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Universal scores for accessibility and inequalities in urban areas
Motivations
High entrance barriers
You need a Ph.D. in the specific domain to do research. But sometimes even to understand the results.
Overspecialization in Science
Very difficult to cross the branches of science.
Slow learning
curve
Very difficult to perform self-education path
images:[
Branch Tree Drawing Clip art - branches clipart @kisspng
,]
Components
"Simplicity is the ultimate sophistication"
Data visualization
Interactive visualizations of results.
Gamification
Involve general audience to partecipate.
images:[
Jegi - flickr
]
Motivations 2
I was born in Rome
I had a very difficult childhood
Rome public transport are "not so good".
Ok. But how much compared to the other cities?
Where is the better served [by public transport] place in the city?
And in the world?
Urban Accessibility measures
Urban Accessibility measures
Huge scientific literature
The first definition of accessiblity in urban context is done more than 50 years ago
Many different definitions of accessibility
But no attemp to compute it at large scale.
A science of city needs quantitative measurement.
We want easy to understand, easy to compute and meaningful quantities to measure public transport efficiency.
And we define and measure them.
Boundaries and Tessellation.
It is possible to compute isochrones
First step towards an accessibility measure:
The larger isochrones are, the faster you move.
Velocity Score
Consider the Area of the Isochrone a time \(t\) computed in \(P\):
\begin{equation}
r(t,P) = \sqrt{\frac{A(t, P)}{\pi}}
\end{equation}
dividing by time, we obtain a quantity with the dimension of a velocity:
\begin{equation}
v(t,P) = \frac{r(t,P)}{t}
\end{equation}
Integrating over time:
\begin{equation}
v_{score}(P) = \frac{\int_0^{\infty} v(t, P) f(t) dt}{\int_0^{\infty} f(t) dt},
\end{equation}
\(f(t)^1\) is the daily time budget distribution for public transport.
The Velocity Score can be consider as the average velocity of a daily typical trip taking a random direction from \(P\).
\(^1\) Robert Kölbl, Dirk Helbing. Energy laws in human travel behaviour. New Journal of Physics 5, 48 IOP Publishing, 2003.
Velocity Score
Average velocity taking a random direction
Paris
Rome
interactive maps and more cities:
Sociality Score
Consider the populations inside the Isochrone a time \(t\) computed in \(P\):
\begin{equation}
s(t,P) = \sum_{i \mid t_i(P) < t} p(h_i),
\end{equation}
we sum over all the hexagons with time \(t_i\) less than \(t\) and \(p(h_i)\) is the population within \(h_i\).
\begin{equation}
s(P) = \frac{\int_0^{\infty} s(t,P)f(t)dt}{\int_0^{\infty} f(t) dt},
\end{equation}
\(f(t)^1\) is the daily time budget distribution for public transport.
The Sociality Score quantifies how many citizens it is possible to reach with a daily typical trip starting from \(P\).
\(^1\) Robert Kölbl, Dirk Helbing. Energy laws in human travel behaviour. New Journal of Physics 5, 48 IOP Publishing, 2003.
Sociality Score
Number of people is possible to reach in a typical day trip starting from a point.
Paris
Rome
interactive maps and more cities:
City Rankings
City Velocity
Velocity Score per person
City Sociality
Sociality Score per person
Cohesion
City Sociality divided by total population
Distributions
Values distribution
Area distributions - Population distributions
Inequality distribution of
accessibilities
Exponential decay from the center of the city.
fitting function: \(f(t) = e^{-t/\tau} + \sigma_0 \)
Exponential decay from the center of the city.
fitting function: \(f(t) = e^{-t/\tau} + \sigma_0 \)
Why these patterns are observed in all cities?
Are these inequalities unavoidable?
Can be modified or optimized?
In which way?
CityChrone
Interactive platform
Citizen Science [DataViz & Gamification]
SETI@home [1999]: analyze radio signals, searching for signs of extraterrestrial intelligence. People can partecipate using their PC, donating their computational resources.
foldit [2008]: fold the structures of selected proteins as perfectly as possible, using tools provided in the game. Nature paper with credits more than 57000 authors.
Quantum Moves [2012]: simulations of logical operations in a quantum computer. Played over 8 million times by more than 200,000 players worldwide.
The 200 000 players were all beaten by the stochastic optimization method. :(
Algorithms: routing in urban context
Walking routing algortimh:
OSRM
New class of public transport routing algorithms:
CSA [2013],
RAPTOR [2011]
This new class of algoritms are easy to implements and fast, but they have some crucial limitations in urban context.
They needs to be closure by transitiveness in the walking path.
We modified the CSA and the RAPTOR algorithm in order to use it in urban context.
CityChrone
Interactive platform
Now I know how much Rome public transports suck
What we have to do to reach Paris?
What are the best interventions given a budget?
Let's Play!
CityChrone
Interactive platform for exploring new scenario
Budget: 5 Bilion €
Name Scenario: Gram Author: Pietro
After 1 year
Name Scenario: rer + circle Author: mat
Useful Links
Interactive platform:
Open Source and Open Data:
Article:
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