Análise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.

Detalhes bibliográficos
Autor(a) principal: Mon-Ma, Marly Mitiko
Data de Publicação: 2005
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional da UFSCAR
Texto Completo: https://repositorio.ufscar.br/handle/ufscar/4403
Resumo: The technological development has generated great amount of potential data bases in order to supply information for several aspects related to road safety. However, the transformation of these great amount of data in useful information for the technicians, public managers and the population in general, requests the modeling and the treatment of these data using some analysis tools that allow a visualization of the results in form easily understandable. This work presents a new methodology of traffic accidents analysis based in the artificial neural network (ANN). ANN can be very useful for organizations, public or particular, mainly to those that propose to understand the phenomena of the traffic in order to looking for solutions integrated to several areas such as education, engineering and fiscalization. This research had as general objective to identify the patterns of traffic accidents that happened at urban intersections. The data of accidents that happened in the period from 2000 to 2003, in the city of São Carlos were used for the case study, in order to subsidize the elaboration and the evaluation of public policies of traffic accidents reduction and specially the reduction of accident severity. The study explores the assumption that different accident types are related to different patterns. The patterns obtained by ANN showed that there are significant differences in the factors that can affect the different types of accidents. The knowledge of the patterns of each accident type is essential to develop actions corrective or preventive road safety's improvement in order to avoid undesirable effects when these actions are implemented. However, the comparison between the patterns of the different types of accidents was difficult due to the heterogeneity of the situations and the different elements that compose the road environment that can affect the occurrence of the accident.
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spelling Mon-Ma, Marly MitikoRaia Junior, Archimedes Azevedohttp://lattes.cnpq.br/6413793013018019600a4391-d6d2-4f0b-a9df-afc12ca267672016-06-02T20:01:03Z2007-08-202016-06-02T20:01:03Z2005-10-06MON-MA, Marly Mitiko. Analysis of the importance of the intervening variable in the traffic accidents in urban intersections using Artificial Neural Networks.. 2005. 157 f. Dissertação (Mestrado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2005.https://repositorio.ufscar.br/handle/ufscar/4403The technological development has generated great amount of potential data bases in order to supply information for several aspects related to road safety. However, the transformation of these great amount of data in useful information for the technicians, public managers and the population in general, requests the modeling and the treatment of these data using some analysis tools that allow a visualization of the results in form easily understandable. This work presents a new methodology of traffic accidents analysis based in the artificial neural network (ANN). ANN can be very useful for organizations, public or particular, mainly to those that propose to understand the phenomena of the traffic in order to looking for solutions integrated to several areas such as education, engineering and fiscalization. This research had as general objective to identify the patterns of traffic accidents that happened at urban intersections. The data of accidents that happened in the period from 2000 to 2003, in the city of São Carlos were used for the case study, in order to subsidize the elaboration and the evaluation of public policies of traffic accidents reduction and specially the reduction of accident severity. The study explores the assumption that different accident types are related to different patterns. The patterns obtained by ANN showed that there are significant differences in the factors that can affect the different types of accidents. The knowledge of the patterns of each accident type is essential to develop actions corrective or preventive road safety's improvement in order to avoid undesirable effects when these actions are implemented. However, the comparison between the patterns of the different types of accidents was difficult due to the heterogeneity of the situations and the different elements that compose the road environment that can affect the occurrence of the accident.O desenvolvimento tecnológico tem gerado grandes bases de dados com potencial para fornecer informações sobre diversos aspectos relacionados com a segurança viária. No entanto, a conversão de um grande volume de dados em informações úteis para os técnicos, gestores públicos e a população em geral, requer a modelagem e o tratamento destes dados utilizando ferramentas de análise que permitam uma visualização dos resultados de forma facilmente compreensível. Este trabalho apresenta uma nova metodologia para análise de acidentes de trânsito fundamentada na rede neural artificial (RNA). A RNA pode ser de grande utilidade para organizações públicas e privadas, principalmente para aquelas que se propõem compreender os fenômenos do trânsito a fim de buscar soluções integradas em diversas áreas tais como educação, engenharia e fiscalização. A pesquisa teve como objetivo geral identificar os padrões de acidentes de trânsito que ocorreram nas interseções urbanas. Os dados de acidentes que ocorreram no período de 2000 a 2003, na cidade de São Carlos foram utilizados para o estudo de caso, visando fornecer subsídios para a elaboração e a avaliação de políticas públicas voltadas para redução do número de acidentes de trânsito e essencialmente na redução global da severidade. O estudo explora a suposição de que diferentes tipos de acidente estão relacionados com padrões distintos. Os padrões obtidos através da RNA mostram que há divergências significativas nos fatores que podem influenciar os diferentes tipos de acidentes. Conhecer padrões de cada tipo de acidente se faz necessária para que as medidas corretivas ou preventivas voltadas para a melhoria da segurança viária não resultem em efeitos indesejados quando são implementadas, no entanto comparações entre padrões de diferentes tipos de acidentes mostraram-se particularmente difíceis devido à heterogeneidade das situações e dos diferentes elementos que compõem o ambiente viário e que podem influenciar na ocorrência do acidente.application/pdfporUniversidade Federal de São CarlosPrograma de Pós-Graduação em Engenharia Urbana - PPGEUUFSCarBRAcidentes de trânsitoSegurança viáriaPadrões de acidenteRedes neurais (Computação)Trânsito urbanoTrafficRoad safetyTraffic accidentsPatternsNeural networksENGENHARIASAnálise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.Analysis of the importance of the intervening variable in the traffic accidents in urban intersections using Artificial Neural Networks.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis-1-1181dd3cc-84bf-4774-8aab-1fd0c8893861info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINALDissMMM.pdfapplication/pdf1370681https://repositorio.ufscar.br/bitstream/ufscar/4403/1/DissMMM.pdf4891da17b25caf7951985f7209d9c825MD51THUMBNAILDissMMM.pdf.jpgDissMMM.pdf.jpgIM Thumbnailimage/jpeg7159https://repositorio.ufscar.br/bitstream/ufscar/4403/2/DissMMM.pdf.jpge4f42c01ce550788767b094d4b1a4d9aMD52ufscar/44032023-09-18 18:31:01.848oai:repositorio.ufscar.br:ufscar/4403Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:31:01Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false
dc.title.por.fl_str_mv Análise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.
