The effect of different aggregations of severity levels of crashes with pedestrians in urban areas
Promoting a safer road environment for pedestrians requires an understanding of the risk factors associated with the injuries suffered by these users while involved in crashes. Injury levels as recorded by police reports may be subjected to bias and errors specially in adjacent and not extreme inju...
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| Format: | Article |
| Language: | English |
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Associação Nacional de Pesquisa e Ensino em Transportes (ANPET)
2022-10-01
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| Series: | Transportes |
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| Online Access: | https://www.revistatransportes.org.br/anpet/article/view/2664 |
| _version_ | 1828343861068431360 |
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| author | Mateus Nogueira Silva Flávio José Craveiro Cunto Marcos José Timbó Lima Gomes |
| author_facet | Mateus Nogueira Silva Flávio José Craveiro Cunto Marcos José Timbó Lima Gomes |
| author_sort | Mateus Nogueira Silva |
| collection | DOAJ |
| description |
Promoting a safer road environment for pedestrians requires an understanding of the risk factors associated with the injuries suffered by these users while involved in crashes. Injury levels as recorded by police reports may be subjected to bias and errors specially in adjacent and not extreme injury categories. The aim of this study is to investigate the impact of different severity classification configurations on identifying factors related to crashes involving pedestrians in urban areas. Multinomial logit models were estimated using crash records from the city of Fortaleza between the years 2017 and 2019. The results indicated that the combination of some severity levels can lead to different significant variables and, thus, depending on the specification of the response variable, the influence of important risk factors may end up being ignored in the model. Among the analyzed factors, the age of pedestrians, the day of the week, the time of the crash and the type of road remained significant for the different configurations of severity levels. In addition, the model with three severity categories (mild/moderate, severe, and fatal) presented the best performance in terms of model adjustment. It was observed from this model that factors such as the advanced age of pedestrians, crashes occurring at night, with heavy vehicles, on weekends and located on arterial or expressways are associated with more severe injuries.
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| first_indexed | 2024-04-13T23:49:09Z |
| format | Article |
| id | doaj.art-a1558c424fe541098a2b6093ef470f25 |
| institution | Directory Open Access Journal |
| issn | 2237-1346 |
| language | English |
| last_indexed | 2024-04-13T23:49:09Z |
| publishDate | 2022-10-01 |
| publisher | Associação Nacional de Pesquisa e Ensino em Transportes (ANPET) |
| record_format | Article |
| series | Transportes |
| spelling | doaj.art-a1558c424fe541098a2b6093ef470f252022-12-22T02:24:12ZengAssociação Nacional de Pesquisa e Ensino em Transportes (ANPET)Transportes2237-13462022-10-0130310.14295/transportes.v30i3.2664The effect of different aggregations of severity levels of crashes with pedestrians in urban areas Mateus Nogueira Silva0Flávio José Craveiro Cunto1Marcos José Timbó Lima Gomes2Federal University of Ceará, Ceará – BrazilFederal University of Ceará, Ceará – BrazilFederal University of Cariri, Ceará – Brazil Promoting a safer road environment for pedestrians requires an understanding of the risk factors associated with the injuries suffered by these users while involved in crashes. Injury levels as recorded by police reports may be subjected to bias and errors specially in adjacent and not extreme injury categories. The aim of this study is to investigate the impact of different severity classification configurations on identifying factors related to crashes involving pedestrians in urban areas. Multinomial logit models were estimated using crash records from the city of Fortaleza between the years 2017 and 2019. The results indicated that the combination of some severity levels can lead to different significant variables and, thus, depending on the specification of the response variable, the influence of important risk factors may end up being ignored in the model. Among the analyzed factors, the age of pedestrians, the day of the week, the time of the crash and the type of road remained significant for the different configurations of severity levels. In addition, the model with three severity categories (mild/moderate, severe, and fatal) presented the best performance in terms of model adjustment. It was observed from this model that factors such as the advanced age of pedestrians, crashes occurring at night, with heavy vehicles, on weekends and located on arterial or expressways are associated with more severe injuries. https://www.revistatransportes.org.br/anpet/article/view/2664Injury severityPedestrian crashMultinomial logit model |
| spellingShingle | Mateus Nogueira Silva Flávio José Craveiro Cunto Marcos José Timbó Lima Gomes The effect of different aggregations of severity levels of crashes with pedestrians in urban areas Transportes Injury severity Pedestrian crash Multinomial logit model |
| title | The effect of different aggregations of severity levels of crashes with pedestrians in urban areas |
| title_full | The effect of different aggregations of severity levels of crashes with pedestrians in urban areas |
| title_fullStr | The effect of different aggregations of severity levels of crashes with pedestrians in urban areas |
| title_full_unstemmed | The effect of different aggregations of severity levels of crashes with pedestrians in urban areas |
| title_short | The effect of different aggregations of severity levels of crashes with pedestrians in urban areas |
| title_sort | effect of different aggregations of severity levels of crashes with pedestrians in urban areas |
| topic | Injury severity Pedestrian crash Multinomial logit model |
| url | https://www.revistatransportes.org.br/anpet/article/view/2664 |
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