Aug 052015

A huge amount of urban traffic comes from cars circling for available parking. Robot fleets could change all that.

Image Amr Dalsh / REUTERS
Amr Dalsh / REUTERS

Traffic jams aren’t exactly Zen. People are anxious about getting somewhere else instead of being happy about where they are.

To make matters more frustrating: In many cases, the cars clogging roadways are often already at their destination—and just circling the blocks looking for parking. There’s plenty of research showing that a surprisingly large number of people are driving, trying to find a place to leave their car. A group called Transportation Alternatives studied the flow of cars around one Brooklyn neighborhood, Park Slope, and found that 64 percent of the local cars were searching for a place to park. It’s not just the inner core of cities either. Many cars in suburban downtowns and shopping-mall parking lots do the same thing.

Robot cars could change all that. The unsticking of the urban roads is one of the side effects of autonomous cars that will, in turn, change the landscape of cities—essentially eliminating one of the enduring symbols of urban life, the traffic jam full of honking cars and fuming passengers. It will also redefine how we use land in the city, unleashing trillions of dollars of real estate to be used for more than storing cars. Autonomous cars are poised to save us uncountable hours of time, not just by letting us sleep as the car drives, but by unblocking the roads so they flow faster.

Donald Shoup, a professor of urban planning at the University of California, Los Angeles, wrote a book called The High Cost of Free Parking, about how low-cost parking ruins cities. He estimates that cities that underprice their parking encourage circling, resulting in roads where up to 45 percent of the traffic is people looking for a place to park. His solution is for cities to boost the cost of street parking until there are usually a few free spots on each block.

Robot cabs don’t need to park. They just move on and pick up the next fare. Human-guided cabs don’t need to park much during the day either, but even in the densest cities there aren’t enough of them. In Manhattan, there are 100,000 off-street parking spots alone below 60th Street and even more on the streets. New York City brags that there are 500 metered spots that accept credit cards in the Broadway theater district. But there are only 13,150 Yellow Cab Medallions for the entire city. In the future, when demand ebbs at the end of the day, robot cabs can simply move to the edges of the city for rest, refueling, and repair—all out of the way.

To study this effect for myself, I built a simulator with rows and rows of city blocks filled with little cars headed for random destinations. The cars aren’t drawn to scale and there is no effort to simulate stop lights or collisions, but even in this simple model, the streets quickly clog up. If a car reaches its destination and there are no more parking spaces, it chooses a new destination at random, turns grey, and starts circling.

Here’s a video showing how the simulator works:

What’s striking is that the streets start clogging up when 15 percent to 25 percent of the blocks are full. If the cars can’t find a place to park in one section, they start bouncing around looking for another and jamming the streets. And because finding another spot takes almost as much time as getting to the destination, they start to fill up the streets quickly.

Here’s one video showing the simulator just after the first few blocks are full. The percentage of cars searching for parking starts to soar.

This next video is taken later in the simulation when more than 60 percent of the blocks are full. Most of the cars on the streets are on a quest for one of the open parking spots.

Notice that most of the empty spots are toward the bottom. The procedure for choosing a random location does not pick initial destinations uniformly, effectively simulating cities where some blocks are more desirable. Once the major destinations start to fill up, it takes some time for the cars to find the empty locations. They don’t have access to any central database of empty spots so they circle mindlessly until they happen upon an empty spot. (The simulator is very basic and full of poor approximations of the way that humans look for spaces. One researcher, for instance, suggests that people circling for parking often take right turns at red lights because they don’t want to wait. The simulator doesn’t try to be that smart: It just chooses a new destination nearby at random. The source code for the simulator is written in a game platform called Construct 2 and is available to anyone who wants to play with it and make it better. You can play with the simulator yourself here.)

Some parking garages have installed sensors that count the number of empty spaces, and signs to share this information to keep people from driving down full aisles. When autonomous fleets take over, they’ll have access to similar databases. The cities will probably keep a few parking spaces around for cars that need to pause but most will probably be repurposed as parks or retail locations.

Even though the simulator I used is just an approximation, it supports researchers’ findings about just how many cars in urban environments are looking for parking at any given time.

The results also show that autonomous cars have the potential to change urban life dramatically. If replacing the human drivers and their need to park will reduce the demand for the roads and eliminate the stressful traffic jams, it will make city life that much more peaceful. Maybe not Zen, exactly, but more like it.

This post originally appeared on The Atlantic.

Original article.

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