Modelling Road Saturation Dynamics on a Complex Transportation Network Based on GPS Navigation Software Data

High traffic concentration during weekdays in the Great Metropolitan Area of Costa Rica causes severe traffic congestion and high costs for the population. It is crucial to deeply understand the dynamics of traffic congestion to design and implement long term solutions. Given the lack of official data to study traffic congestion, we model it using a transportation network based on data captured throughout the year 2018 by a GPS navigation software application (Waze), provided by the Ministry of Public Works and Transportation (MOPT in Spanish). In this paper, we focus on the data transformation procedure to create the transportation network and propose a traffic congestion classification with the available data. We developed a practical methodology which consists of four main stages: data preparation, road network modelling, road saturation estimation, and saturation dynamics analysis. The results show it is possible to model road saturation level using the proposed methodology. We were able to classify road segments in five categories that effectively represent the levels of road saturation. This classification gives us a clear overview of the real-world conditions faced by road network users.