Browsing by Subject "safety, walking, safety-in-numbers, crashes, traffic counts, network structure, accessibility"

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    Accessibility and Centrality Based Estimation of Urban Pedestrian Activity
    (2015) Murphy, Brendan; Levinson, David, M; Owen, Andrew
    Non-motorized transportation, particularly including walking and bicycling, are increasingly becoming important modes in modern cities, for reasons including individual and societal wellness, avoiding negative environmental impacts of other modes, and resource availability. Institutions governing development and management of urban areas are increasingly keen to include walking and bicycling in urban planning and engineering; however, proper placement of improvements and treatments depends on the availability of good usage data. This study attempts to predict pedestrian activity at 1123 intersections in the Midwestern, US city of Minneapolis, Minnesota, using scalable and transferable predictive variables such as economic accessibility by sector, betweenness network centrality, and automobile traffic levels. Accessibility to jobs by walking and transit, automobile traffic, and accessibility to certain economic job categories (Education, Finance) were found to be significant predictors of increased pedestrian traffic, while accessibility to other economic job categories (Management, Utilities) were found to be significant predictors of decreased pedestrian traffic. Betweenness centrality was not found to be a significant predictor of pedestrian traffic, however the specific calculation methodology can be further tailored to reflect real-world pedestrian use-cases in urban areas. Accessibility-based analysis may provide city planners and engineers with an additional tool to predict pedestrian and bicycle traffic where counts may be difficult to obtain, or otherwise unavailable.
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    Evaluating the "Safety In Numbers" Effect With Estimated Pedestrian Activity
    (2015) Murphy, Brendan; Levinson, David M; Owen, Andrew
    Pedestrian and bicyclist collision risk assessment offers a powerful and informative tool in urban planning applications, and can greatly serve to inform proper placement of improvements and treatment projects. However, sufficiently detailed data regarding pedestrian and bicycle activity are not readily available for many urban areas, and thus the activity levels and collision risk levels must be estimated. This study builds upon other current work by the authors regarding pedestrian and bicycle activity estimation based on centrality and accessibility metrics, and extends the analysis techniques to estimation of pedestrian collision risk. The Safety In Numbers phenomenon, which refers to the observable effect that pedestrians become safer when there are more pedestrians present in a given area, i.e. that the individual per-pedestrian risk of a collision decreases with additional pedestrians, is a readily observed phenomenon that has been studied previously. The effect is investigated and observed in acquired traffic data, as well as estimated data, in Minneapolis, Minnesota.