Drone-Assisted Parking

Can a drone help you more easily find parking? These and other traffic-improvement ideas were explored thanks to Siemens’ Mobility IDEA Contest.

by Chad Vander Veen - Editor, FutureStructure / January 20, 2015

For cities, parking can often prove a double-edged sword. It’s a major source of revenue but also a primary cause of traffic congestion and headaches for motorists. In the last few years many “smart” parking solutions have been conceived and some implemented, such as embedded sensors that relay to a smartphone when a parking space is available. But instead of tearing up the asphalt to build in these sensors, what if cities used drones to monitor parking availability?

This and other traffic-improving ideas from around the world were brought to the table via Siemens’ Mobility IDEA (Improving Design and Engineering for All) Contest. Launched at last year’s ITS World Congress in Detroit, the contest concluded January 15 with the “Smart Parking Lot Using Quadcopter Network” proposal earning the top prize.

University of Massachusetts, Dartmouth student Amir Ehsani Zonouz submitted the winning idea. The second place idea was submitted by Clemson University student Sakib Khan for technology that allows for safe pedestrian crossings, according to Siemens, and third place was submitted by Technical University Munich student Sasan Amini on self-parking autonomous vehicles.   

Nearly 400 people submitted 180 ideas, said Ben Collar, head of U.S. Research & Development for Siemens Road and City Mobility. “We wanted to get everybody on board thinking about how we solve the traffic problems we face today and tomorrow. Nowadays it’s becoming apparent you can get a lot of interesting ideas, you can help move the bar, when you also engage the public. So we were interested to understand what kind of problems the public saw as important in the future as well as what kind of solutions they could come up with.”

According to Zonouz’s proposal, parking could be improved by using an autonomous quadcopter network.

“Quadcopters find free spots, and the shortest path to those spots and finally guide the driver to the best spot.”

The Quadcopters could also monitor conditions for people or pets in cars susceptible to heatstroke or be on the lookout for any suspicious activities. Zonouz also suggested that quadcopters could be outfitted to monitor incoming vehicle flow or different parts of a complex parking lot and use machine learning to identify drivers’ favorite spots

Collar said that some cities may not be interested in ripping up streets to install sensors that eventually need to be replaced. Many places are not going to be so interested in in-ground sensors because they have to be replaced after a while, the battery life is what it is, and when you have to replace those sensors that’s an additional incurred cost.

“It can be pretty costly to tear up the asphalt and put it back together again,” Collar said. “So this avoids having to electrify the parking lot. Not very many parking lots have electricity over the whole lot. They might have the lights but that’s it. But otherwise there’s not a lot of electricity out there and that’s very costly, especially for big lots. And when it comes to big lots, having a mobile monitoring system is pretty much ideal. It avoids that infrastructure cost and allows for a lot of flexibility.”

The second place idea, a vehicle-to-pedestrian warning system for safer road crossings using dedicated short-range communication technology. The third place idea, a self-parking vehicle solution, envisions drivers being able to exit their cars at a desired location and the cars then shuttling themselves off to find a parking space.

“A lot of car companies are developing self-parking capabilities,” said Collar. “On the infrastructure side there still needs to be information made available to the cars so they know where to park. That’s what this idea was about.”

Having been chosen as the top entry, Zonouz's proposal has earned him an invitation to visit a Siemens site to work on a prototype of the quadcopter system.

All submitted ideas went through three stages of consideration. In stage one, ideas were judged via a crowdsourcing model. The top ideas from stage one proceeded to stage two, which required a technical analysis and high-level architecture. Finalists were then asked to put together a high-level business model. Those were then put in front of a jury and applicants had five minutes to pitch their idea.

Though there were only three winners, the contest yielded a number of interesting proposals, including leveraging the Internet of Things to understand a city as an organism and a low-cost OnStar-type solution for drivers in countries or regions where communications infrastructure is lacking. That idea, submitted by Dmitry Potemkin of Russia, particularly resonated with Collar.

“His idea was basically to send location information and information about the fact that this really is an emergency that’s happened in his car,” he said, explaining that in parts of Russia emergency response may be hours away or responders may not take emergency reports as credible. “For me it was really eye-opening because I guess I’ve gotten so used to the idea I always know where I am because I have a smartphone. This helped me come back to the idea that there are places in this world that have very different infrastructure and traffic problems."

For the winner, Collar said the next step is where the fun starts.

“We’re going to get together and having a hacking session for two or three days, have some fun, and produce something that the world can look at and we can gain some understanding about the possibilities for the system.”

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