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Auflistung nach Schlagwort "Bicycle Data"

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  • Konferenzbeitrag
    BITS: A Key Performance Indicators (KPIs) supported approach to assess traffic safety for cyclists at intersections in the Netherlands
    (EnviroInfo 2022, 2022) Schering, Johannes; Gómez, Jorge Marx
    Traffic safety is an important factor in the decision process whether people decide to use the bicycle or not. Critical situations that do not lead to an accident are often not reported to the police. To fill this knowledge gap, several regions as the city of Zwolle and the Province of Friesland (Netherlands) have started to detect near accidents at intersections among vehicles and bicycles by 3D camera data to evaluate traffic safety. Four intersections in Friesland and Zwolle were monitored. Different types of intersections (e.g. shared space concept) were considered. Near accidents can be divided into different conflict categories depending on vehicle speed and time to collision (Post-Encroachment Time PET). The preprocessed data including Key Performance Indicators (KPIs) to make cycling safety at the intersections measurable and comparable are provided. Based on the numbers and visualizations, it will be discussed which of the discussed intersections show critical profiles regarding numbers of near accidents, distribution and amount of very critical situations. With the results the intersections can be adjusted to increase traffic safety.Encroachment Time PET). The pre-processed data including relevant Key Performance Indicators (KPIs) to make cycling safety at the intersections measurable and comparable are provided. Based on the numbers and visualizations, it will be discussed which of the dis-cussed intersections show critical profiles regarding the total numbers of near accidents, its distribution and the amount of very critical situations. Based on the results the intersections can be adjusted to increase the safety situation in a city.
  • Textdokument
    Potentials of Bicycle Infrastructure Data Lakes to Support Cycling Quality Assessment
    (INFORMATIK 2022, 2022) Schering,Johannes; Marx Gómez,Jorge; Büsselmann,Lena; Alfaro,Federico; Stüven,Jan
    A data-driven quality assessment of bicycle infrastructure is necessary in times of crisis to support the decision-making process in cycling promotion. The INFRASense project was initiated to support the scoring of bike paths by providing new crowdsourcing data that is combined with other relevant data sources (traffic amount, accidents, citizen reportings etc.). The storage and processing of heterogeneous bike infrastructure data may be a challenge. With its flexibility a Data Lake could be an alternative to the traditional Data Warehouse. In the first step the paper gives an overview about data-driven initiatives in the use-case of bike infrastructure quality assessment and the recently started research project INFRASense. We will provide an overview about data sources that may potentially be included into the data driven quality assessment. Big Bicycle Data is available in many different structures and formats (CSV, XML, SHP etc.). In the second step the concepts of Data Lake and Data Warehouse are introduced. The benefits and weaknesses of these two solutions are shown followed by a discussion about which one of these is the best concept for storage, processing, and analysis of heterogeneous bicycle infrastructure data. In the last step we are providing an outlook how an efficient bicycle infrastructure data management system could be implemented.