Multiple mobility data fusion & enrichment for demand-driven mobility use cases

Data-driven mobility analyses are gaining more and more importance for future-oriented, demand-driven and sustainable transportation planning. They allow for small-scale spatial, urban, and transportation planning. In MultiMoFusion, district and neighborhood development are the focus of use case orientated research. In order to assess the impact of neighbourhood-related mobility measures, traditional survey methods are hardly sufficient due to limited spatial, content-related and temporal resolution. By complementing them with new, innovative survey methods, it is possible to close knowledge gaps. Therefore, the goal of MultiMoFusion is to enrich SMASI (Smartphone Assisted Self-Interviews) surveys with anonymized mobile phone movement data (Floating Phone Data (FPD)). A holistically new, high-quality and quantitative demand data source with the advantages of both data worlds is generated.

MultiMoFusion also deals with the innovative use of new and target-oriented communication based on data. Methods from storytelling supplemented with interactive (geo)visualization elements in form of storymaps can be used to generate attention for current mobility challenges. Likewise, the collection of technical, organizational and legal integration requirements towards a future national mobility data space and the investigation of transferability will take place.

Aspern Seestadt is an perfect laboratory for testing and experimenting within the framework of MultiMoFusion. The SMASI data collected here in the scope of the mobility panel form a strong basis for MultiMoFusion. In addition to the existing data of the study area, macroscopic mobile phone movement data will be added. A data fusion is to be used to create a model that improves the SMASI data on the basis of the floating phone data in order to increase representativeness on the one hand and also to depict a continuous, temporal longitudinal section of mobility on the other.

The combination of the fused data and the use of further quantitative but also qualitative methods in the context of the Use Cases shows the advantages, limits and potentials of data fusion. Together with stakeholders, further possible applications (Future Cases) will be discussed and collected - where a transfer strategy to other areas will also be developed.

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