Real time parking is a tricky business.
The main objective of real time parking is trying to solve what industry insiders are beginning to refer to as the “Shoup” dilemma. Simply put, a high volume of urban congestion is caused by people unnecessarily circling the block for parking. Ideally there should be a functioning driver alert system that points people to available spaces in real time. With multiple visions being shepherded to provide for the needs of drivers, we must begin by exploring the most effective solutions to the this problem.
The most obvious solution within the parking and transportation industry is clearly the ability to tell the driver where an exact parking space it at any given time. Recently, some cities have begun experimenting with on-street sensors (resembling a hockey puck) that are planted in each parking space. This method will indeed provide good data if done properly, however, it may not be the easiest and most efficient solution. For starters, many municipalities in today’s economic climate cannot afford the absurd installation costs it would take to get these hockey pucks in the ground. The long lead time for the RFP process,the actual installation, the data gathering, and finally consumer distribution are also contributing factors. It also begs the question: does telling a driver where exact space vacancies are create an unwanted scenario of more cluster/competition among drivers eager to be the first to get to a space?
Furthermore, when a driver is downtown within a couple blocks from their destination, this is the time they start considering their parking options. Because parking is such a perishable good (i.e. spaces come and go very quickly), if a sensor tells you there is a vacant space, chances are by the time you arrive it will be taken by someone else. What a driver REALLY needs to know, at any given time, is which area will be the most likely place to park with the shortest wait. Fortunately, sensors are not needed for this information. This can be done with an intelligent system that derives data from various real time and static sources e.g. live meter transactions, pay by phone records, and even other data unrelated to parking – weather, time of day, day of week, events, etc. Essentially, the goal is to create predictive “heat maps” that would inform the drivers of the best available parking locations in real time. Why go the extra distance with costly sensors that could potentially create more chaos on the streets?
So this is a call to the industry to use some finesse and creativity to solve this problem. Instead of tearing up streets and wasting tons of money, we can do all this with exciting infrastructure and some awesome technology.
For more information on Parking In Motion’s heat maps, please contact us @ email@example.com.