Listen to the people! comparing perceived and documented disruptions in public transportation, through quantitative quality of experience, the case study of NYC

Gabriela Gongora Svartzman, Jose E.Ramirez Marquez

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    5 Scopus citations

    Abstract

    Public transportation systems are core infrastructures to smart cities and are expected to perform on a daily basis and in a reliable manner. However, such systems can be affected by external and internal events that manifest as delays. There are two sources customers can consult, which will impact their decision rewarding commuting times; either the official (provided by the transportation agency) or the reported by other passengers. It is debated whether the first approach is more accurate than the latter. This work compares both alternatives, using Natural Language Processing techniques and visual analytics to determine the delays on trains and evaluate their resilience process. For this purpose the impact of a massive snowstorm in November, 2018 to New York's Metro North Railroad system was used as a case study.

    Original languageEnglish
    Title of host publication2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
    Pages947-952
    Number of pages6
    ISBN (Electronic)9781728145693
    DOIs
    StatePublished - Oct 2019
    Event2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy
    Duration: 6 Oct 20199 Oct 2019

    Publication series

    NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
    Volume2019-October
    ISSN (Print)1062-922X

    Conference

    Conference2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
    Country/TerritoryItaly
    CityBari
    Period6/10/199/10/19

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