Identifying dangerous routes through safety performance functions: case of Costa Rica - Agüero Valverde, Jonathan (2025)
Road network screening is fundamental to reduce the frequency and severity of road crashes. For this purpose it is necessary to have a detailed crash database and an updated road inventory, which are not available in Costa Rica. Recently, macro-level crash models have become popular, since their level of aggregation have lower information requirements; they can be used to develop Safety Performance Functions (SPF) at route level. Using these SPFs routes with excess crash frequency can be identified and a detail safety screening can be performed on those routes. This study seeks to identify the most dangerous routes in Costa Rica using the SPFs and the Empirical Bayes method. The results show that the Negative Binomial model is appropriate to represent the SPFs for routes in Costa Rica since it considers the exposure and over-dispersion present in the data. In addition, the model indicates that the most dangerous routes in Costa Rica in terms of excess deaths are the Route 32, followed by Route 2, Route 4, Route 1 and Route 34. The other 5 routes completing the 10 most dangerous are in order Route 35, Route 21, Route 36, Route 27 and Route 6.