A GIS-MCDA spatial classification model to support group decision-making in traffic crash risk management

• Novel GIS-MCDA framework integrates group decision-making with spatial analysis for traffic safety management. • PROMSORT method enables transparent classification of road risk levels incorporating multiple stakeholders. • Geographic visualization of results allows the identification of crash-prone areas for targeted interventions. The global incidence of fatalities resulting from road crashes, particularly in Brazil, is a matter of great concern. Public managers need to employ efficient measures to decrease these figures. A multicriteria model of geographic support for group decision-making is proposed in this context. The model considers the preferences of many decision-makers involved in traffic management in a medium-sized city in northeastern Brazil. A methodology was presented for simplifying the categorization of routes for each decision maker and the integration of individual outcomes into a collective outcome. Considering the viewpoint of each decision maker, it was suggested that the city’s roads be categorized based on the level of risk they present for the occurrence of traffic crashes using the PROMSORT multicriteria approach. The ultimate categorization was established by considering five distinct categories that indicate different degrees of route importance. The results were geographically represented using a Geographic Information System. Employing the framework may accurately identify the city’s most susceptible regions and allocate resources and risk reduction initiatives with greater efficiency. Therefore, it is possible to obtain valuable information that can assist municipal managers in creating more efficient strategies to improve road safety.