data from across the globe for their map service. As for more comprehensive street information, Google uses cars that photograph their environment. However, as the road-system of the world is a constantly changing network of infrastructure, in order to be able to provide up-to-date navigator information Google has to complete manual mapping every six months. An expensive, repetitive process. Even still, the data is not perfect because it’s not submitted in real time.
Waze solved navigation with crowdsourcing – and did it better.
In year 2007, a small navigation company called Waze launched. They attacked the same problem of mapping as Google, but did it through crowdsourcing. With Waze, each app user functions as a “sensor”, and contributes street information to the cloud service. The collected data is readily available to the network of other users, so the service is able to communicate traffic jams, construction work and closed off streets in real time, all with the group effort of the app’s users.
So, it turned out that not only was the traffic information provided by Waze users better and more comprehensive than Google’s because it was in real time and accurate, the costs were also just a fraction of the huge resources Google had to exhaust. Even better – with user growth, Waze’s resources grew simultaneously because the users are the resource. Result: Google was pretty much obliged to buy Waze in 2013 (for over $1 billion!) because it was a real challenger to Google’s strong position.
And the same could apply to on-street parking too.
The above example goes to show that crowdsourcing has undeniable benefits when it comes to accuracy, real-time information and resources spent. Now, how is all of this related to the parking industry?
Very much, actually. The “network” of curbside parking spots in a city is just as complex as the street network itself. The occupancy rates and street parking infrastructure are constantly changing, and data collected by installed sensors is not effective enough in keeping up with it. There is an almost endless number of variables to take into account when it comes to day-to-day real-time data, and so far no one has managed to build a sensor system that would work near flawlessly in a street-parking environment – at a reasonable cost and good scalability.
What if the parking industry used crowdsourcing instead of sensors?
Instead of expensive, high-maintenance and location-tied sensors, parking data could be generated with crowdsourcing apps. What if motorists, parking companies and cities had an incentive to inform each other in real time about the changing environment? Motorists could instantly see the occupancy rate of a given street, because drivers would themselves be able to communicate where they are parked or where they have just vacated a space. Parking providers would also be able to collect valuable data about the changes and patterns of occupancy, and also communicate this information back to motorist for a better working city as a whole.
This would not only be a quality improvement in measuring curbside occupancy rates, but could also be used in all traffic and parking management. The beauty of crowd effort is that the more people are involved, the better the quality and volume. Every smartphone is indeed a high-tech sensor, so why not introduce a crowdsourced system for parking?
Crowdsourcing is the most cost-effective and comprehensive way to collect on-street parking data.
To sum up, we can conclude that as far as cost-effectiveness and quality go, crowdsourcing is a much better solution than the traditional methods for tracking traffic or occupancy rates. While the sensor programs prove that real-life parking information is very valuable for cities, relying on expensive processes that require installing is not without problems. With crowdsourcing, the same benefits could be received with the group effort of motorists, cities and parking providers, constantly and in real time.
A small company like Waze being able to challenge the mapping giant Google with this simple strategy is proof that crowdsourced data is the direction of the future in parking as well. Just like GPS, it’s pretty much a no-brainer in creating a great user experience and offering parking providers better and more exhaustive results with fewer resources.