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The Mobility Oracle: A Framework for Approximating Human Mobility
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OA
AI
DOI：10.3390/smartcities9060101.png)
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Abstract
En 中文
Urban mobility modeling plays a critical role in understanding transport infrastructure and improving its efficiency and sustainability. While existing tools are effective for modeling, they typically require extensive data acquisition, such as surveys, questionnaires, or tracking, as well as domain knowledge for calibration. We propose the Mobility Oracle, a framework that can algorithmically approximate urban mobility by incorporating human preferences in the routing process. The framework relies on open-source data and generates synthetic datasets for further analysis. It can be adapted to different contexts as it is reproducible, modular, and flexible. 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 smaller tracked dataset within one of the cities. The resulting mode shares show an average difference of 4.7% at the city scale and a maximum of 1.9% for the tracked sample. These results demonstrate that the 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 across different urban contexts.
Keywords:
urban mobility
modal split
transportation modeling
OpenStreetMap
human preferences
route analytics
Journal
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