dc.title.alternative.eng.fl_str_mv Analysis of the importance of the intervening variable in the traffic accidents in urban intersections using Artificial Neural Networks.
title Análise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.
spellingShingle Análise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.
Mon-Ma, Marly Mitiko
Acidentes de trânsito
Segurança viária
Padrões de acidente
Redes neurais (Computação)
Trânsito urbano
Traffic
Road safety
Traffic accidents
Patterns
Neural networks
ENGENHARIAS
title_short Análise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.
title_full Análise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.
title_fullStr Análise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.
title_full_unstemmed Análise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.
title_sort Análise da importância das variáveis intervenientes nos acidentes de trânsito em interseções urbanas utilizando redes neurais artificiais.
author Mon-Ma, Marly Mitiko
author_facet Mon-Ma, Marly Mitiko
author_role author
dc.contributor.author.fl_str_mv Mon-Ma, Marly Mitiko
dc.contributor.advisor1.fl_str_mv Raia Junior, Archimedes Azevedo
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/6413793013018019
dc.contributor.authorID.fl_str_mv 600a4391-d6d2-4f0b-a9df-afc12ca26767
contributor_str_mv Raia Junior, Archimedes Azevedo
dc.subject.por.fl_str_mv Acidentes de trânsito
Segurança viária
Padrões de acidente
Redes neurais (Computação)
Trânsito urbano
topic Acidentes de trânsito
Segurança viária
Padrões de acidente
Redes neurais (Computação)
Trânsito urbano
Traffic
Road safety
Traffic accidents
Patterns
Neural networks
ENGENHARIAS
dc.subject.eng.fl_str_mv Traffic
Road safety
Traffic accidents
Patterns
Neural networks
dc.subject.cnpq.fl_str_mv ENGENHARIAS
description The technological development has generated great amount of potential data bases in order to supply information for several aspects related to road safety. However, the transformation of these great amount of data in useful information for the technicians, public managers and the population in general, requests the modeling and the treatment of these data using some analysis tools that allow a visualization of the results in form easily understandable. This work presents a new methodology of traffic accidents analysis based in the artificial neural network (ANN). ANN can be very useful for organizations, public or particular, mainly to those that propose to understand the phenomena of the traffic in order to looking for solutions integrated to several areas such as education, engineering and fiscalization. This research had as general objective to identify the patterns of traffic accidents that happened at urban intersections. The data of accidents that happened in the period from 2000 to 2003, in the city of São Carlos were used for the case study, in order to subsidize the elaboration and the evaluation of public policies of traffic accidents reduction and specially the reduction of accident severity. The study explores the assumption that different accident types are related to different patterns. The patterns obtained by ANN showed that there are significant differences in the factors that can affect the different types of accidents. The knowledge of the patterns of each accident type is essential to develop actions corrective or preventive road safety's improvement in order to avoid undesirable effects when these actions are implemented. However, the comparison between the patterns of the different types of accidents was difficult due to the heterogeneity of the situations and the different elements that compose the road environment that can affect the occurrence of the accident.
publishDate 2005
dc.date.issued.fl_str_mv 2005-10-06
dc.date.available.fl_str_mv 2007-08-20
2016-06-02T20:01:03Z
dc.date.accessioned.fl_str_mv 2016-06-02T20:01:03Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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dc.identifier.citation.fl_str_mv MON-MA, Marly Mitiko. Analysis of the importance of the intervening variable in the traffic accidents in urban intersections using Artificial Neural Networks.. 2005. 157 f. Dissertação (Mestrado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2005.
dc.identifier.uri.fl_str_mv https://repositorio.ufscar.br/handle/ufscar/4403
identifier_str_mv MON-MA, Marly Mitiko. Analysis of the importance of the intervening variable in the traffic accidents in urban intersections using Artificial Neural Networks.. 2005. 157 f. Dissertação (Mestrado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2005.
url https://repositorio.ufscar.br/handle/ufscar/4403
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