The Mobility Oracle: A Framework for Approximating Human Mobility

Abstract

Urban mobility modeling plays a critical role in understanding transport infrastructure and improving its efficiency and sustainability. While existing tools are effective for mobility modeling, they typically require extensive data acquisition, such as surveys, questionnaires, or tracking, as well as domain knowledge for calibration. Instead, we propose the Mobility Oracle , a framework that algorithmically approximates urban mobility by incorporating human preferences in the routing process.

The framework builds on open-source data and generates a synthetic dataset for further analysis. It is reproducible, modular, and flexible, making it straightforward to adapt to different contexts. Both the theoretical components and the practical implementation are presented, along with a case study that illustrates the framework’s potential applications.

Validation is carried out for Vienna (Austria) and Munich (Germany), comparing our approach against the official city-wide modal splits and a small tracked dataset within one of the cities. The resulting mode shares show a maximum difference of 10% at the city scale and 1.9% for the tracked sample. These results demonstrate that Mobility Oracle can be a useful tool to approximate human mobility.

City planners and decision makers can use it to systematically test and evaluate alternative planning scenarios in different urban contexts.