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Open AccessJournal ArticleDOI

Social Force Model for Pedestrian Dynamics

Dirk Helbing, +1 more
- 01 May 1995 - 
- Vol. 51, Iss: 5, pp 4282-4286
TLDR
Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.
Abstract
It is suggested that the motion of pedestrians can be described as if they would be subject to ``social forces.'' These ``forces'' are not directly exerted by the pedestrians' personal environment, but they are a measure for the internal motivations of the individuals to perform certain actions (movements). The corresponding force concept is discussed in more detail and can also be applied to the description of other behaviors. In the presented model of pedestrian behavior several force terms are essential: first, a term describing the acceleration towards the desired velocity of motion; second, terms reflecting that a pedestrian keeps a certain distance from other pedestrians and borders; and third, a term modeling attractive effects. The resulting equations of motion of nonlinearly coupled Langevin equations. Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.

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Citations
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Journal ArticleDOI

A spatio-temporal probabilistic model of hazard- and crowd dynamics for evacuation planning in disasters

TL;DR: A novel spatio-temporal probabilistic model that integrates crowd and hazard dynamics, using ship- and building fire as proof-of-concept scenarios, and opens up for novel in situ threat mapping and evacuation planning under uncertainty, with applications to emergency response.
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Effects of back step and update rule on congestion of mobile objects

TL;DR: It is found that there is always a phase transition from free flow to jammed state at some critical density with and without back step under sequential and parallel update for large systems.

A Discrete Choice Modeling Framework for Pedestrian Walking Behavior with Application to Human Tracking in Video Sequences

TL;DR: This work addresses the problem of pedestrian walking behavior modeling, interpreting the walking process as a sequence of choices over time, and chooses a mathematical framework based on discrete choice analysis, which provides a set of well founded econometric tools to model disaggregate phenomena.
Posted Content

Social NCE: Contrastive Learning of Socially-aware Motion Representations

TL;DR: In this paper, a social contrastive loss is introduced to regularize the extracted motion representation by discerning the ground-truth positive events from synthetic negative ones, and informative negative samples are constructed based on prior knowledge of rare but dangerous circumstances.
Journal ArticleDOI

Pedestrian Trajectory Prediction Combining Probabilistic Reasoning and Sequence Learning

TL;DR: A novel framework for pedestrian trajectory prediction is presented, which integrates Dynamic Bayesian network and Sequence-to-Sequence model through an adaptive online weighting method, and results show that the model outperforms those baselines.
References
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Book

Field theory in social science

Kurt Lewin
Book

Kinetic theory of vehicular traffic

TL;DR: A theory of multi-LANE traffic flow and the space-time evolution of thevelocity distribution of cars are examined to help understand the role of driver behaviour and strategy in this network.
Journal ArticleDOI

Improved fluid-dynamic model for vehicular traffic.

TL;DR: The fluid-dynamic traffic model of Kerner and Konh\"auser is extended by an equation for the vehicles' velocity variance, able to describe the observed increase of velocity variance immediately before a traffic jam develops.
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