Economic theory, smartphones, sensors and analytics beat expensive, brick-and-mortar solutions.
By Hank Shaw
It’s rush hour. And you’re looking for a prime parking spot in one of the world’s great cities. So what do you do? You drive around waiting for a spot to open up, burning fuel, losing your patience, and wishing there was a simple solution.
But what if your city doesn’t have the money or space for a brand-new garage in the city center? Are you doomed to the rush hour equivalent of a wild parking space goose chase every day?
Well, here’s the good news. There’s another approach that replaces a traditional brick-and-mortar solution with sound economic theory and innovative technology. Here’s how it works.
A quick look at dynamic demand management
The first step is to adopt the economic concept of demand management by implementing dynamic parking pricing.
Here’s what it means: The price of parking goes up in the most popular areas during times of peak demand. Meanwhile, a few blocks away where there’s less demand, the cost of parking goes down.
So unless people want to pay a premium for the most popular parking spots, they have an incentive to go a little out of their way to find a cheaper parking spot. Which helps level out the demand in the busiest areas.
Proving the concept
In theory, it’s an easy idea to grasp. But to make it work, you need sophisticated technology to monitor demand in real-time, adjust pricing, and help commuters quickly find an open parking space.
Of course, that may seem like a futuristic solution. But guess what? It’s already in use in the city of Los Angeles’ busy downtown area today.
On-street parking spaces are equipped with a wireless sensor that provides streaming data on parking availability. So “the system” knows which spaces are available at all times.
Thanks to advanced transportation analytics, the system also has the capability to quickly identify patterns, predict the level of demand at different times of day, and set parking prices that are based on the time of day.
OK. So far we have a demand management system that works great for the city. But what about commuters?
With help from smartphones, GPS technology and that hard-working network of parking space sensors, you can let drivers know exactly which spaces are available. You can even provide turn-by-turn directions. How’s that for convenience?
Of course, this intelligent parking solution is just one example of how demand management is bringing more efficiency to the world of transportation. After all, cities like Stockholm and Singapore are already adjusting tolls on congested highways during peak times to reduce traffic jams and bottlenecks.
Happier commuters. Less wasted fuel and damage to the ozone. More efficient use of costly infrastructure. Plus, some of these innovations can even boost revenues.
Now you know why there’s going to be a lot more demand for dynamic demand management in the future.
Based upon the article “How economics and machine learning can tackle transportation congestion,” authored by Xerox Research Centre Europe (XRCE) researchers Onno Zoeter, Christopher R. Dance, and Stéphane Clinchantas well as Eduardo Cardenas, a Xerox analyst whose interests include machine learning, data mining and data analysis for parking and transportation problems.
It is from a series of articles from XRCE researchers that celebrate the lab’s 20th anniversary.