Crowd Hybrid Model for Pedestrian Dynamic Prediction in a Corridor

Xiaoxia Yang,Qianling Wang

doi:10.1109/access.2019.2928556

Xiaoxia Yang, Qianling Wang

Open Access

https://doi.org/10.1109/access.2019.2928556

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Journal: IEEE Access	Publication Date: Jan 1, 2019
Citations: 21	License type: CC BY 4.0

Affiliation: Qingdao University, Hebei University of Technology

Abstract

The pedestrian dynamic prediction is of great theoretical significance to provide information to staff in public buildings for decision makings. Based on the conservation law of mass and the social force model, the crowd hybrid model, in which the heterogeneity of pedestrians from the microscopic level is considered, is established to predict the dynamic characteristics of pedestrian flow in a corridor. In this model, the corridor is divided into multiple calculation black boxes in which the number of pedestrians is conserved, and the adopted density-outflow data via social force model is required to be saved in the data base in advance. The crowd dynamics in the corridor is studied, and simulation results indicate that the pedestrian density and motion state, i.e., free state and jamming state, can be predicted. The proposed crowd hybrid model combines the advantages of both macroscopic pedestrian movement model with less computation and microscopic pedestrian movement model considering the detailed interactions of individuals. This hybrid modeling method is especially suitable for the pedestrian dynamic prediction in a corridor where a camera or laser cannot satisfy the requirements of monitoring.

Highlights

Corridors occupy important roles in public buildings, e.g. subway stations, airports, or stadiums
THE CROWD HYBRID MODEL In order to monitor and predict pedestrian dynamics in the corridor, especially in the complex shape of the corridor such as a S-bend, this paper proposes a hybrid modeling method based on the microscopic social force model (SFM) and the law of mass conservation
Based on the crowd hybrid model proposed in this paper, we should first obtain the initial information of pedestrian density in each calculation black box, determine the value of outflow according to Eqs. (6)-(7)

Summary

INTRODUCTION

Corridors occupy important roles in public buildings, e.g. subway stations, airports, or stadiums. One of the main contributions in this paper is to propose a hybrid method to solve the problem of pedestrian flow state prediction with high real-time performance, in order to control inflows in advance which could help avoiding congestions. This hybrid model can give full play to the advantages of microscopic model such as SFM in describing individual habits, gender, heterogeneity and other detailed behaviors, and give play to the characteristics of macroscopic model with less computation.

DESCRIPTION OF THE SFM

VERIFICATION OF THE CROWD HYBRID MODEL

MODEL VALIDITY ANALYSIS

CONCLUSION