The World Association for Waterborne Transport Infrastructure (PIANC) has recently established guidelines for designing the dimensions of inland waterways through the Safety and Ease of Navigation (S&E) methodology. This approach determines safe waterway widths based on 11 factors estimated in a deterministic manner. The resulting S&E score is then applied to define the safe width of waterways. However, semantic analysis shows that nearly 40 % of these parameters are inherently vague and cannot be unambiguously estimated using deterministic formulas, which limits the reliability of PIANC's methodology. To address this limitation, this study introduces a fuzzy logic model developed in accordance with the Human-Centered Design Approach (HCDA). The model focuses on seven key burden with uncertainty factors – such as crew cohesion, local waterway knowledge, and ship–traffic interactions – capturing the human and environmental dimensions of navigation safety. A Mamdani fuzzy inference system with triangular and trapezoidal membership functions were applied, with parameter values refined through expert elicitation sessions involving experienced inland vessel skippers across Europe. Two French inland navigation case studies (Lower Seine River and the Freycinet network) were used to validate the proposed approach. A case study on the Lower Seine River demonstrates that, unlike the binary PIANC framework, the proposed fuzzy model provides more conservative and nuanced results (0.525 compared to 0.305 in the current state assessment) while still aligning with design requirements. For the Freycinet network, the supportive checking demonstrates a comparable or stronger agreement, with an Accuracy of 77.3 % and Specificity of 81.8 % (compared to 68.2 % and 57.1 % for the Lower Seine), indicating an opportunity for cross-validation due to other case studies. The study demonstrates how the fuzzy model's total score can be directly translated into the required fairway width by interpreting the S&E categories (A, B, C), thereby linking safety evaluation with practical design recommendations. The main contribution of this work lies in systematically integrating HCDA principles into inland waterway planning, ensuring that human factors are explicitly represented. The findings confirm that fuzzy logic significantly enhances the PIANC methodology, supporting safer, more resilient, and human-centered waterway design. Future research will expand the approach to additional case studies across different European rivers, and investigate adaptive calibration of membership functions to account for varying traffic densities and environmental conditions. • Factors of the first rating group were identified using expert knowledge. • Fuzzy model evaluates waterway S&E due to HCDA. • Fuzzy model provides a broader evaluation than the binary PIANC assessment. • The S&E estimate obtained by the fuzzy model better refines the inland waterway width. • Fuzzy model offers a more realistic and actionable assessment for practitioners.
Medvediev et al. (Fri,) studied this question.
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