Spatial autocorrelation analysis of cargo trucks on highway crashes in Chile

Carola A. Blazquez, Barbara Picarte, Juan Felipe Calderón, Fernando Losada

Resultado de la investigación: Article

6 Citas (Scopus)

Resumen

The growing number of cargo trucks on highway crashes in recent years due to the increase in freight movement in Chile motivates this study to identify the formation of persistent crash clusters on highway Ruta 5 (R5). Two spatial statistical methods (Moran's I and Getis-Ord Gi*) were used to determine whether crashes on this highway showed spatial clustering over time from a global and local perspective. Globally, recurrent crash clusters are spatially correlated on vertical curves and straight highway sections on northern R5 with different truck types and with the tractor-trailer units during rainy days on southern R5. The local spatial autocorrelation results suggest that the contributing causes related to the loss of control of the vehicle, the fatigue and imprudence of the driver, and crashes involving tractor units with trailer tend to cause persistent rollover crash clusters throughout R5. Overall, clustering of crash attributes with high values (i.e., hot spots) occurring on highway locations with vertical curves and on cloudy days predominated in the northern R5, and the largest number of recurrent hot spots occurred on sunny days along southern R5. A hot spot spatial co-occurrence analysis was further performed to identify the strong relationships between the studied crash attributes, and the crash and injury types as outcomes. The indication of high risk for the clustering of cargo trucks on highways crashes provides a basis for improving highway safety and reduce the associated social and economic costs.

Idioma originalEnglish
Páginas (desde-hasta)195-210
Número de páginas16
PublicaciónAccident Analysis and Prevention
Volumen120
DOI
EstadoPublished - 1 nov 2018

Huella dactilar

Ruta
Spatial Analysis
Chile
Motor Vehicles
Autocorrelation
Trucks
Light trailers
Tractors (truck)
Cluster Analysis
Statistical methods
Fatigue of materials
Economics
cause
Fatigue
statistical method
Costs
fatigue
indication
Safety
Costs and Cost Analysis

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Safety, Risk, Reliability and Quality
  • Public Health, Environmental and Occupational Health
  • Law

Citar esto

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abstract = "The growing number of cargo trucks on highway crashes in recent years due to the increase in freight movement in Chile motivates this study to identify the formation of persistent crash clusters on highway Ruta 5 (R5). Two spatial statistical methods (Moran's I and Getis-Ord Gi*) were used to determine whether crashes on this highway showed spatial clustering over time from a global and local perspective. Globally, recurrent crash clusters are spatially correlated on vertical curves and straight highway sections on northern R5 with different truck types and with the tractor-trailer units during rainy days on southern R5. The local spatial autocorrelation results suggest that the contributing causes related to the loss of control of the vehicle, the fatigue and imprudence of the driver, and crashes involving tractor units with trailer tend to cause persistent rollover crash clusters throughout R5. Overall, clustering of crash attributes with high values (i.e., hot spots) occurring on highway locations with vertical curves and on cloudy days predominated in the northern R5, and the largest number of recurrent hot spots occurred on sunny days along southern R5. A hot spot spatial co-occurrence analysis was further performed to identify the strong relationships between the studied crash attributes, and the crash and injury types as outcomes. The indication of high risk for the clustering of cargo trucks on highways crashes provides a basis for improving highway safety and reduce the associated social and economic costs.",
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Spatial autocorrelation analysis of cargo trucks on highway crashes in Chile. / Blazquez, Carola A.; Picarte, Barbara; Calderón, Juan Felipe; Losada, Fernando.

En: Accident Analysis and Prevention, Vol. 120, 01.11.2018, p. 195-210.

Resultado de la investigación: Article

TY - JOUR

T1 - Spatial autocorrelation analysis of cargo trucks on highway crashes in Chile

AU - Blazquez, Carola A.

AU - Picarte, Barbara

AU - Calderón, Juan Felipe

AU - Losada, Fernando

PY - 2018/11/1

Y1 - 2018/11/1

N2 - The growing number of cargo trucks on highway crashes in recent years due to the increase in freight movement in Chile motivates this study to identify the formation of persistent crash clusters on highway Ruta 5 (R5). Two spatial statistical methods (Moran's I and Getis-Ord Gi*) were used to determine whether crashes on this highway showed spatial clustering over time from a global and local perspective. Globally, recurrent crash clusters are spatially correlated on vertical curves and straight highway sections on northern R5 with different truck types and with the tractor-trailer units during rainy days on southern R5. The local spatial autocorrelation results suggest that the contributing causes related to the loss of control of the vehicle, the fatigue and imprudence of the driver, and crashes involving tractor units with trailer tend to cause persistent rollover crash clusters throughout R5. Overall, clustering of crash attributes with high values (i.e., hot spots) occurring on highway locations with vertical curves and on cloudy days predominated in the northern R5, and the largest number of recurrent hot spots occurred on sunny days along southern R5. A hot spot spatial co-occurrence analysis was further performed to identify the strong relationships between the studied crash attributes, and the crash and injury types as outcomes. The indication of high risk for the clustering of cargo trucks on highways crashes provides a basis for improving highway safety and reduce the associated social and economic costs.

AB - The growing number of cargo trucks on highway crashes in recent years due to the increase in freight movement in Chile motivates this study to identify the formation of persistent crash clusters on highway Ruta 5 (R5). Two spatial statistical methods (Moran's I and Getis-Ord Gi*) were used to determine whether crashes on this highway showed spatial clustering over time from a global and local perspective. Globally, recurrent crash clusters are spatially correlated on vertical curves and straight highway sections on northern R5 with different truck types and with the tractor-trailer units during rainy days on southern R5. The local spatial autocorrelation results suggest that the contributing causes related to the loss of control of the vehicle, the fatigue and imprudence of the driver, and crashes involving tractor units with trailer tend to cause persistent rollover crash clusters throughout R5. Overall, clustering of crash attributes with high values (i.e., hot spots) occurring on highway locations with vertical curves and on cloudy days predominated in the northern R5, and the largest number of recurrent hot spots occurred on sunny days along southern R5. A hot spot spatial co-occurrence analysis was further performed to identify the strong relationships between the studied crash attributes, and the crash and injury types as outcomes. The indication of high risk for the clustering of cargo trucks on highways crashes provides a basis for improving highway safety and reduce the associated social and economic costs.

KW - Freight trucks

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