Could technology be the answer to our parking woes?
Impossible as it might seem, the price of parking can have massive repercussions on the vitality of a city’s downtown. In Part 1, I talked about how finding the right price can reduce congestion and boost business, but that’s not all it can do. The effort to provide parkers with “perfect information” can have a number of positive repercussions.
How, for example, can cities maximize the use of downtown parking spaces? What if a computer program could change the parking rate based on the amount of spaces currently available? That way, drivers could receive the best possible information about availability and parking managers could ensure that the perfect proportion of spaces are used. As long as the system were programmed properly, there would always be spaces available. In addition, the rate would always be low enough to ensure that downtown businesses thrive.
This is part of the doctrine of respected guru Donald Shoup, author of The High Cost of Free Parking, but so far, most cities have been reluctant. The notable exception is San Francisco, which boldly moved forward in May 2009 with the SFPark pilot program. 18,250 spaces across the city are currently priced variably according to demand. The system is calibrated to ensure that 10% of parking spaces are free at all times to reduce the need for drivers to cruise around looking for a spot. Because this is a pilot, the system is constantly adjusted based on data collected from sensors built into the pavement. Prices can fluctuate between $0.25 and $6 for a curbside spot or between $1 and $10 for a garage spot, but they can only change $0.50 per hour, so drivers don’t return to find a much higher bill than they expected.
There is talk of expanding the system as well as implementing an instrument called a Parking Benefit District (PBD). This would involve rethinking parking from the ground up at a neighbourhood scale, but only if local residents vote to approve it. Variable rate parking would be instituted in areas of high demand and residential parking rates would rise; all proceeds from the process would be spent on amenities like improved public spaces and bicycle parking.
My only concern is that San Francisco hasn’t yet reached the economic nirvana of “perfect information”. It would be useful to have access to online maps showing the cheapest places to park, which would allow drivers to type in an address and bring up a list of the closest, cheapest spaces. Text message alerts could let drivers know if their parking is getting more expensive, and could offer information on cheaper nearby spaces.
You might be surprised to learn that I don’t drive. I believe that cars should have as limited a role in day-to-day life as possible. However, finding the right price for parking can strengthen and grow urban cores, which are more walkable and pedestrian-friendly than their suburban competition. The other big perk for drivers and non-drivers alike is that if parking spaces are used more intelligently, our cities will simply need less of them. Fewer parking spaces mean less dead space in the city, and more vitality (which translates into dollars!)
My parking pipe dream involves a system where all spaces are priced variably like in San Francisco, and anyone can quickly and easily find out which spots are cheaper and where via smart cell phones, signposts and computers. Whenever the rate for your space changes, you get a text message. Private parking lots can take part in the system, as well as private individuals with empty driveways. Ideally, a commuter would park in a space during the day and a downtown resident could use it at night. That way, every single space would be used to the best of its potential. The money earned could fund exciting projects, and the resulting efficiencies would mean that more of the city could be claimed for pedestrians.
- post by Denis Agar. Denis lives in Toronto and his post was originally published at PlanningPool.com. CityCaucus has teamed up with PlanningPool.com and cross posts columns of common interest.