A Generic Bi-Layer Data-Driven Crowd Behaviors Modeling Approach

Authored by Weiwei Xing, Shibo Zhao, Shunli Zhang, Yuanyuan Cai

Date Published: 2017

DOI: 10.1587/transinf.2016edp7438

Sponsors: Chinese National Natural Science Foundation

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Crowd modeling and simulation is an active research field that has drawn increasing attention from industry, academia and government recently. In this paper, we present a generic data-driven approach to generate crowd behaviors that can match the video data. The proposed approach is a bi-layer model to simulate crowd behaviors in pedestrian traffic in terms of exclusion statistics, parallel dynamics and social psychology. The bottom layer models the microscopic collision avoidance behaviors, while the top one focuses on the macroscopic pedestrian behaviors. To validate its effectiveness, the approach is applied to generate collective behaviors and re-create scenarios in the Informatics Forum, the main building of the School of Informatics at the University of Edinburgh. The simulation results demonstrate that the proposed approach is able to generate desirable crowd behaviors and offer promising prediction performance.

Tags

Simulation Agent-based modeling Agents Crowd simulation Motion Navigation Data-driven approach Pedestrian behaviors