Integrating Real-time Availability with Parking Payments
By Stefanny Perez
Apart from regulating traffic demand in congested areas, paid parking regulations involve a business model where drivers pay for their infrastructure use, rather than the general population. It also represents a significant source of income for municipalities, which can be invested in infrastructure improvements at the same downtown core and Business Improvement Areas, which in turn can attract more visitors.
However, the management and use of curb spaces represent a challenge for municipalities. It extends towards users who tend to find parking to be a stressful process. Paid parking regulations are often difficult to understand and are represented as text descriptions or static maps, which is not useful for wayfinding. Instead, drivers rely only on parking signs, which may also be confusing as many different regulations apply on the street at different times of the day.
Parking search and parking payment are two different processes and are usually not connected. Optimizing these two layers of the parking process with digital methods not only improves the experience for users but it also improves compliance, occupancy, and turnover, and gives city departments all the information to plan, make decisions, and achieve their goals in aspects like transportation and the city’s public realm.
An interactive map may be the optimal solution to display all the paid parking locations, their prices, and the maximum allowed stay. With a live data feature, users can see the availability of curbside spaces or parking lots in real time. This information enables users to locate their destination on a map and choose the optimal parking location based on cost, distance, and availability.
Cities also benefit from tracking occupancy and turnover rates to manage induced traffic due to cruising. But what is the cost of all this useful data? Live data obtained from parking payment transactions comes at no extra cost from the digital payment system, as it does not require any infrastructure or hardware investments. Therefore, using payment data to measure occupancy and estimate real-time availability is a highly scalable method in any city to achieve 100% coverage.
The future holds exciting possibilities for smart cities. Nothing is static nor are cities, so systems are becoming dynamic and adaptable to conditions.
Adaptive parking prices will help regulate demand and improve the transportation conditions in busy areas, while predictive parking demand will assist users in planning trips. These systems require sophisticated machine intelligence and big data to understand the dynamics of each city and set prices to achieve a city’s goals, whether it is to maximize revenue or occupancy.