scholarly journals A Harmony Search Algorithm for the Reproduction of Experimental Data in the Social Force Model

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Osama Moh'd Alia ◽  
Mohammed Mahmod Shuaib
Keyword(s):  
Experimental Data ◽  
Flow Rate ◽  
Harmony Search ◽  
Force Model ◽  
Social Force ◽  
Specific Flow Rate ◽  
Social Force Model ◽  
Specific Flow ◽  
The Social ◽  
Density Relation

Crowd dynamics is a discipline dealing with the management and flow of crowds in congested places and circumstances. Pedestrian congestion is a pressing issue where crowd dynamics models can be applied. The reproduction of experimental data (velocity-density relation and specific flow rate) is a major component for the validation and calibration of such models. In the social force model, researchers have proposed various techniques to adjust essential parameters governing the repulsive social force, which is an effort at reproducing such experimental data. Despite that and various other efforts, the optimal reproduction of the real life data is unachievable. In this paper, a harmony search-based technique called HS-SFM is proposed to overcome the difficulties of the calibration process for SFM, where the fundamental diagram of velocity-density relation and the specific flow rate are reproduced in conformance with the related empirical data. The improvisation process of HS is modified by incorporating the global best particle concept from particle swarm optimization (PSO) to increase the convergence rate and overcome the high computational demands of HS-SFM. Simulation results have shown HS-FSM’s ability to produce near optimal SFM parameter values, which makes it possible for SFM to almost reproduce the related empirical data.

scholarly journals The Inflection Point of the Speed-Density Relation and the Social Force Model

2016 ◽  
Vol 1 ◽  
Author(s):  
Tobias Kretz ◽  
Jochen Lohmiller ◽  
Johannes Schlaich
Keyword(s):  
Inflection Point ◽  
Temporal Variations ◽  
Force Model ◽  
Social Force ◽  
Social Force Model ◽  
Single File ◽  
Stop And Go ◽  
The Social ◽  
Density Relation ◽  
Continuous Description

It has been argued that the speed-density diagram of pedestrian movement has an inflection point. This inflection point was found empirically in investigations of closed-loop single-file pedestrian movement.The reduced complexity of single-file movement does not only allow a higher precision for the evaluation of empirical data, but it also significantly simplifies analytical considerations. This is especially true if one assumes homogeneous conditions, i.e. neglects temporal variations (consider time averages, neglect stop-and-go waves), individual differences of pedestrians (all simulated pedestrians have identical parameters) and investigates only steady-state (not the initial phase). As will be shown in this contribution one then can make a transition from the microscopic to a continuous and macroscopic perspective.Building on that it will be shown that certain (common) variants of the Social Force Model (SFM) do not produce an inflection point in the speed-density diagram if – assuming periodic boundary conditions – infinitely many pedestrians contribute to the force computed for one pedestrian. It will furthermore be shown that if – in said 1d movement situation – one only considers nearest neighbors for the computation of the inter-pedestrian forces the Social Force Model in the continuous description results in the so called Kladek formula for the speed-density relation. Since the Kladek formula exhibits the desired inflection point this observation is used as a motivation for an extension of the Social Force Model which allows to transform the continuous description of the SFM continuously to the Kladek formula and which also exhibits the inflection point in the speed density relation. It will be shown then, that this extended SFM yields astonishingly similar speed density relations as the original SFM when only a fixed limited number of (nearest) pedestrians are considered in the computation of the inter-pedestrian force.Finally it will be discussed, if also the description of the speed-density diagram for (motorized, four-wheel) vehicular and/or bicycle traffic could benefit from these measures.

scholarly journals SPECIFICATION OF THE SOCIAL FORCE PEDESTRIAN MODEL BY EVOLUTIONARY ADJUSTMENT TO VIDEO TRACKING DATA

2007 ◽  
Vol 10 (supp02) ◽  
pp. 271-288 ◽  
Author(s):  
ANDERS JOHANSSON ◽  
DIRK HELBING ◽  
PRADYUMN K. SHUKLA
Keyword(s):  
Large Scale ◽  
Optimal Parameter ◽  
Video Tracking ◽  
Urban Environments ◽  
Force Model ◽  
Tracking Data ◽  
Social Force ◽  
Social Force Model ◽  
Video Recordings ◽  
The Social

Based on suitable video recordings of interactive pedestrian motion and improved tracking software, we apply an evolutionary optimization algorithm to determine optimal parameter specifications for the social force model. The calibrated model is then used for large-scale pedestrian simulations of evacuation scenarios, pilgrimage, and urban environments.

scholarly journals Speed modulated social influence in evacuating pedestrian crowds

2020 ◽  
Vol 5 ◽  
Author(s):  
Hye Rin Lindsay Lee ◽  
Abhishek Bhatia ◽  
Jenny Brynjarsdóttir ◽  
Nicole Abaid ◽  
Alethea Barbaro ◽  
...  
Keyword(s):  
Experimental Data ◽  
Collision Avoidance ◽  
Social Factors ◽  
Model Parameters ◽  
Force Model ◽  
Confined Space ◽  
Social Force ◽  
Social Force Model ◽  
Agent Based ◽  
Deviation Rate

Evacuation is a complex social phenomenon with individuals tending to exit a confined space as soon as possible. Social factors that influence an individual include collision avoidance and conformity with others with respect to the tendency to exit. While collision avoidance has been heavily focused on by the agent-based models used frequently to simulate evacuation scenarios, these models typically assume that all agents have an equal desire to exit the scene in a given situation. It is more likely that, out of those who are exiting, some are patient while others seek to exit as soon as possible. Here, we experimentally investigate the effect of different proportions of patient (no-rush) versus impatient (rush) individuals in an evacuating crowd of up to 24 people. Our results show that a) average speed changes significantly for individuals who otherwise tended to rush (or not rush) with both type of individuals speeding up in the presence of the other; and b) deviation rate, defined as the amount of turning, changes significantly for the rush individuals in the presence of no-rush individuals. We then seek to replicate this effect with Helbing's social force model with the twin purposes of analyzing how well the model fits experimental data, and explaining the differences in speed in terms of model parameters. We find that we must change the interaction parameters for both rush and no-rush agents depending on the condition that we are modeling in order to fit the model to the experimental data.

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