Estimating travel demand based on OpenStreetMap in the context of urban digital twins

Abstract

A digital twin of a smart city captures the dynamics of people interacting within the urban environment composed of several interconnected systems. Urban mobility, which is simulated by a traffic model within an urban digital twin, is becoming an increasingly complex component within this ecosystem. Demand modeling is an important part of the set-up of a traffic model for a city. Nevertheless, most cities do not have the data, budget, or experience to estimate the demand in their region. Therefore, this study develops a demand generation method that enables to easily estimate travel demand for any region. It is a trip-based modeling approach based on the freelyavailable land-use data of OpenStreetMap (OSM). The model is applied to a case study of Antwerp as part of the Flemish DUET pilot. It is shown a crude estimate of travel demand can be generated from widely available open OSM data.