Utility-based agent model for intermodal behaviors: a case study for urban toll in Lille

Abstract

To reduce the congestion and pollution in urban cities, the political authorities encourage the modal shift from private cars in favor of sustainable trip behaviors such as intermodality (through combinations of private cars and public transport). Coercive decisions such as urban tolls are also an increasingly investigated solution. To avoid the cost of toll taxes, agents thus select intermodal transportation modes (private cars and public transport) by parking their vehicles in park-and-ride (PR) facilities at the entrance to the area toll. This paper proposes a methodology for an agent-based model (ABM), particularly a model called utility-based agent, to reproduce intermodal trip behaviors in a city and to assess the impact of an urban toll. In this context, we focus on multinomial logit models, coupled with the agent-and-activity simulation tool MATSim, is used to determine the modal choice for each agent. Based on open data (for European Metropolis of Lille, MEL), the simulation shows that \(\varvec{20}\) € (\(\varvec{21.75}\) $) of toll tax is sufficient to reduce by \(\varvec{20}\%\) the use of private vehicles.