The parking industry is being transformed by new technologies that are enabling cities to significantly reduce levels of congestion. It is estimated that drivers searching for parking are responsible for about 30% of traffic congestion in cities. Sensor networks that detect vehicle occupancy are providing the basic intelligence behind smart parking systems, but other players are emerging with alternative products and strategies for reducing congestion.
Sensors and Their Limitations
Sensor networks, which generally consist of sensor hardware, communications technologies, and software applications, provide real-time parking availability information to make it easier for drivers to find a parking space. Large cities such as San Francisco, Los Angeles, and Moscow, among others, have adopted these types of sensor-driven smart parking systems that have demonstrably improved the chronic congestion in their respective city centers. According to Navigant Research’s new report, Smart Parking Systems, the installed base of sensor-enabled on-street smart parking spaces is expected to surpass 1 million worldwide by 2024.
Sensors provide excellent accuracy into vehicle occupancy, and Navigant Research estimates that sensor costs are decreasing by 10% to 15% per year. Nevertheless, the primary barrier to more widespread adoption of sensor-driven smart parking networks is the high upfront cost for cities to buy, install, and run the sensors. It can cost cities anywhere from $200 to $350 in upfront costs per parking space to install a sensor network, in addition to monthly software fees.
Some new players in the market, such as Parko and ParkAide, are looking to offer cities a different parking solution at a significantly lower price tag—but with much less accuracy than sensors. Israeli startup Parko raised $1.1 million in seed funding in mid-2014, and uses crowdsourced data to help drivers find available parking spots. The company uses advanced algorithms analyzing anonymous data from when people park on the street, which spot they park in, and when they leave. This data is combined with GIS land-use information, parking supply figures, road types, regulations, current traffic, day of the week, weather, holidays, and local events to determine which streets and parking spaces are more probable to have open spots. This creates scenarios on the company’s app such as “most probable” and “least likely parking availability.” Similarly, ParkAide’s Mobile Parking Availability product is a general public mobile application that shows and direct consumers to a probable open parking space.
While Parko and ParkAide offer an innovative and lower-cost parking solution compared to sensors, they are unlikely to replace the use of sensor networks for smart parking. The advanced algorithms, while likely helpful tools, do not provide the accuracy of sensors. Above all, they do not provide city transport departments with the control over parking fees and regulation that smart parking systems do.
These companies will also need to prove their apps’ utility to drivers in real-world situations. Residents living in cities with high traffic congestion often already know which streets are more likely than others to have parking availability. Nevertheless, if these algorithms are able to provide help to drivers unfamiliar with an area, then they will have a role to play among the range of new urban mobility options that are emerging.
Tags: Clean Transportation, Sensors, Smart Parking, Traffic & Congestion, Transportation Efficiencies
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