A visual analytics framework for exploring theme park dynamics

Michael Steptoe, Robert Krüger, Rolando Garcia, Xing Liang, Ross Maciejewski

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    In 2015, the top 10 largest amusement park corporations saw a combined annual attendance of over 400 million visitors. Daily average attendance in some of the most popular theme parks in the world can average 44,000 visitors per day. These visitors ride attractions, shop for souvenirs, and dine at local establishments; however, a critical component of their visit is the overall park experience. This experience depends on the wait time for rides, the crowd flow in the park, and various other factors linked to the crowd dynamics and human behavior. As such, better insight into visitor behavior can help theme parks devise competitive strategies for improved customer experience. Research into the use of attractions, facilities, and exhibits can be studied, and as behavior profiles emerge, park operators can also identify anomalous behaviors of visitors which can improve safety and operations. In this article, we present a visual analytics framework for analyzing crowd dynamics in theme parks. Our proposed framework is designed to support behavioral analysis by summarizing patterns and detecting anomalies. We provide methodologies to link visitor movement data, communication data, and park infrastructure data. This combination of data sources enables a semantic analysis of who, what, when, and where, enabling analysts to explore visitor-visitor interactions and visitorinfrastructure interactions. Analysts can identify behaviors at the macro level through semantic trajectory clustering views for group behavior dynamics, as well as at the micro level using trajectory traces and a novel visitor network analysis view.We demonstrate the efficacy of our framework through two case studies of simulated theme park visitors.

    Original languageEnglish (US)
    Article number4
    JournalACM Transactions on Interactive Intelligent Systems
    Volume8
    Issue number1
    DOIs
    StatePublished - Feb 1 2018

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    Semantics
    Trajectories
    Electric network analysis
    Macros
    Communication
    Industry

    Keywords

    • Behavior
    • Semantic trajectories
    • Trajectory analysis
    • Visual analytics

    ASJC Scopus subject areas

    • Human-Computer Interaction
    • Artificial Intelligence

    Cite this

    A visual analytics framework for exploring theme park dynamics. / Steptoe, Michael; Krüger, Robert; Garcia, Rolando; Liang, Xing; Maciejewski, Ross.

    In: ACM Transactions on Interactive Intelligent Systems, Vol. 8, No. 1, 4, 01.02.2018.

    Research output: Contribution to journalArticle

    Steptoe, Michael ; Krüger, Robert ; Garcia, Rolando ; Liang, Xing ; Maciejewski, Ross. / A visual analytics framework for exploring theme park dynamics. In: ACM Transactions on Interactive Intelligent Systems. 2018 ; Vol. 8, No. 1.
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