Evaluating impacts of traffic regulations in complex mobility systems using scenario-based simulations

Urban traffic regulation policies are increasingly used to address congestion, emissions, and accessibility in cities, yet their impacts are difficult to assess due to the socio-technical complexity of urban mobility systems. Recent advances in data availability and computational power enable new forms of model-driven, simulation-based decision support for transportation policy design. This paper proposes a simulation paradigm for the ex-ante evaluation of direct and indirect impacts, spanning traffic conditions, congestion, and emissions. The approach integrates a multi-layer urban mobility model combining a physical layer of mobility flows and emissions with a social layer capturing behavioral responses and adaptation to policy changes. Real-world data are used to instantiate the current as-is scenario, while policy alternatives and behavioral assumptions are encoded as model parameters to generate multiple what-if scenarios. The paradigm supports systematic comparison across scenarios by analyzing variations in simulated outcomes induced by policy interventions. The proposed approach is illustrated through a case study that aims to assess the impacts of the introduction of broad urban traffic restriction schemes. Results demonstrate the paradigm’s ability to explore alternative regulatory designs, user responses, and modeling assumptions, supporting informed and anticipatory evaluation of urban traffic policies.