Parking: May the Best Price Win
William J. Mitchell and the members of the MIT Smart Cities research group are creating innovative ways to change how we live in urban areas through, in part, the application of new technologies that enable urban energy efficiency and sustainability, and enhance opportunity, equity, and cultural creativity. Smart Cities research is particularly concerned with the emerging roles of networked intelligence in fabrication and construction, urban mobility, building design and intelligently responsive operation, and public space. The group explores the new forms and functions of cities in the digital electronic era, and suggests design and planning directions for the future.
Question: What is the solution to combating urban congestion?
Bill Mitchell: There is no magical solution because urban traffic congestion arises from the fact that a lot of people want to be in the same place at the same time often. Like a Red Sox game or something, it’s going to get congested around there. That’s just the way it goes. And so, there’s no magic in all of this. But there are a bunch of things that you can do.
Firstly, our cars are a much smaller footprint than traditional automobiles. Secondly, they occupy much less parking space. Thirdly, they are managed, and this is actually more important, they are managed in a more sophisticated way so you get high utilization rates. You make them available exactly where they need to be available and then get them out of the way.
And then the other thing is, if you think of traffic flow, the way you get throughput, the way you really move a lot of people quickly through a city is not through high speed. This is where having a car that goes 120 mph is useless in the city. What really matters is keeping a uniformed speed. If you can keep steady pace of movement, you can get an enormous throughput. The way you keep a steady pace of movement is by electronic coordination of traffic streams so there is not a lot of stop and start and acceleration and deceleration, but just smooth it all out. That’s really the key thing.
Question: How intelligent can cars become?
Bill Mitchell: A lot of our thinking has to do with creating a sort of market for the resources you need for urban mobility that are kind of transparent where there’s plenty of information in the market where you know what you’re doing and where price incentives enable the management of the system. One example of that is congestion pricing or streets. The typical way to do this that gets thought about these days is very crude. You put a congestion ring around Manhattan and charge people $10 or something if they cost the congestion ring. If you put more information technology into it you can begin to think of things like you monitor traffic congestion on a block by block level of granularity and then you adjust prices in real time, then the more congested the block, then the more it costs you to drive down. And then you can organize a GPS navigation system to do things like, take me the cheapest way to where I need to go subject to a time constraint, or take me the fastest way subject to a pass constraint. And this, I think in the end gives more rational allocation of resources, makes a more transparent system and all of these kinds of things.
Another example of this is, with parking. Right now parking is a terrible market. Parking costs a lot. Prices are fixed, typically. How do you connect buyers to sellers? You can drive around randomly looking for parking space. This is not great. But imagine a system where the automobile navigation system knows where the parking spaces are near where you want to park. They’re dynamically priced and you do an e-bay style auction, essentially. So, you say to your automobile, all right, I’m desperate, I’ve got a dentist appointment in 10 minutes, I can’t be late, just find me a parking space, I’ll pay pretty much anything, just bid high. And it can do that, or I’m a poor student right, and I don’t mind if I walk for 15 minutes. Just get me a bargain, so bid low. So, you can do that kind of thing. And then we’ve already talked about Mobility on Demand where getting access to vehicles, the pricing of that can vary essentially depending on demand. The higher the demand, the more you have to pay for that.
So I think we are going to see a great deal more of systems in which there’s a sort of much more sophisticated pricing and much more sophisticated understanding, both by the providers of mobility resources and by the consumers of mobility resources and what it’s costing and how you want to allocate your resources. Right now it’s very difficult to be irrational about moving around a city. That’s how we want to make it possible for people to be more rational.
Question: Which cities would be the best candidates for Mobility on Demand?
Bill Mitchell: Well I think it has a lot to do with political will and capacity to build desire to do something like this. So, some cities can do that, some can’t. I think there is a complementary to mass transit. One of the best uses of mobility on demand systems is to solve what I like to call the last kilometer problem, or the last mile problem. You know, the subway system for example is extremely efficient, getting from subway station to another subway station, but the subway station where you started is never where you really wanted to start your journey, and the subway station where you finish is never where you really want to end up. Mobility on Demand System can solved that last mile problem. It can get you to the subway station and then you can go very efficiently point to point using the subway system, and then at the other end, out in the suburbs, for example, you can pick up a city car and then the Mobility on Demand System go to where you want to go.
So I think there is an advantage in a highly evolved public transit system that you can develop a synergy with. I think this is important. And then some of it has to do with what kind of physical opportunities exist to build a system too. So, we’ve looked at a number of cities. We looked, for example, at Taipei in a lot of detail. We discovered that, this is obvious if you go to Taipei, it has the highest density of convenience stores in the world. There are 7-11’s everywhere in Taipei. So, an attractive strategy in Taipei is to say, put Mobility on Demand pick up and drop off points outside convenience stores where there’s space for it, the real estate is there. They’re almost automatically in the right locations and there’s a business synergy, and so on. So, that’s a particular opportunity that exists in Taipei.
Take another city we’ve looked at, Florence, which couldn’t be more different from Taipei and the historic and urban texture of Florence is built around the Piazzas that are related to the churches and the old parishes and that kind of thing. And so the strategy there that we pursued is a strategy of putting Mobility on Demand pick up and drop off points in the Piazzas, getting traditional automobile parking out of the Piazzas and giving the Piazzas back to the people as social centers and so on.
So I think there’s no, what I’m getting at is there is no general answer here. There are a lot of conditions that may make a city suitable or not suitable for Mobility on Demand Systems, there is no simple formula. I think it takes imagination and design skill and just looking at a particular city and saying, how would we do it in the particular city? What are the opportunities? What are the constraints? What’s the best way to do this?
The technological barriers are not great, so I think we could build the right kinds of automobiles within a couple of years. I don’t think that’s a long timeline. I think the regulatory issues and the political consensus building issues are potentially the long timeline and that could take many years. I think the cities that are likely to be competitive and are likely to win in doing these sorts of things, the ones who are able to cut through all of that kind of stuff and move quickly and effectively, hard to say which ones though, it could be a place like Singapore for example, which has a history of being able to do things like this.
Recorded on January 21, 2010
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