Abstract
Identification of key indicators that cause safety challenges and vulnerable roads is crucial for improving traffic safety. This paper, therefore, entails to the development of a novel multiphase multicriteria decision-making (MCDM) model to evaluate the vulnerability of urban roads for traffic safety. This was conducted by using data from 17 important roads of a South African city and combining several methods such as CRiteria Importance through Intercriteria Correlation (CRITIC), data envelopment analysis (DEA), and measurement of alternatives and ranking according to compromise solution (MARCOS). Taking the elements of the DEA method, two new approaches for calculating the weights of criteria, the DEA-1 and DEA-2 models, were formed and integrated with the CRITIC method to obtain the final values of criteria weights. The MARCOS method was applied to evaluate 17 alternatives, for each direction separately. The aim of developing such a model is to use the advantages of obtaining objectivity of criteria weights through linear programming and correlation of values of the collected data. Also, the MARCOS method, as one of the newer and applicable methods, provides additional significance. Extensive sensitivity analyses were conducted to validate the model. The findings suggest that there are a certain number of roads that have a high level of safety for both directions, as well as a group of risky roads, which need traffic improvement measures. Thus, the results indicate that the model is sensitive to various approaches and can prioritize vulnerable roads comprehensively based on which safety measures can be taken.
Highlights
Identification of key indicators that cause safety challenges and vulnerable roads is crucial for improving traffic safety. is paper, entails to the development of a novel multiphase multicriteria decision-making (MCDM) model to evaluate the vulnerability of urban roads for traffic safety. is was conducted by using data from 17 important roads of a South African city and combining several methods such as CRiteria Importance through Intercriteria Correlation (CRITIC), data envelopment analysis (DEA), and measurement of alternatives and ranking according to compromise solution (MARCOS)
Extensive sensitivity analyses were conducted to validate the model. e findings suggest that there are a certain number of roads that have a high level of safety for both directions, as well as a group of risky roads, which need traffic improvement measures. us, the results indicate that the model is sensitive to various approaches and can prioritize vulnerable roads comprehensively based on which safety measures can be taken
As already mentioned in the previous section of the paper, data have been collected for both directions, and the evaluation is performed so it is evident that there are differences in terms of safety of individual streets. When it comes to the S-direction, the group of the five safest streets includes the following, respectively: Eric Rosendorf Street, Volkspele Drive, Stals Road, Gardenia Avenue, and Pellissier Drive. e group of least safe streets for the S-direction includes Wynand Mouton Drive, Paul Kruger Drive North, Paul Kruger Drive (E), and Benade Drive (N)
Summary
Identification of key indicators that cause safety challenges and vulnerable roads is crucial for improving traffic safety. is paper, entails to the development of a novel multiphase multicriteria decision-making (MCDM) model to evaluate the vulnerability of urban roads for traffic safety. is was conducted by using data from 17 important roads of a South African city and combining several methods such as CRiteria Importance through Intercriteria Correlation (CRITIC), data envelopment analysis (DEA), and measurement of alternatives and ranking according to compromise solution (MARCOS). Us, the results indicate that the model is sensitive to various approaches and can prioritize vulnerable roads comprehensively based on which safety measures can be taken. E occurrence of higher vehicular traffic accidents has been experienced on the principal thoroughfares of the cities and on the arterial roads and intersections located in the suburban areas. In the context of South African cities, most of the studies are aimed at either establishing the linkage between different road, traffic, environmental or human factors with the occurrence of the accidents on the roads or developing remedial measures to improve road safety. Since remedial measures to improve road safety demand prioritization or ranking of vulnerable roads in addition to exploring the causes of the occurrence of accidents, there is a need for robust, advanced, and flexible methods that could accommodate various parameters effectively and offer reliable predictions
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