Utilização de sistema de informações geográficas na tomada de decisões do sistema viário com base em dados de acidentes de trânsito no município de Pato Branco
Due to the high social and economic losses that traffic accidents require, traffic accidents should be a priority in the tactical and strategic planning of urban mobility. For preventive actions, interventions and prediction of future traffic accidents to be possible, it is necessary to know the pla...
| Autor principal: | Legramanti, Gabriela |
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| Formato: | Dissertação |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2021
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| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/25617 |
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| Resumo: |
Due to the high social and economic losses that traffic accidents require, traffic accidents should be a priority in the tactical and strategic planning of urban mobility. For preventive actions, interventions and prediction of future traffic accidents to be possible, it is necessary to know the places where accidents occur with greater intensity, but many traffic authorities do not have a welldefined method for this procedure. Due to the simultaneous storage and management capacity of spatial data that the Geographic Information System has, GIS represents an excellent tool for controlling traffic accidents. With this in mind, this study aims to develop a method, based on GIS, for management of traffic accidents. The technique used to identify the geographic area with the greatest tendency to the occurrence of traffic accidents is the Kernel Density Estimate (KDE). The traffic accident aggravation weights used were the standard severity unit. Weight 4 for data with the presence of injury, weight 6 for accidents involving pedestrians and weight 13 for the occurrence of deaths. The radius used in KDE was 75 meters, as it represents better stretches and critical intersections of the study area. When comparing the KDE classifications in 2014 and 2019, by neighborhood, we can see that the neighborhoods with the highest accident density were the neighborhoods Centro, Baixada, Trevo da Guarani, Brasília and Amadori. On a smaller scale, it was also possible to identify which stretches and intersections are most critical in each location in the city. The method and results of this work provide subsidies to identify, in a clear way, places with tendencies to traffic accidents. We conclude that the use of standardized process and more detailed data on traffic accidents, associated with GIS models, which include convenient registration, mapping and convenient analysis, which indicate points that require interventions in the road system, are essential for the management of road safety. |
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