Sidewalk traffic data can be a strong tool for urban planners: is a city working as designed?

A recent study analyzed sidewalk traffic data and drilled down into what makes a city street a popular walkable destination. Researchers ID’d several factors, like the total building floor space within the areas, and its total ground area at the street level. This consists of the “built density,” including the main street location.

Aside from the built density and street type, attraction factors include local shops or transit stops that are found in the urban area. These are the main factors to consider in identifying what brings foot traffic.

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Researchers from KAUST and Chalmers University have used automated data collection and analytics to understand the factors that influence sidewalk traffic in a given length of the street.


Using an analysis of variance (ANOVA) model, the researchers then parsed out how the pedestrian flow for a given street varied over each day – and what factors influenced that variation. “In a previous study, we found strong links between the total number of people walking on a given street in one day and certain characteristics of the urban environment,” researcher David Bolin said.

With this larger dataset – a boon relative to other, similar studies that had struggled with small, inconsistent datasets – the team substantiated their earlier results and identified another important variable. In addition to built density and street type, “attraction variables” (e.g. local markets, transit stops) emerged as a controlling factor for foot traffic.

The researchers compared their results with four common machine learning methods, finding favorable results but noting that “there is room for improvement in capturing the variability in the data, especially between cities.”