Refining SUMO Simulation Strategies for Realistic Traffic Patterns: Insights from Field Experience

Urbanization and the surge in vehicle numbers have posed significant challenges, including tackling traffic congestion, reducing ecological footprint, and enhancing safety. In the context of developing efficient and sustainable transportation technologies, this research focuses on gaining insights into traffic patterns, human behavior, and their impact on urban livability. Drawing on field experience, this study investigates the intricate traffic conditions in the regional shopping center of Saint-Quentin-en-Yvelines using advanced SUMO simulations. By refining traffic models and fine-tuning their parameters, the simulation strategy is gradually adjusted to accurately simulate the traffic dynamics. Generated data are then analyzed to ascertain the usefulness of the whole approach in capturing realistic traffic patterns. The outcomes pave the way for designing smart vehicular applications to improve traffic flow in comparable urban contexts.