Using Motifs for Population Synthesis in Multi-agent Mobility Simulation Models

Abstract

Agent-based mobility simulation (ABMS) models simulate the mobility choices of each individual in a population over a full day. The realization of these choices leads to trips, which consequently determine the demand for different transport infrastructures. Such simulation models need to encode the mobility plans of the whole population in a way that is representative of the investigated population. Recently, mobility motifs have been shown to provide a representation of certain features of the daily activity. The distribution of the motifs is very stable for different regions as well as over time. In this paper, mobility motifs are used as the cornerstone of a new method for population synthesis for ABMS models. We demonstrate how to generate synthetic populations that are representative for the investigated population in terms of the distribution of various control variables including motif choice. The main idea in this respect is to adjust alternative-specific constants in the discrete choice models representing motif choice as well as other mobility choices obtained from individual-level data such that the predicted choice distribution coincides with the one obtained from the aggregated data. Moreover, the dependence of motif choice on a number of underlying socio-demographic features is investigated, demonstrating that while there is some dependence on socio-demographic features, the explanatory power of the corresponding models is minor. The estimated models, however, show a remarkable stability of the coefficients over time. Both factors taken together indicate the potential of motif choice as a central piece in the synthesis of ABMS models.