Macroscopic Fundamental Diagram for pedestrian networks: Theory and applications

Serge P. Hoogendoorn, Winnie Daamen, Victor L. Knoop, Jeroen Steenbakkers, Majid Sarvi

Research output: Contribution to journalConference articleScientificpeer-review

13 Citations (Scopus)
139 Downloads (Pure)

Abstract

The Macroscopic Fundamental diagram (MFD) has proven to be a powerful concept in understanding and managing vehicular network dynamics, both from a theoretical angle and from a more application-oriented perspective. In this contribution, we explore the existence and the characteristics of the pedestrian Macroscopic Fundamental Diagram (p-MFD). From a theoretical perspective, the main contribution of this research shows how we can derive the p-MFD from assumed local fundamental diagrams (FDs). We show that we can relate the average (out-) flow from a pedestrian network as a function of the average spatial density ρ and the density spatial variation σ2. We show that the latter is essential to provide a reasonable description of the overall network conditions. For simple linear relations between density and speed, we derive analytical results; for more commonly used FDs in pedestrian flow theory we show the resulting relation using a straightforward simulation approach. As a secondary contribution of the paper, we show how the p-MFD can be constructed from pedestrian trajectory data stemming from either microsimulation or from experimental studies. The results found are in line with the theoretical result, providing further evidence for the validity of the p-MFD concept. We furthermore discuss concepts of hysteresis, due to the differences in the queue build up and recuperation phases. We end with applications of the presented concepts, e.g. in crowd management.

Original languageEnglish
Pages (from-to)480-496
Number of pages17
JournalTransportation Research Procedia
Volume23
DOIs
Publication statusPublished - 2017

Keywords

  • Macroscopic Fundamental Diagram
  • pedestrian networks
  • spatial variation of density

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