A Hybrid Best-Worst Method (BWM)—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Approach for Prioritizing Road Safety Improvements
The increase in road accidents underscores the urgent need for effective methodologies to evaluate and prioritize road safety improvements. Traditional decision-making processes in road safety management often confront challenges due to the lack of a comprehensive approach, particularly in handling...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10441826/ |
| _version_ | 1797289878111649792 |
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| author | Priyank Trivedi Jiten Shah Robert Cep Laith Abualigah Kanak Kalita |
| author_facet | Priyank Trivedi Jiten Shah Robert Cep Laith Abualigah Kanak Kalita |
| author_sort | Priyank Trivedi |
| collection | DOAJ |
| description | The increase in road accidents underscores the urgent need for effective methodologies to evaluate and prioritize road safety improvements. Traditional decision-making processes in road safety management often confront challenges due to the lack of a comprehensive approach, particularly in handling multiple evaluation criteria. This study introduces a novel Hybrid Multi-Criteria Decision-Making approach that amalgamates the Best-Worst Method (BWM), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and the Simple Additive Weighting (SAW) method. This approach is designed to prioritize road safety improvements effectively by analyzing various criteria and alternatives in a structured manner. Focusing on a 500-meter road section, the study identifies eight distinct road improvement criteria and divides the road section into five sub-sections for detailed analysis. The BWM is utilized to determine the criteria weights, which are subsequently integrated into the TOPSIS and SAW methodologies for prioritizing improvements in each road subsection. This hybrid approach provides a comprehensive framework for decision makers, including road safety auditors and transportation professionals, facilitating a nuanced and systematic evaluation of safety improvements. The methodology’s efficacy is validated through field expert consultations and comparative analysis with standalone SAW results. The validation underscores the potential of the proposed approach as a robust tool for road safety stakeholders, enabling them to make informed decisions based on a detailed, Chainage-wise analysis of road sections. The Python code for TOPSIS is available at <uri>https://github.com/kanak02/TOPSIS</uri>. |
| first_indexed | 2024-03-07T19:12:23Z |
| format | Article |
| id | doaj.art-84d7404bd063474b86a47b27a4520a25 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-07T19:12:23Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-84d7404bd063474b86a47b27a4520a252024-03-01T00:00:21ZengIEEEIEEE Access2169-35362024-01-0112300543006510.1109/ACCESS.2024.336839510441826A Hybrid Best-Worst Method (BWM)—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Approach for Prioritizing Road Safety ImprovementsPriyank Trivedi0https://orcid.org/0000-0003-2391-6866Jiten Shah1https://orcid.org/0000-0002-7100-8582Robert Cep2https://orcid.org/0000-0001-9610-4215Laith Abualigah3https://orcid.org/0000-0002-2203-4549Kanak Kalita4https://orcid.org/0000-0001-9289-9495Department of Civil Engineering, Institute of Infrastructure Technology Research and Management (IITRAM), Ahmedabad, IndiaDepartment of Civil Engineering, Institute of Infrastructure Technology Research and Management (IITRAM), Ahmedabad, IndiaDepartment of Machining, Assembly and Engineering Metrology, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, Ostrava, Czech RepublicComputer Science Department, Al Al-Bayt University, Mafraq, JordanDepartment of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala Research and Development Institute of Science and Technology, Avadi, IndiaThe increase in road accidents underscores the urgent need for effective methodologies to evaluate and prioritize road safety improvements. Traditional decision-making processes in road safety management often confront challenges due to the lack of a comprehensive approach, particularly in handling multiple evaluation criteria. This study introduces a novel Hybrid Multi-Criteria Decision-Making approach that amalgamates the Best-Worst Method (BWM), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and the Simple Additive Weighting (SAW) method. This approach is designed to prioritize road safety improvements effectively by analyzing various criteria and alternatives in a structured manner. Focusing on a 500-meter road section, the study identifies eight distinct road improvement criteria and divides the road section into five sub-sections for detailed analysis. The BWM is utilized to determine the criteria weights, which are subsequently integrated into the TOPSIS and SAW methodologies for prioritizing improvements in each road subsection. This hybrid approach provides a comprehensive framework for decision makers, including road safety auditors and transportation professionals, facilitating a nuanced and systematic evaluation of safety improvements. The methodology’s efficacy is validated through field expert consultations and comparative analysis with standalone SAW results. The validation underscores the potential of the proposed approach as a robust tool for road safety stakeholders, enabling them to make informed decisions based on a detailed, Chainage-wise analysis of road sections. The Python code for TOPSIS is available at <uri>https://github.com/kanak02/TOPSIS</uri>.https://ieeexplore.ieee.org/document/10441826/Best-worst method (BWM)multi-criteria decision making (MCDM)road safety improvementsimple additive weighting (SAW)technique for order preference by similarity to ideal solution (TOPSIS) |
| spellingShingle | Priyank Trivedi Jiten Shah Robert Cep Laith Abualigah Kanak Kalita A Hybrid Best-Worst Method (BWM)—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Approach for Prioritizing Road Safety Improvements IEEE Access Best-worst method (BWM) multi-criteria decision making (MCDM) road safety improvement simple additive weighting (SAW) technique for order preference by similarity to ideal solution (TOPSIS) |
| title | A Hybrid Best-Worst Method (BWM)—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Approach for Prioritizing Road Safety Improvements |
| title_full | A Hybrid Best-Worst Method (BWM)—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Approach for Prioritizing Road Safety Improvements |
| title_fullStr | A Hybrid Best-Worst Method (BWM)—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Approach for Prioritizing Road Safety Improvements |
| title_full_unstemmed | A Hybrid Best-Worst Method (BWM)—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Approach for Prioritizing Road Safety Improvements |
| title_short | A Hybrid Best-Worst Method (BWM)—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Approach for Prioritizing Road Safety Improvements |
| title_sort | hybrid best worst method bwm x2014 technique for order of preference by similarity to ideal solution topsis approach for prioritizing road safety improvements |
| topic | Best-worst method (BWM) multi-criteria decision making (MCDM) road safety improvement simple additive weighting (SAW) technique for order preference by similarity to ideal solution (TOPSIS) |
| url | https://ieeexplore.ieee.org/document/10441826/ |
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