Modelo macroscópico del tráfico y estimación del tiempo de viaje en autopistas utilizando datos de sensores radar

Abstract

Traffic management on highways is crucial for sustainable mobility and reducing congestion. This study applies macroscopic traffic models, based on radar sensor data, over a 17 km section of the Cuenca-Azogues highway, between Vista Linda and Puerta de Hierro. Its objective is to improve travel time reliability and optimize traffic flow, highlighting the importance of these models for road safety. Congestion and maximum speed data were analyzed, applying Greenshields' theorem to model traffic flow. Travel time reliability was evaluated through the Travel Time Index (TTI), Buffer Index (BI), and Level of Service (LOS). The most significant results show two congestion peaks: from 7:00-8:00 am and from 6:00-7:00 pm, with Wednesday being the most congested day. The south-north direction was more critical from 7:00-8:00 am, and the north-south direction from 5:00-6:00 pm. Maximum speeds were 72.94 km/h in the south-north direction and 74.80 km/h in the north-south direction. The analysis based on Greenshields' theorem concluded that no significant congestion occurs. The weighted TTI was 1.28 for the south-north direction and 1.25 for the north-south direction, both corresponding to a LOS of "B." It is recommended to implement a traffic management system and create a broader data repository to improve future traffic management.