The MIT Senseable City Lab recently developed something called the Green View Index. It is a measure of a city’s tree canopy. Below are the GVIs for Boston (18.2%), Geneva (21.4%), London (12.7%), and New York (13.5%). You may have to zoom in.
And here is a screenshot of Toronto. We have a GVI of 19.5%.
The MIT Senseable City Lab recently teamed up with a few other research groups to investigate the relationship between human interactions and city size. If you happen to be a member of the Journal of the Royal Society Interface, you can download the full report here. But in true ATC fashion, I’m going to give you the Coles Notes version here.
What the study did was look at billions of anonymized mobile phone data in both Portugal and the UK in order to determine how our real life social networks change with city size. And what they found is a pretty consistent relationship:
[T]his study reveals a fundamental pattern: our social connections scale with city size. The larger the town you live in, the more people you call and the more calls you make. The scaling of this relation is “super-linear,” which means that on average, if you double the size of a town, the sum of phone contacts in the city will more than double – in a mathematically predictable way.
What’s interesting about this finding is that it starts to explain how cities–and the clustering of people–can act as fertile ground for the exchange of ideas and knowledge. The bigger the city the more people you probably know.
The index was developed by methodically scanning for trees in Google Street View panoramas. The reason street view was used – as opposed to aerial photography – was so that they could capture the human experience at street level.
All of MIT’s interactive city maps can be found here. It’s also interesting to pan around and see which neighborhoods are the greenest – particularly if you are familiar with the city.
One thing I noticed is that large green spaces such as Central Park, High Park, and Stanley Park don’t show up as very green. And that’s because the index uses car-based street view data. I feel like these green spaces should count for something though.
Earlier this year, researchers from the Massachusetts Institute of Technology, the Swiss Institute of Technology, and the Italian National Research Council developed something that they call “slot-based intersections.” In a world where cars have sensors and drive themselves, it is intended as a more efficient alternative to traditional intersections. Goodbye traffic lights.
Much like air-traffic control, the way the system works is by assigning individualized time slots to each car for when they may enter an intersection. For example, in the diagram below (Sequence 01) the car approaching from the bottom left (#10) has a “stop distance slot” in front of it reserved for 3 of the cars that are currently in the intersection. The two that are traveling perpendicular to it and the car currently turning left into the same lane as #10 (on the other side of the intersection). The car in the midst of turning right (#5) is exempt because there’s no possibility of collision.
In Sequence 02 (below) you can see that car #10 is now turning left, which means it has its own time slot in the intersection. Other approaching cars now have a “stop distance slot” dependent on car #10.
In all cases, cars making a right turn are able to move freely, provided they will not interfere with any other cars.
The researchers estimate that real-time slot allocation might double the number of vehicles that a traditional traffic-light intersection can handle today and, in some cases, it might completely eliminate stop and go traffic.
Often when I write about self-driving vehicles I hear people tell me that cars are still cars. It doesn’t matter whether they are self-driving or not. The same inefficiencies apply. They are not the solution to urban gridlock. Elon Musk was also criticized (following his Master Plan) for not properly understanding urban geography.
But self-driving cars will create new efficiencies. I am not saying that they are a silver bullet, but I am saying that they will help a great deal. I don’t think that anyone truly understands the extent of these efficiencies, but there are a myriad of possibilities. This Senseable City Lab project is a perfect example.
What I am grappling with right now is the relationship between self-driving vehicles and traditional forms of public transit. Until we get a handle on the efficiencies and overall impact, it’s hard to ascertain how these different forms of mobility will work together. My gut tells me that the lines are bound to get blurry and that self-driving “cars” will feel less and less like the cars we know today.
Below is a video that was published along with the research. If you can’t see it, click here.
But what I’m curious about (I don’t have the report) is if there’s some kind of upper limit. Presumably this “super-linear” relationship tapers off after a certain city size, because there has got to be limits to the number of people we can maintain productive relationships with.
