How a city's design creates congestion

Date:
September 22, 2021
Source:
University of Texas at San Antonio
Summary:
City planners predict that as more people move into urban areas,
traffic jams will get worse. That's why sustainability experts
propose a new way to analyze traffic congestion. Using more precise
measures to describe the shape of cities and considering other
socioeconomic factors, the model, which was applied to nearly 100
American cities, could lead to a better understanding of the link
between congestion and land use.



FULL STORY ==========================================================================
City planners predict that as more people move into urban areas, traffic
jams will get worse. That's why sustainability expert Neil Debbage,
an assistant professor in the UTSA College of Liberal and Fine Arts'
Department of Political Science and Geography, proposes a new way to
analyze traffic congestion.


========================================================================== Using more precise measures to describe the shape of cities and
considering other socioeconomic factors, the model, which was applied
to nearly 100 American cities, could lead to a better understanding of
the link between congestion and land use.

"Anecdotally, we often hear that more sprawling cities like San
Antonio suffer from worse traffic congestion, but we wanted to test
this relationship by analyzing a large number of cities with diverse
urban forms." Previously, indirect metrics, such as population density,
job location and the total number of homes within a defined area, were
used to estimate traffic congestion. Working alongside with Mingshu Wang, associate professor at the University of Glasgow, a new approach was
designed based on the configuration of land use within cities.

The model also used new variables, including the level of intensity of
urban land use and congestion type, and control variables, such as median
age, total population and the presence of auto commuters to determine
their impact on congestion.

The researchers used congestion data from the Urban Mobility Scorecard
(UMS) database. This source combines real-time speed data, volume and
roadway information from the Federal Highway Administration. Specifically, congestion was defined according to annual excess fuel consumed during
rush hours and free-flowing traffic, annual hours of delay during rush
hour and off-peak times, and a time travel index based on the ratio
between travel time during rush hour divided by the time of the same
trip under free-flowing conditions.

This more precise definition of congestion helped Wang and Debbage answer
three specific questions: What city type, either those with one dominant
urban center or multiple centers, creates more congestion? Which types of
urban land use, such as high-intensity or low-intensity, are associated
with congestion? What are the relationships between the shape of a city
and congestion and how do those links vary depending on the specific
type of congestion analyzed? The UTSA-Glasgow model indicated that
cities with more urban land use were associated with higher congestion
levels. The researchers' findings support the long-held belief that
traffic congestion is tied to urbanization, but also highlighted that high-intensity urban land use played a more notable role.

The researchers also found that the shape of cities impacted
congestion. Cities that had one dominant urban core generally were
associated with lower levels of congestion while more polycentric cities,
those with multiple urban centers, suffered from more traffic. The
study found that the shape of cities had more of an impact on general congestion than traffic just during rush hour periods.

"By analyzing different land use intensities, we were able to identify
more precisely what aspects of city shape influence congestion,
which can hopefully inform more tailored land use policy responses." ========================================================================== Story Source: Materials provided by
University_of_Texas_at_San_Antonio. Note: Content may be edited for
style and length.


========================================================================== Journal Reference:
1. Mingshu Wang, Neil Debbage. Urban morphology and traffic congestion:
Longitudinal evidence from US cities. Computers,
Environment and Urban Systems, 2021; 89: 101676 DOI:
10.1016/j.compenvurbsys.2021.101676 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/09/210922161930.htm

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