Sensors and demand-driven pricing are helping cities make parking smart.
Finding a parking space is not a process that most people associate with pizzazz or innovation. Many things have evolved about the way that people drive over the history of the automobile, but finding a place on the street to park that automobile while you run into the store isn’t particularly one of them—at least since parking meters came into use in urban settings in the 1930s.
But this routine, if frustrating, task, has recently become a poster child for some of the most cutting-edge work in urban policy, reflecting much of the current thinking on how to tackle some of the most inefficient aspects of modern city life. Parking is verging on becoming—gasp!—smart.
During the previous Dark Age of street parking, finding an open space was a matter of dumb luck and persistence (circling the block for 20 minutes until you finally accept that it’s easier to park half a mile away than wait for a spot). This process, barbaric though it may be, is the best that could be done in the analog age. Moreover, it was the inevitable result of imperfect information—the driver doesn’t know where the open spaces are, and so has to resort to brute force methods to find one that’s available—and unresponsive prices—within a neighborhood the price of a meter is the same and doesn’t adjust based on the level of demand for a certain block or particular space.
Finding a street parking space in a big city, in other words, has been the modern-day equivalent of trying to get foodstuffs during a period of rationing in the USSR: there is a fixed supply of a good, but consumers don’t know how much there is, and there is no price-signaling system to efficiently distribute the good in question. And beyond the inconvenience to you and your fellow drivers, the additional circling and congestion adds to pollution.
As in so many fields, however, technology—and the ingenuity of some researchers and city administrators—promises to change everything.
At the heart of this revolution lies technology like that announced in 2011 by IBM: sensors determine when a spot is occupied by a vehicle and relay that information to a software suite that maps the real-time occupancy of a city’s parking meters. This system can then be coupled with an algorithm that prices each block or even each individual parking space; a mobile app transmits this information to consumers. The result should theoretically make finding a parking spot quick and efficient, rendering those old methods of spot-hunting obsolete (and reducing emissions for circling cars, to boot).
San Francisco and Los Angeles led the way in implementing pilot programs. LA Express Park pilot program was implemented on 4.5 square miles of downtown LA, with a target of 10-30 percent of spots open on any given block. SFpark, in contrast, implemented a pilot program on 7,000 of the city’s 28,800 metered spaces and also included over 12,000 spaces in 15 publicly-owned garages as well, and was aiming for approximately 15 percent of spaces open for each block. Prices can reach a maximum of $6 per hour for most spaces depending on demand, with an allowed maximum of $0.25 increases per hour or $0.50 decreases per hour (note that once a resident has parked their car, the price that they pay remains fixed, so they don’t have to worry about their rate changing while shopping).
Results have been relatively promising. In the first six months of the LA trial, the program saw a 5 percent reduction in underutilized spaces and a reduction in parking congestion of 10 percent and a 2 percent increase in revenue. This was accompanied, however, by an 11 percent decrease in parking rates overall, with a survey indicating that 76 percent of drivers would park in the surrounding areas where parking was now cheaper. In San Francisco, one year after implementation changes in price were found to successfully increase occupancy for underused blocks and decrease blocks approximately two-thirds of the time, suggesting an overall success at maintaining the desired number of open spaces. The program was also recently recognized as one of the top ten urban innovations worldwide by Sustania.
Neither system was perfect, however. The pilot programs were relatively restricted and the LA example suggests that rather than just introducing fluidity into the system, a substantial portion of drivers may just park outside of the test area, shifting congestion into the surrounding neighborhoods and straining the old-school parking system in those areas rather than just encouraging a more dynamic parking system overall. To reach the ideal imagined by city officials, the area will likely need to be expanded and residents permitted time to fully acclimate to the new system rather than just avoiding the area completely. This lack of awareness of the program also hindered efforts in San Francisco, in which some drivers simply didn’t know that they could find cheaper spots on the next block.
Furthermore, the current versions of the concept largely ignore the fact that drivers will need to be constantly consulting their phones while negotiating city traffic to find that perfect space to suit their needs; not necessarily a safe prospect. If one day the parking information is displayed on the heads-up display on all new vehicles, the implementation will likely be safer and easier for the driver.
But these smart parking efforts reflect more than the sum of their parts; more than just another innovative solution to a mundane, everyday problem, smart parking embodies much of the current thinking of urbanist policymakers. Entrepreneurs and policy wonks alike are using technology to increase the information available to both producers and consumers in transactions that have previously lacked data. And in doing so they are creating markets where there once were none.
Time will tell on whether these smart parking systems will live up to their name. But for the moment, perhaps it’s enough to be grateful that something as mundane as a parking meter can every now and then be an indicator of change and innovation.
This story was originally published by Data-Smart City Solutions.