Applying Income-Sensitive Road Pricing Schemes Based on a Transport Model: Simulation Study for Mexico City

Abstract

This study implements the Multi-Agent Transport Simulation (MATSim) Open Mexico City Scenario as an activity-based transport model, which is completely built on open data. The model’s base case is calibrated against real-world origin-destination survey data for Mexico City. In a first case study, different road pricing setups are applied. The different setups vary in the tolled area as well as the applied pricing scheme. Here, either an absolute daily toll of 52 Mexican pesos, or different tolls, which are relative to the agent’s monthly income, are charged. The simulation results show that, the higher the toll, the more car users are drawn to alternative transport modes. With more moderate tolls, fewer agents are drawn from using private cars, but higher total toll revenues are achieved. Therefore, to achieve the highest possible revenue, the model proposes to choose a toll setup featuring a widely expanded toll area as well as moderate prices to prevent as many agents as possible from switching to other transport modes (from private car), which is intuitive. Further, the results suggest that the simulated road pricing measures can be an effective tool to cause a modal switch from private cars to transport modes with high capacities, such as public transport or minibus/taxibus. However, policymakers should be cautious about the implementation, as it could prevent citizens with low monthly incomes from being able to afford the usage of a private car.