Investigating the link between the built environment and the incidence of pedestrian crashes in Cape Town, South Africa

[摘要] ENGLISH ABSTRACT: Pedestrians are the most vulnerable road users in the road environment, particularly in the developing world. To gain a better understanding of pedestrian crash causation, the built environment has been given much attention in the international traffic safety research. However, research of this nature is still scarce in the developing world, including South Africa. This study investigates the link between the built environment and the incidence of pedestrian crashes. The study used pedestrian crash data collected in Cape Town over a 3-year period between 2012 and 2014. The research method involved screening, geocoding and supplementing poor quality secondary data on pedestrian crashes. Moreover, the study applies a variety of analytical methods including univariate, bivariate, geospatial and multivariate analyses. Four GIS-based spatial analysis methods were used to identify clusters of pedestrian crashes within the study area. These methods include the planar kernel density estimation (KDE), the Anselin local Moran's I, the Getis-Ord Gi* and the Optimized Hot Spot Analysis (OHA). Two modelling techniques, the Generalised Linear Modelling (GLM) and Geographically Weighted Regression (GWR) modelling were used to relate the built environment and population variables to total; intersection; and killed and seriously injured (KSI) pedestrian crashes. For this analysis, the data was aggregated and analysed at the census suburb level. Among other results, it was found that population; land use mix; traffic signals; roundabouts/mini-circles; industrial use; four- and multi-legged intersections; and high mobility roads are associated with greater numbers of pedestrian crashes. The study also revealed that pedestrian crashes are positively related to socio-economic deprivation. In addition, spatial variations of the associations in the models were investigated and discussed. Hotspots of pedestrian crashes were identified mostly in the South Eastern regions of Cape Town which are also areas where economically-disadvantaged residents are concentrated. The presented models can be used to predict future pedestrian crashes using information that is easily available at the city level. The models are also crucial for the planning of safe walking environments which are particularly needed in South Africa and other developing countries.

[发布机构] Stellenbosch University