A system dynamics approach to strengthening road space reallocation policy

Résumé fourni par la source

Urban mobility systems face climate, health, and spatial challenges that call for policies to reduce private car use while increasing access by public transport and active modes. Road space reallocation shows promise, but there is limited understanding of how citywide implementation affects travel behavior over time. This research addresses this gap by mapping the effects on cycling through causal loop diagrams and building a quantitative System Dynamics (SD) model informed by these diagrams. The method is combined with scenario discovery to evaluate the role of uncertainties on the effectiveness of the policy. The simulation results show that cycling increases in a non-linear way under citywide reallocation. While uncertainties do not influence the direction of change, they do influence the magnitude of change. Uncertainties related to bike adoption are particularly influential. The findings highlight that to increase cycling ridership it is important to promote bike adoption alongside infrastructure improvements. The study contributes by extending and quantifying existing conceptual SD models and by incorporating Diffusion of Innovation theory in a transport model. By explicitly accounting for feedback effects, this study demonstrates the potential of SD to help policymakers anticipate non-linear impacts that unfold over time.