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Risk terrain modeling for road safety: identifying crash-related environmental factors in the province of Cádiz, Spain

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Abstract

Environmental Criminology has developed a robust framework that provides the scientific support and necessary foundation for crime analysis through crime mapping. This theoretical approach focuses on the situational and temporal characteristics of criminal opportunity rather than on the offender’s behavior for crime prevention. In the scope of road safety and traffic crashes, few studies have adopted this approach. This study used risk terrain modeling (RTM), developed by the Rutgers Center on Public Security, to determine the relative importance of varying environmental risk factors on alcohol-related crashes and traffic accidents. The independent variables consisted of a set of potential environmental risk factors, while the dependent variable comprised all DWI crashes and traffic accidents in the province of Cádiz in 2012. According to the results of the current study, restaurant locations are spatially associated with the occurrence of drunk driving crashes, while proximity restaurants and recreational lodging centers correlate with the sites of traffic accidents.

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Notes

  1. We used line-feature shapefiles to represent all of Cádiz’ road networks. These data were obtained from the Instituto de Estadística y Cartografía de Andalucía.

  2. Translated from Spanish: Accidentes, Recogida de Información y Análisis (ARENA)

  3. (9 factors * 2 operationalizations * 4 blocks * 2 “half increments” + 2 factors * 1 operationalization * 4 blocks * 2 “half increments”) = 160 variables.

  4. The same potential risk factors were tested in both RTM models for traffic accidents and DWI crashes.

  5. The “best model” consisted of the one with the lowest Bayesian information criterion (BIC) score.

  6. The cell size for the analysis was 500 m, similar to RTM, and the search radius was set to 4000 m, thus assuming the maximum spatial influence used with RTM.

  7. In the PAI formula, n is the number of crashes in the high-risk places or the hot spots, N is the total number of crashes, a is the area in square kilometers of the high-risk places or the hot spots, and A is the total area for the study.

  8. Based on the differential relative risk score (RRS) obtained with RTM for highways (RRS = 8.19) and secondary road networks (RRS = 5.23).

  9. As indicated by the RRS value of 1.82 obtained from the “Best Model Specifications” output produced by the RTMDx software.

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Funding

The current study was part of the I + D + i project entitled “(MapVial) Environmental Criminology, police intervention and decision making for the prevention of under the influence driving and car accidents. Analysis of a province”, with reference SPIP2015-01691, funded by the Dirección General de Tráfico (DGT).

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Authors and Affiliations

  1. Rutgers Center on Public Security, Rutgers University, 123 Washington St., 5th Floor, Newark, NJ, 07102, USA

    Alejandro Giménez-Santana

  2. Centro Crímina para el Estudio y Prevención de la Delincuencia, Universidad Miguel Hernández de Elche, Alicante, Spain

    José E. Medina-Sarmiento & Fernando Miró-Llinares

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  1. Alejandro Giménez-Santana
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  2. José E. Medina-Sarmiento
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Correspondence to Alejandro Giménez-Santana.

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Giménez-Santana, A., Medina-Sarmiento, J.E. & Miró-Llinares, F. Risk terrain modeling for road safety: identifying crash-related environmental factors in the province of Cádiz, Spain. Eur J Crim Policy Res 24, 451–467 (2018). https://doi.org/10.1007/s10610-018-9398-x

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