Self-Organizing Pedestrian Movement

By Dirk Helbing, Péter Molnár, Illés J. Farkas, Kai Bolay. 2001

825 citations recorded by the source corpus.

Subfields: Building and Construction, Control and Systems Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/ebb274a27303dbb03ee7990bee4ba867882425b2

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Citations in the corpus

Specification of the Social Force Pedestrian Model by Evolutionary Adjustment to Video Tracking Data (2007, background): “These phenomena include the formation of lanes of uniform walking direction in crowds with oppositely moving pedestrians, stripe formation in two intersecting pedestrian streams, and oscillations of the passing direction at bottlenecks under normal conditions with moderate densities [9, 12 ].”
On the Modeling of Traffic and Crowds: A Survey of Models, Speculations, and Perspectives (2011, background): “Experimental activities on crowd emerging phenomena are focused on the selforganizing ability of pedestrians as documented in [103], where a variety of emerging behaviors are visualized.”
Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions (2005, methodology): “The (statically) optimal pedestrian behavior can, in principle, be determined by simulating the learning behavior of pedestrians (Bolay 1998; Helbing et al. 2001).”
Abnormal crowd behavior detection using social force model (2009, background): “While understanding of actions performed by individuals is a problem yet to be fully solved, crowd scene analysis faces even more challenges like emergent behaviors and self-organizing activities [11].”
Core Challenges of Social Robot Navigation: A Survey (2021, methodology): “The Social Force Model (SFM) [94] is one of the most prevalent models in this category.”
Unfreezing the robot: Navigation in dense, interacting crowds (2010, background): “We additionally remark that the illustration in Figure 2(b), the crowd experiments catalogued in the research of [8], [9], [7], the multi-robot coordination theorems of [26], [25], and the tracking experiments of [18], [19], [16], all corroborate the argument that autonomous dynamic agents utilize j”
The biological principles of swarm intelligence (2007, background): “2007) or even crowds of human beings (Helbing et al. 2001).”
Robot navigation in dense human crowds: Statistical models and experimental studies of human–robot cooperation (2015, background): “We additionally remark that in the crowd experiments catalogued in the research of Helbing and Molnar (1995) and Helbing et al. (2001, 2000), the multi-robot coordination theorems of van den Berg et al. (2008, 2009), and the tracking experiments of Pellegrini et al. (2009), Pellegrini et al. (2010)…”
Human mobility: Models and applications (2017, background): “The most popular model falling into this category is the so-called social force model proposed by Helbing and Molnár [225, 226].”
Human Movement Behaviour in Urban Spaces: Implications for the Design and Modelling of Effective Pedestrian Environments (2004, methodology): “…to validate their models using purposely collected observational data relating to a specific behaviour and case-study location (see, for example, Helbing et al, 2001), there is widespread agreement that a more comprehensive appreciation of how pedestrians negotiate space is required to enhance…”
The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics (2010, background): “The study of human crowd dynamics has recently found great interest in many research fields [1,2,3,4,5].”
Encoding Natural Movement as an Agent-Based System: An Investigation into Human Pedestrian Behaviour in the Built Environment (2002, background): “These have led to observations of lifelike emergent phenomena based on simple rules such as lane forming simply by a predisposition to move to the left or right in the face of oncoming traffic (for further details, see Helbing et al, 2001).”
Time-Evolving Measures and Macroscopic Modeling of Pedestrian Flow (2008, background): “…and numerical approximation of the resulting mathematical structures, which is the main target of this work, follow more easily and straightforwardly than in case of standard hyperbolic conservation laws, also used in the specialized literature by some Authors to address analogous problems.”
Traffic and related self-driven many-particle systems (2000, background): “(b) Correlation between the velocity of successive vehicles in the right lane as a function of the density, determined from singlevehicle data (from Helbing et al., 2001b).”