Continuum Theory for Pedestrian Traffic Flow: Local Route Choice Modelling and its Implications

Hoogendoorn, Serge P.; Wageningen-Kessels, Femke van; Daamen, Winnie; Duives, Dorine C.; Sarvi, Majid

doi:10.1016/j.trpro.2015.06.020

Cited by 21 publications

(11 citation statements)

References 32 publications

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“…To unravel pedestrian movements on ArenA Boulevard itself, a wide range of research opportunities exist. One exciting research avenue is to combine observations from (low-end) Placemeter cameras and, for example, Bluetooth and Wi-Fi detectors with advanced analytical pedestrian models (10) and Bayesian estimation methods analogously to successful approaches to both estimating car traffic states and data fusion [e.g., Yuan et al (11) and van Hinsbergen et al (12)]. Such a combination may result in comprehensive and scalable methods of estimating pedestrian traffic states.…”

Section: Discussion and Outlookmentioning

confidence: 99%

“…This calculation can be achieved for a location at which the parking lot is the sole incoming flow and for which a direct measurement of pedestrian flows is available. If the camera is located far from the parking lot, then variations in walking speed will hinder the temporal linkage of the two measurements (10). By taking these considerations into account, the authors selected a parking lot next to entrance a 8 and pedestrian count m 2 .…”

Section: Vehicle Occupancy Ratementioning

confidence: 99%

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Multimodal Data Fusion for Big Events

Papacharalampous

Cats

Lankhaar

et al. 2016

Transportation Research Record: Journal of the Transportation R

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Many of the transportation problems that are prevalent in urban areas culminate in large-scale events. Such events generate large multi-modal flows that arrive and depart within short time intervals to constrained areas. Monitoring and managing big events pose a challenge for transport planners, operators, event organizers and city officials. In this study, data concerning multi-modal flows was collected and analyzed for a so-called triple event in Amsterdam, the Netherlands, where more than 60,000 people visited the Amsterdam ArenA area. The collection and fusion of large and diverse datasets provided this study a unique opportunity to reconstruct from incomplete data, the crowds' arrival and departure times and estimate their modal split patterns. Considerably different arrival and departure time patterns are observed for car and public transport users. Visitors that arrive by public transport arrive approximately 45 minutes prior to the event start times compared with 75 minutes for car users. The lag between event end time and the departure time of public transport users is approximately 20-50 minutes whereas a lag of 20-80 minutes can be observed for departing cars. The factors that possibly underlie these differences are discussed along with the limitations of our analysis. The results of this study can support decisions concerning the allocation of parking lots and the scheduling of public transport services.

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Section: Discussion and Outlookmentioning

confidence: 99%

Section: Vehicle Occupancy Ratementioning

confidence: 99%

Multimodal Data Fusion for Big Events

Papacharalampous

Cats

Lankhaar

et al. 2016

Transportation Research Record: Journal of the Transportation R

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“…From a macroscopic (or rather, continuum) perspective, concepts like density, flow and average speed are relatively straightforward to interpret. For an introduction into the key variables for continuum multi-directional pedestrian flow modeling, we refer to Hoogendoorn et al (2015).…”

Section: Definitions and Nomenclaturementioning

confidence: 99%

Macroscopic Fundamental Diagram for pedestrian networks: Theory and applications

Hoogendoorn

Daamen

Knoop

et al. 2018

Transportation Research Part C: Emerging Technologies

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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 and the density spatial variation . 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. AbstractThe 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 and the density spatial variation . 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.

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“…We propose a simple velocity model, which may be applied either in Lagrangian or in Eulerian coordinates. The velocity is calculated using a simplified version of the approach described by Hoogendoorn et al [2014Hoogendoorn et al [ , 2015:…”

Section: Velocity: Speed and Route Choicementioning

confidence: 99%

The Lagrangian coordinate system and what it means for two-dimensional crowd flow models

Wageningen-Kessels

Leclercq

Daamen

et al. 2016

Physica A: Statistical Mechanics and its Applications

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A continuum crowd flow model is reformulated in the Lagrangian coordinate system. The system has proven to give computational advantages over the traditional Eulerian coordinate system for (one-dimensional) road traffic flow. Our extension of the model and simulation method to (two-dimensional) crowd flow paves the way to explore whether the advantages also hold in two dimensions. This paper provides a first exploration and shows that a model and simulation method for two-dimensional crowd flow can be developed in the Lagrangian coordinate system and that is leads to promising results.keywords Crowd flow, Model, Simulation, Lagrangian coordinates ObjectiveCrowd flow models are used to describe, understand and predict collective behaviour of crowds. Roughly, two types of models exist: microscopic models in which the movements of individual pedestrians are described and traced and macroscopic (or continuum) models which are the focus of this study. Continuum models describe the dynamics of crowds as a continuum flow, in terms of average speed, velocity and density [Hughes, 2002]. It has been shown that, in contrast to previous claims, continuum models can reproduce self-organisation and certain important dynamic phenomena such as lane formation and diagonal striping [Hoogendoorn et al., 2014]. Furthermore, simulations based on continuum models have the potential to significantly reduce computation time whilst keeping high accuracy. This makes them useful for a larger range of applications, including real time state estimation and prediction for crowd management and optimisation of control strategies. For this, the solutions to the model equations need to be calculated using both fast and accurate computational methods.The Lagrangian coordinate system has been applied to traffic flow models [Leclercq et al., 2007]. Van Wageningen-Kessels et al. [2010], Yuan et al. [2012] show that the system has many advantages over the traditional Eulerian coordinate system, including more accurate reproduction of shock waves and more efficient state estimation based on trajectory data.Our main contribution is the proposal of an extension of Lagrangian simulation methods previously applied for one-dimensional traffic flow models to two-dimensional crowd flow models. We introduce the reformulation of the two-dimensional continuum crowd flow model into Lagrangian coordinates (Section 2), develop a numerical simulation method (Section 3) and show that it leads to meaningful simulation results (Section 4). Open questions and future research directions are discussed in Section 5.

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Continuum Theory for Pedestrian Traffic Flow: Local Route Choice Modelling and its Implications

Cited by 21 publications

References 32 publications

Multimodal Data Fusion for Big Events

Multimodal Data Fusion for Big Events

Macroscopic Fundamental Diagram for pedestrian networks: Theory and applications

The Lagrangian coordinate system and what it means for two-dimensional crowd flow models

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