ArticleEntropy (Basel, Switzerland)2022
An Integrated Fuzzy Analytic Hierarchy Process (AHP) Model for Studying Significant Factors Associated with Frequent Lane Changing.
Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 37 citations in OpenAlex.
- Crash causation, countermeasures, and strengthening of road safety policy in Nepal: a narrative review.Frontiers in public health · 2026Review
- A hybrid fuzzy and convolutional neural network framework for urban road traffic risk and sustainability assessment.Scientific reports · 2025Article
- Auditing road safety achievement using MEREC-ARAS-QBKM model: an empirical study for APEC member economies.Scientific reports · 2024Article
- Article
- Extended Multicriteria Group Decision Making with a Novel Aggregation Operator for Emergency Material Supplier Selection.Entropy (Basel, Switzerland) · 2023Article
- Temporal Instability of Factors Affecting Injury Severity in Helmet-Wearing and Non-Helmet-Wearing Motorcycle Crashes: A Random Parameter Approach with Heterogeneity in Means and Variances.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
7 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Frequent lane changes cause serious traffic safety concerns, which involve fatalities and serious injuries. This phenomenon is affected by several significant factors related to road safety. The detection and classification of significant factors affecting lane changing could help reduce frequent lane changing risk. The principal objective of this research is to estimate and prioritize the nominated crucial criteria and sub-criteria based on participants' answers on a designated questionnaire survey. In doing so, this paper constructs a hierarchical lane-change model based on the concept of the analytic hierarchy process (AHP) with two levels of the most concerning attributes. Accordingly, the fuzzy analytic hierarchy process (FAHP) procedure was applied utilizing fuzzy scale to evaluate precisely the most influential factors affecting lane changing, which will decrease uncertainty in the evaluation process. Based on the final measured weights for level 1, FAHP model estimation results revealed that the most influential variable affecting lane-changing is 'traffic characteristics'. In contrast, compared to other specified factors, 'light conditions' was found to be the least critical factor related to driver lane-change maneuvers. For level 2, the FAHP model results showed 'traffic volume' as the most critical factor influencing the lane changes operations, followed by 'speed'. The objectivity of the model was supported by sensitivity analyses that examined a range for weights' values and those corresponding to alternative values. Based on the evaluated results, stakeholders can determine strategic policy by considering and placing more emphasis on the highlighted risk factors associated with lane changing to improve road safety. In conclusion, the finding provides the usefulness of the fuzzy analytic hierarchy process to review lane-changing risks for road safety.
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