Simulation Model of Behavioral Preferences of City Park Visitors
УДК 004.942:519.6
Abstract
The article describes the development of a simulation model to analyze the behavioral preferences of city park visitors. The purpose of this model is to identify mass congestion of visitors and study the load on infrastructure facilities. Analysis of these factors is necessary when designing new or changing old infrastructure facilities to create a favorable public environment and increase the safety of visitors in the park.
An approach based on maximizing the utility action using the Utility AI is utilized to simulate human behavior. Behavior trees and smart objects are used to process events and interactions between agents.
The developed model simulates fully the collective behavior of park visitors and helps study the statistical results of each model run. In particular, the application of this model allows identifying places of mass congestion of people in the park and better understanding of the specifics of visitors’ journey across the park. Also, the model helps locate the areas where additional infrastructure elements are needed. The developed model can be used for computer study of other territories of similar type.
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Арутюнян М.А. Математическая модель оценки вероятности пересечения улицы пешеходами в некотором случайном месте // Моделирование, оптимизация и информационные технологии. 2023. Т. 11. № 4 (43). DOI: 10.26102/2310-6018/2023.43.4.036
Зарипова Р.С., Рочева О.А., Гарипова Г.Р. Оптимизация дорожного движения с использованием имитационного моделирования // International Journal of Advanced Studies. 2022. Т. 12. № 3-2. С. 40-45.
Chraibi M., Schadschneider A., Tordeux A. Social Distancing and the Future of Pedestrian Dynamics // arXiv. 2023. DOI: https://arxiv.org/abs/2308.06065
Bellomo N., Gibelli L. Behavioral Human Crowds and Society // Crowd Dynamics, Volume 4. Cham: Springer International Publishing. 2023. P. 1-8. DOI: 10.1007/978-3-031-46359-4_1
Официальная статистика // Официальный сайт Федеральной службы государственной статистики. URL: https://rosstat.gov.ru/statistic (дата обращения: 15.11.2024).
Донских А.К., Барабанов В.Ф., Гребенникова Н.И., Белых М.А. Обзор архитектуры систем управления интеллектом на основе полезности и дерева поведения // Вестник Воронежского государственного технического университета. 2021. Т. 17. № 2. С. 36-41.
Millington I. Artificial Intelligence for Games. London: Morgan Kaufmann Publishers, 2006. 856 p.
Navigation System // Epic Games Unreal Engine Documentation. URL: https://dev.epicgames.com/documentation/ru-ru/unreal-engine/navigation-system-in-unreal-engine? application_version=5.3 (дата обращения: 15.11.2024).
Smart Objects Quick Start // Unreal Engine 5.5 Documentation. URL: https://dev.epicgames.com/documentation/en-us/unreal-engine/smart-objects-in-unreal-engine---quick-start (дата обращения: 15.11.2024).
Ладоша Е.Н., Хмырова А.Д. Применение искусственного интеллекта в процессе 3D моделирования сложных архитектурных объектов // Научный лидер. 2024. № 19 (169). С. 19-22.
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