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Auflistung nach Autor:in "Schering,Johannes"

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  • Textdokument
    A New Approach to Determine Cycling KPIs in the Context of Behavioral Data
    (INFORMATIK 2022, 2022) Moturu,Harish; Marx Gómez,Jorge; Schering,Johannes
    The Corona pandemic has brought a great change in the mobility sector especially in European countries. As a consequence many cities invested much more budget in bike infrastructure than before while the percentage of people using bicycle as the mode of transport for every day routine has been rapidly increased at many places . Available data on cycling use, traffic safety etc. can support the decision making process. We dont't know much about distraction and stress factors when using the bike in a city because such kind of data was not available until now. In the beginning of this paper we present the current state-of-the-art in field of cycling KPIs. What is new in the cycling research domain are cycling KPIs that consider behavioral data. A set of new KPIs in this specific field are introduced in this contribution. As part of the SmartHelm project EEG, eyetracking and GPS data of cargo bike riders was collected and processed. The paper describes the preliminary results obtained from implementing the methodology to calculate behaviour based new cycling KPIs. The conclusion states how the KPIs can be applied in various fields and how it can be adjusted and expanded in the future to the specific stakeholder requirements.
  • 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.