An Urban Traffic Optimization Approach Using Simulation: Case Study in Maceió/AL
Optimization, Traffic simulation, Algorithms
Latin American metropolises have been facing serious traffic congestion problems as a result of rapid population growth, increasing vehicle numbers and inefficient public policies. Most cities do not have a real-time urban traffic control system to optimize the flow of vehicles. In this context, the use of urban traffic optimization models appears as a low cost alternative to evaluate several problems and promote possible improvements. Through the Urban Mobility Simulator (SUMO), this paper proposes a new urban traffic simulation model for a prominent road in the city of Maceió, Alagoas, Brazil. The chosen road was Fernandes Lima Avenue, as it represents one of the most important road corridors of the city. The proposed model allows understanding the behavior of the vehicle flow on the road, which has peculiarities such as the blue lane (exclusive for public transportation) and three sections with pedestrian traffic lights. The validation of the proposed model was done considering data obtained from real observations. The results indicate that the model is capable of providing estimates with errors smaller than 5% related to the volume of vehicle traffic at signalized intersections and smaller than 10% related to the total average travel time of vehicles traveling along the entire avenue. Finally, the analysis of the experimental results shows that it is possible to use the proposed model to apply possible interventions on the street, such as the removal of the pedestrian signals and the blue stripe, resulting in an increase in vehicle flow, reduction of travel time, fuel consumption, and carbon dioxide emissions.