Nowadays, one of the most popular and ecological forms of passengers’ transport is rail. In the last couple of years (especially after COVID-19 pandemic) many more passengers selected this type of transportation rather than cars or even airplanes. It is connected with much higher travel comfort as well as the possibility of effective work on the train. However, due to the higher popularity, one extremely important problem was observed. It is connected with the passengers’ flow that can lead even to traffic. Sometimes it is hard to select an appropriate type of train to effectively serve all the interested people. In this work, we would like to propose not only the survey under the latest AI-based models for prediction of passengers’ pileups but also provide information about possible ideas that will be tested on the real data, collected from one of the trains stations in Poland.


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    Title :

    Artificial Intelligence models for prediction of passengers’ flow in rail transport


    Contributors:


    Publication date :

    2024-08-27


    Size :

    769839 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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