A hybrid simulation-assignment modeling framework for crowd dynamics in large-scale pedestrian facilities. (April 2016)

• Record Type: Journal Article
• Authors: Abdelghany, Ahmed; Abdelghany, Khaled; Mahmassani, Hani
• Is Part Of: Transportation research. Volume 86(2016)
• Page Start: 159
• Page End: 176
• Publication Date: 2016-04
• Subjects: Crowd dynamics -- Simulation models -- Networks -- Cellular automata -- Pedestrian flow; Transportation -- Research -- Periodicals; 388.011
• DOI: 10.1016/j.tra.2016.02.011
• Languages: English
• ISSNs: 0965-8564

Abstract

Highlights: Modeling framework for crowd management. Hybrid network representation structure. Shortest path algorithm on a node-link network. Tactical level on a cellular automata network. Application to large-scale facility on large crowd. Abstract: This paper presents a hybrid simulation-assignment modeling framework for studying crowd dynamics in large-scale pedestrian facilities. The proposed modeling framework judiciously manages the trade-off between ability to accurately capture congestion phenomena resulting from the pedestrians' collective behavior and scalability to model large facilities. We present a novel modeling framework that integrates a dynamic simulation-assignment logic with a hybrid (two-layer or bi-resolution) representation of the facility. The top layer consists of a network representation of the facility, which enables modeling the pedestrians' route planning decisions while performing their activities. The bottom layer consists of a high resolution Cellular Automata (CA) system for all open spaces, which enables modeling the pedestrians' local maneuvers and movement decisions at a high level of detail. The model is applied to simulate the crowd dynamics in the ground floor of Al-Haram Al-Sharif Mosque in the City of Mecca, Saudi Arabia during the pilgrimage season. The analysis illustrates the model's capability in accurately representing the observed congestion phenomena in the facility.