[PDF][PDF] Evaluation of road sections in order assessment of traffic risk: Integrated FUCOM-MARCOS model

Ž Stević, I Tanackov, M Subotić - 1st International Conference on …, 2020 - researchgate.net
Ž Stević, I Tanackov, M Subotić
1st International Conference on Challenges and New Solutions in …, 2020researchgate.net
In this research an integrated multi-criteria decision-making (MCDM) model for evaluation of
road sections in order assessment of traffic risk has been applied. It is considering part of
road network I category with length 6.6 km with total of nine short sections. The influence of
geometric characteristics on traffic risk is reflected through identifying conflict points on
roads, traffic accidents, and any other unforeseen situation that is inherently dangerous for
traffic participants. In order to identify the road sections with the highest risk, it is necessary to …
Abstract
In this research an integrated multi-criteria decision-making (MCDM) model for evaluation of road sections in order assessment of traffic risk has been applied. It is considering part of road network I category with length 6.6 km with total of nine short sections. The influence of geometric characteristics on traffic risk is reflected through identifying conflict points on roads, traffic accidents, and any other unforeseen situation that is inherently dangerous for traffic participants. In order to identify the road sections with the highest risk, it is necessary to consider a number of criteria that affect risk. For determining criteria weights on the basis which evaluation of road sections is performed Full Consistency Method (FUCOM) is applied. After data collection and forming MCDM model Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS) is used for selection most dangerous section. Results showed that exists one dominant section with higher risk for all traffic participants. In order to make validation of obtained results extend sensitivity analysis is performed: changing criteria weights, comparison to other MCDM methods and reverse ranking matrix. Also, Spearman's correlation coefficient was calculated as a statistical indicator of rank correlation in a sensitivity analysis. In addition, the standard deviation of the obtained results was determined. Through sensitivity analysis obtained results are validated.
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