Road Safety Resource Allocation Using Interactive Multiobjective Optimization

Augeri, Maria Grazia · 2021 · Crossref

DOI: 10.48295/et.2021.84.4

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Summary

This paper addresses the challenge of allocating limited road safety budgets to hazardous sites to maximize safety benefits while minimizing costs. The authors propose a decision-support tool for safety engineers and decision-makers (DMs) to prioritize countermeasures across multiple locations, considering conflicting objectives such as reducing accident frequencies, minimizing implementation and maintenance costs, and maximizing the service life of interventions. The motivation stems from the need for a transparent, interactive methodology that avoids the arbitrary aggregation of objectives found in traditional cost-benefit analyses or weighted sum approaches. The study introduces an Interactive Multiobjective Optimization method based on the Dominance-based Rough Set Approach (IMO-DRSA). This methodology utilizes binary (0-1) integer variables to represent the implementation or non-implementation of specific countermeasures. The process is iterative: first, a set of Pareto-optimal solutions is generated; second, the DM evaluates these solutions and identifies a subset as "good." The DRSA then induces decision rules from these preferences, which are translated into constraints to refine the solution space in subsequent iterations. This continues until the DM identifies a satisfactory compromise solution. The model incorporates Crash Modification Factors (CMFs) to estimate the expected reduction in crashes, accounting for the combined effects of multiple simultaneous countermeasures using a non-linear formula to avoid overestimation. The methodology is demonstrated through a case study involving 43 urban intersections in Italy identified as high-crash locations. The analysis considered various low-cost countermeasures, such as road lighting, signage, and traffic calming measures, with a budget constraint between €30,000 and €35,000. Five objective functions were maximized: total crash reduction, number of countermeasures with medium or high service life, and number of countermeasures with low or medium operation and maintenance costs. In the initial iteration, eight Pareto-optimal solutions were presented to an expert panel acting as the DM. The panel rated three solutions as "good," allowing the system to induce decision rules. For instance, one induced rule specified that a solution is "good" if it includes at least 33 countermeasures with operation and maintenance costs rated "at most" medium. These rules helped narrow the feasible solutions to better align with the DM's preferences. The significance of this work lies in providing a structured, transparent framework for resource allocation that respects the DM's subjective preferences without requiring arbitrary weighting of objectives. By using easily understandable "if-then" decision rules, the IMO-DRSA method facilitates stakeholder interaction and ensures that the final allocation strategy is both technically sound and politically acceptable. The approach is scalable and adaptable to different planning periods, countermeasure types, and budget constraints, offering a robust alternative to traditional optimization techniques in road safety management.

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• comparative international