The Parameter Calibration of Social Force Model for Pedestrian Flow Simulation Based on YOLOv5

Autor: Tianle Li, Bingbing Xu, Weike Lu, Zidan Chen, Sizheng Zhang, Fanjun Xia
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Sensors, Vol 24, Iss 15, p 5011 (2024)
Druh dokumentu: article
ISSN: 1424-8220
DOI: 10.3390/s24155011
Popis: With the increasing importance of subways in urban public transportation systems, pedestrian flow simulation for supporting station management and risk analysis becomes more necessary. There is a need to calibrate the simulation model parameters with real-world pedestrian flow data to achieve a simulation closer to the real situation. This study presents a calibration approach based on YOLOv5 for calibrating the simulation model parameters in the social force model inserted in Anylogic. This study compared the simulation results after model calibration with real data. The results show that (1) the parameters calibrated in this paper can reproduce the characteristics of pedestrian flow in the station; (2) the calibration model not only decreases global errors but also overcomes the common phenomenon of large differences between simulation and reality.
Databáze: Directory of Open Access Journals
Nepřihlášeným uživatelům se plný text nezobrazuje