A Computationally Reproducible Multicriteria Framework for Recommending iRAP Road Safety Countermeasures: A Vehicle Occupant Case Study in San Juan, Argentina

This study develops a computationally reproducible multicriteria framework for ranking iRAP road-safety countermeasures and constructing a robust recommended portfolio. The framework was applied to five road tracts on RN 20 and RN 40 in San Juan, Argentina, comprising 292 analytical segments. An immutable Before baseline was constructed for Vehicle Occupants using six crash-type components and the iRAP v3.10 methodology. A dynamic ViDA countermeasure catalog was used to generate reversible segment-countermeasure alternatives, while relative cost, safety benefit, initial risk, coverage, service life, and transformation-rule confidence were incorporated into the decision model. Of 357 unit alternatives evaluated, 283 reduced Vehicle SRS, 74 produced no benefit, and none increased calculated risk. Four deterministic weighting scenarios and 1000 Monte Carlo simulations identified eight very robust and 18 robust alternatives. The resulting 26-alternative portfolio had a relative cost of 26.0 and reduced aggregate Vehicle SRS from 6302.957 to 6132.258, yielding a jointly recalculated benefit of 170.699 SRS units. Twenty-six segments improved and none deteriorated. The framework preserves baseline integrity, supports dynamic inclusion or exclusion of countermeasures, and recalculates their combined modeled effects to avoid double counting. The archived case-study inputs and computational workflow support independent reproduction of the reported numerical results, while transfer to other networks requires context-specific road coding, transformation rules, costs, and engineering review.