Big Data Application for Urban Transport Solutions

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F22%3A00358403" target="_blank" >RIV/68407700:21260/22:00358403 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/SCSP54748.2022.9792538" target="_blank" >https://doi.org/10.1109/SCSP54748.2022.9792538</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SCSP54748.2022.9792538" target="_blank" >10.1109/SCSP54748.2022.9792538</a>

Result language
angličtina
Original language name
Big Data Application for Urban Transport Solutions
Original language description
With the development of intelligent transport systems in cities, the efficient use of big data is becoming increasingly important. The aim of this paper is to focus on specific sources of Big Data and specific outputs that can be obtained from these data in the conditions of the Czech Republic and then use these to propose recommendations for traffic solutions in a specific traffic area in Prague using the Pelc-Tyrolka area as a case study. In the research part, good examples of practice in the use of Big Data for transport solutions in the area abroad are found. These are then confronted with the real situation within Prague. In the methodology part, the procedure for effective processing and evaluation of different data sources (detector data, FCD data, data from information systems) is defined. Based on this procedure, data from the Pelc-Tyrolka area was evaluated to assess two specific traffic solutions in the area, and based on the results, recommendations were then proposed for future solutions in the area. Finally, the conclusions from the case study are generalized for the future use of Big Data in transport in the conditions of the Czech Republic.
Czech name
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Czech description
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Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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