A novel spherical decision-making model for measuring the separateness of preferences for drivers’ behavior factors associated with road traffic accidents
Expert Systems with Applications, ISSN: 0957-4174, Vol: 238, Page: 122318
2024
- 22Citations
- 33Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
Enhancing road safety through a more effective understanding of drivers' behavior is a viable approach to curbing traffic collisions. When evaluating driving behavior, the selection of methodologies is diverse, often facing scrutiny. This study aims to detect, compare and quantify critical drivers' behavior factors concerning road safety in Budapest, Hungary. Employing the Analytic Hierarchy Process (AHP) within a spherical fuzzy framework, based on Spherical Fuzzy Sets (SFS), we assess driver preferences. Kendall's test gauges’ agreement levels among hierarchical driver groups. At Level 1, our Spherical Fuzzy AHP (SFAHP) identifies 'Lapses' as crucial, followed by 'Errors' for experienced and young drivers. However, foreign drivers prioritize 'Errors' and 'Violations.' At Level 2, “Aggressive violations” prevails across all groups, contrasting with “Ordinary violations.” At Level 3, “Driving with alcohol use” reigns supreme. Kendall's concordance demonstrates low similarity at Level 1, while strong agreement surfaces for Levels 2 and 3. Our insights can empower transportation authorities to bolster road safety strategies by addressing these pivotal behavior factors.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0957417423028208; http://dx.doi.org/10.1016/j.eswa.2023.122318; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85183879247&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0957417423028208; https://dx.doi.org/10.1016/j.eswa.2023.122318
Elsevier BV
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