A Mobility Model of Theme Park Visitors

Realistic human mobility modeling is critical for accurate performance evaluation of mobile wireless networks. Movements of visitors in theme parks affect the performance of systems which are designed for various purposes including urban sensing and crowd management. Previously proposed human mobility models are mostly generic while some of them focus on daily movements of people in urban areas. Theme parks, however, have unique characteristics in terms of very limited use of vehicles, crowd's social behavior, and attractions. Human mobility is strongly tied to the locations of attractions and is synchronized with major entertainment events. Hence, realistic human mobility models must be developed with the specific scenario in mind. In this paper, we present a novel model for human mobility in theme parks. In our model, the nondeterminism of movement decisions of visitors is combined with deterministic behavior of attractions in a theme park. The attractions are categorized as rides, restaurants, and live shows. The time spent at these attractions are computed using queueing-theoretic models. The realism of the model is evaluated through extensive simulations and compared with the mobility models SLAW, RWP and the GPS traces of theme park visitors. The results show that our proposed model provides a better match to the real-world data compared to the existing models.

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