Estimation of walking density based on characteristics of the built environment at the level of traffic zones

Authors

DOI:

https://doi.org/10.58922/transportes.v31i3.2874

Keywords:

Built Environment, Walking trips, Spatial regression models, Pedestrian Exposure

Abstract

The influence of the built environment on pedestrian exposure is an essential element for analyzing road safety and urban planning. Due to the scarcity of pedestrian exposure data, road safety modeling can use proxy variables from the built environment to represent quantitative pedestrian exposure and the urban planning does not always consider the pedestrian or estimate in conjunction with other modes. In search of prioritizing pedestrians due to their greater vulnerability in relation to other modes, the aim of the article is to estimate the density of pedestrian trips in traffic zones from the characteristics of the built environment. The method proposes the comparison between global regression, geographically weighted regression (GWR) and the recent multiscale geographically weighted regression (MGWR) approach. The analysis of the residuals proved that the specification of the MGWR model is more powerful in terms of fitting the model and filtering the spatial autocorrelation. Population density, length of roads per zone area and distance to public transport are among the significant predictor variables for estimating the number of walking trips per area of the traffic zone.

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Published

2023-12-11

How to Cite

Xavier, V. J., Gomes, M. J. T. L., & Cunto, F. J. C. (2023). Estimation of walking density based on characteristics of the built environment at the level of traffic zones. Transportes, 31(3), e2874. https://doi.org/10.58922/transportes.v31i3.2874

Issue

Vol. 31 No. 3 (2023)

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Articles

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Copyright (c) 2023 Vanessa Jamille Xavier, Marcos José Timbó Lima Gomes, Flávio Jose Craveiro Cunto

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