652
Views
22
CrossRef citations to date
0
Altmetric
ARTICLES

A macroscopic approach for calibration and validation of a modified social force model for bidirectional pedestrian streams

, ORCID Icon, & ORCID Icon
Pages 1637-1661 | Received 12 Oct 2018, Accepted 21 Jun 2019, Published online: 04 Jul 2019
 

Abstract

The original social force model of pedestrians and its variants have been extensively studied in the past. However, little attention has been given to their parameter estimation and validation specifically for the environments with high density and complex phenomena such as self-organization and lane formation. This paper presents a macroscopic framework for calibration and validation of a modified social force model for bidirectional pedestrian streams based on the concept of pedestrian area-wide fundamental diagram, also known as pedestrian Macroscopic Fundamental Diagram (p-MFD). Results demonstrate that the proposed calibration process and the modified social force model can reproduce the empirically observed p-MFD with features such as hysteresis while consistently generating microscopic emergent self-organization and lane formation phenomena. Overall, validation and application results suggest that the calibrated model successfully replicates pedestrian traffic patterns and support the future applications of the model for various operations and planning purposes.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 594.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.