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 destination. The cars aren’t drawn to scale and there are 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 choose 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.)