Simulation of Single-File Pedestrian Flow under High-Density Condition by a Modified Social Force Model

Cheng-Jie Jin (), Ke-Da Shi and Shu-Yi Fang
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Cheng-Jie Jin: Jiangsu Key Laboratory of Urban ITS, Southeast University of China, Nanjing 210096, China
Ke-Da Shi: Jiangsu Key Laboratory of Urban ITS, Southeast University of China, Nanjing 210096, China
Shu-Yi Fang: Jiangsu Key Laboratory of Urban ITS, Southeast University of China, Nanjing 210096, China

Sustainability, 2023, vol. 15, issue 11, 1-15

Abstract: In this paper, a new modified social force model is proposed to simulate the single-file pedestrian flow at high densities. Since the pedestrians could only follow the preceding person in the single-file flow, the way in which the pedestrian chooses their destination is changed. It is set as the current position of the preceding pedestrian, rather than as one fixed location. In order to simulate the possible movement at high densities, the distance for calculating forces between pedestrians was reset, and the obstacles were divided into many particles. Next, the values of many model parameters were reset, and the ranges of possible parameters were discussed. Furthermore, the data from one large-scale single-file experiment were used for model validations. The simulation results of the fundamental diagrams, spatiotemporal diagrams and the time–headway distributions show that the new model can simulate the single-file movement well. The angular trajectories can help in understanding more about the simulation results. The comparisons between the statistical results of local flow rates and local densities show that, in most cases, the simulated and experimental results are quantitatively similar. This model could be a good choice for the high-density simulations of single-file pedestrian flow.

Keywords: pedestrian flow; single-file movement; social force model; fundamental diagram; time–headway distribution (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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