Household-level electric vehicle assignment for city-scale agent-based transport simulation

Abstract

This study aims to advance the methodological capabilities of agent-based transport simulation models to improve the accuracy of simulated traffic volumes and generate electric vehicle travel demand for further charging studies. It presents an extension to the synthetic population and activity-based demand generation of an existing MATSim model for Greater Melbourne by incorporating a household-level car availability and assignment for both regular vehicles and electric vehicles and for people living in different types of dwelling and household. These contributions are needed because growing electric vehicle adoption and dwelling-type differences drive heterogeneous charging behaviour. Within-household interactions shape individual travel demand and, in turn, electric vehicle energy consumption, both of which are key to charging demand estimates and infrastructure planning. The findings highlight the potential significant benefits in travel demand generation and power grid load prediction using transport models when accounting for the complex mechanisms of household resource constraint, assignment and behaviour.