Detalhes bibliográficos
| Ano de defesa: |
2022 |
| Autor(a) principal: |
Santos, Roberta Pimenta Cunha dos
 |
| Orientador(a): |
Zebende, Gilney Figueira
|
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Estadual de Feira de Santana
|
| Programa de Pós-Graduação: |
Mestrado em Modelagem em Ciência da Terra e do Ambiente
|
| Departamento: |
DEPARTAMENTO DE CIÊNCIAS EXATAS
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Palavras-chave em Inglês: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://tede2.uefs.br:8080/handle/tede/1421
|
Resumo: |
Traffic accidents represent the eighth leading cause of death for all age groups in the world. In Brazil, the flows of goods and people occur mainly through the road system. At the same time, the country occupies fifth place in the ranking of countries with the highest rates of road traffic deaths, behind only India, China, USA, and Russia. In this sense, traffic accidents represent a health problem public and also, why not say, an environmental problem. As a result of the increased number of fatal accident victims over the years, it is necessary to scientific basis, to direct the actions to face this problem. To contribute to the formulation of public policies for the reduction of traffic accidents on federal highways, this work has the general objective of analyzing the accident variables refer to the total number of people, injured, injured light, seriously injured, unharmed, ignored and vehicles involved in accidents recorded on the federal highways of Bahia. We also intend to represent the structure, in addition to characterize the behavior of these variables as a function of time, through the application of the cross-correlation coefficient (ρDCCA). This coefficient is based on the methods of Statistical mechanics: DFA (Detrended Fluctuation Analysis), used to identify long-range autocorrelation and DCCA (Detrended Cross-Correlation Analysis), estimates the exponent that characterizes the cross correlation between two non-stationary time series of the same size N. Several fields of knowledge have already been modeled through of the ρDCCA, such as the study of taxi accidents, climatic phenomena, financial market, crime indicators, industrial production behavior, dynamics of dengue cases, among others. To achieve this objective, we analyzed the data series referring to accidents reported by the Federal Highway Police (PRF) of Bahia, between 2007 and 2021. In general, we analyzed the existence of long-range cross-correlation between the dead variable with the others variables since reducing the number of fatal victims are one of the main objectives of PRF to mitigate traffic violence. The ρDCCA results indicated a correlation in all the crossings carried out, which shows that the fluctuations in the amount of Mortos is affected by fluctuations in the quantities of the other variables, according to a positive correlation (highs followed by highs or lows followed by lows). Among other characteristics, accidents were mainly caused by improper posture of the driver, most of which took place on the three main highways in the state, BR 101, BR 324, and BR 116, and most of the people involved were male. |
