Physics maps city complexity
Technology Research News
you're trying to find a city that is both easy to navigate, like Manhattan,
and filled with quiet, low-traffic neighborhoods, like Stockholm, don't
hold your breath. These two characteristics of city life are a trade-off.
This becomes clear when you look at city streets as information networks.
Streets are one of many types of networks that are all around us
-- others include the Internet, social networks, and biological food chains.
A network is made up of nodes and the links between nodes. For example,
streets and intersections, Web pages and links, people and social relationships,
and animals and predator-prey relationships.
Researchers from Umea University in Sweden and the Nordic Institute
of Theoretical Physics in Denmark have compared city street networks from
the standpoint of information handling by looking at road maps in terms
of the information needed to locate specific addresses.
The information needed to navigate in a city can be used to quantify
and compare the complexity of cities, said Martin Rosvall, a researcher
at Umea University. The method could eventually be used to allow city planners
to see how street changes affect navigability and could also be used to
make other types of networks -- like supermarket aisles and airways -- work
more efficiently, he said.
The researchers' model assumes that a person traveling along the
streets of the city gets all travel directions in the form of the sequence
of roads that lead to the target road. In networking terms, these sequences
are sets of nodes linked by intersections. From this perspective, all roads
are the same regardless of how long they are. The number of intersections
between roads is the measure of the information distance between them. This
makes sense intuitively; the more turns there are along a route, the harder
it is to follow.
The model shows each main road as a central hub and each crossroad
as a peripheral node connected to the hub. A grid of streets appears as
a ring of nodes. Connections between streets form a many-pointed star inside
the ring, with each of the star's points meeting the ring at a node.
The researchers found that city street networks resemble well-studied
models of biological and social networks. They also found that it is more
difficult to get from a given street to another given street in a real city
street network than in a random network of streets. "We were… surprised
that streets in cities on average hide from each other compared to a randomized
city," said Rosvall.
The finding was surprising only until the researchers realized that
the scenario was reversed on the neighborhood level. This showed that the
topologies of real cities reflect a tendency for neighborhoods to avoid
being exposed to traffic not destined for the neighborhood. "We simply do
not want to live too close to traffic arteries," said Rosvall. "Neighborhoods
protect us from the disturbance of traffic."
The researchers' model confirmed the widely-held view that the roads
of Manhattan are simpler in terms of information handling than cities with
complicated road-construction histories. "Historical cities have an overabundance
of short streets that make the cities more complex in the sense that they
increase the information distance between streets," said Rosvall.
The researchers' model also showed that ring roads with few exits
shortened the information distance in cities, making them easier to navigate.
Many groups of researchers are studying complicated random networks
like the Internet to glean information about how they grow and how they
handle traffic. There have been fewer studies focusing on communication,
which is manifested in the connections between specific nodes. "The main
focus has been broadcasting of information like in spreading viruses and
advertisements," said Rosvall. "We believe that the specific communication
point of view is more important to get an understanding of network structure."
The researchers' next step is to use the method to study the evolution
of cities, said Rosvall. "We're looking for historical data with snapshots
at different times of the same city."
It would take one to two years for the method to be ready for practical
use, said Rossvall. The growth and modification of cities are very slow
processes, and so any implementation of the method would take at least five
years, he said.
Rosvall's research colleagues were Ala Trusina, P. Minnhagen and
Kim Sneppen. The work appeared in the January 21, 2005 issue of Physical
Review Letters. The research was funded by the Swedish Research Council.
Timeline: 1-2 years
TRN Categories: Networking; Physics; Applied Technology
Story Type: News
Related Elements: Technical paper, "Networks and Cities: An
Information Perspective," Physical Review Letters, January 21, 2005
June 29/July 6, 2005
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