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.

HUMAN–ROBOT COLLISION AVOIDANCE USING A MODIFIED SOCIAL FORCE MODEL WITH BODY POSE AND FACE ORIENTATION

2013 ◽  
Vol 10 (01) ◽  
pp. 1350008 ◽  
Author(s):  
PHOTCHARA RATSAMEE ◽  
YASUSHI MAE ◽  
KENICHI OHARA ◽  
TOMOHITO TAKUBO ◽  
TATSUO ARAI
Keyword(s):  
Collision Avoidance ◽  
Motion Tracking ◽  
Personal Space ◽  
Human Motion ◽  
Force Model ◽  
Social Force ◽  
Social Force Model ◽  
Face To Face ◽  
The Face ◽  
Social Components

The ability of robots to understand human characteristics and make themselves socially accepted by humans are important issues if smooth collision avoidance between humans and robots is to be achieved. When discussing smooth collision avoidance, robot should understand not only physical components such as human position, but also social components such as body pose, face orientation and proxemics (personal space during motion). We integrated these components in a modified social force model (MSFM) which allows robots to predict human motion and perform smooth collision avoidance. In the modified model, short-term intended direction is described by body pose, and a supplementary force related face orientation is added for intention estimation. Face orientation is also the best indication of the direction of personal space during motion, which was verified in preliminary experiments. Our approach was implemented and tested on a real humanoid robot in a situation in which a human is confronted with the robot in an indoor environment. Experimental results showed that better human motion tracking was achieved with body pose and face orientation tracking. Being provided with the face orientation as an indication of the intended direction, and observing the laws of proxemics in a human-like manner, the robot was able to perform avoidance motions that were more human-like when compared to the original social force model (SFM) in a face-to-face confrontation.

scholarly journals An Evacuation Model for Passenger Ships That Includes the Influence of Obstacles in Cabins

2017 ◽  
Vol 2017 ◽  
pp. 1-21 ◽  
Author(s):  
Baocheng Ni ◽  
Zhen Li ◽  
Pei Zhang ◽  
Xiang Li
Keyword(s):  
Force Model ◽  
Social Force ◽  
Key Factors ◽  
Social Force Model ◽  
Interaction Forces ◽  
Factors Affecting ◽  
Agent Based ◽  
Proposed Model ◽  
Passenger Ships ◽  
Passenger Behavior

Passenger behavior and ship environment are the key factors affecting evacuation efficiency. However, current studies ignore the interior layout of passenger ship cabins and treat the cabins as empty rooms. To investigate the influence of obstacles (e.g., tables and stools) on cabin evacuation, we propose an agent-based social force model for advanced evacuation analysis of passenger ships; this model uses a goal-driven submodel to determine a plan and an extended social force submodel to govern the movement of passengers. The extended social force submodel considers the interaction forces between the passengers, crew, and obstacles and minimises the range of these forces to improve computational efficiency. We drew the following conclusions based on a series of evacuation simulations conducted in this study: (1) the proposed model endows the passenger with the behaviors of bypassing and crossing obstacles, (2) funnel-shaped exits from cabins can improve evacuation efficiency, and (3) as the exit angle increases, the evacuation time also increases. These findings offer ship designers some insight towards increasing the safety of large passenger ships.

Modified Social Force Model Based on Predictive Collision Avoidance Considering Degree of Competitiveness

2016 ◽  
Vol 53 (1) ◽  
pp. 331-351 ◽  
Author(s):  
Yuan Gao ◽  
Tao Chen ◽  
Peter B. Luh ◽  
Hui Zhang
Keyword(s):  
Collision Avoidance ◽  
Force Model ◽  
Social Force ◽  
Social Force Model ◽  
Model Based

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 A re-examination of the role of friction in the original Social Force Model

2020 ◽  
Vol 121 ◽  
pp. 42-53 ◽  
Author(s):  
I.M. Sticco ◽  
G.A. Frank ◽  
F.E. Cornes ◽  
C.O. Dorso
Keyword(s):  
Force Model ◽  
Social Force ◽  
Social Force Model

scholarly journals Simulating Interactions between Pedestrians, Segway Riders and Cyclists in Shared Spaces Using Social Force Model

2018 ◽  
Vol 34 ◽  
pp. 91-98 ◽  
Author(s):  
Charitha Dias ◽  
Hiroaki Nishiuchi ◽  
Satoshi Hyoudo ◽  
Tomoyuki Todoroki
Keyword(s):  
Force Model ◽  
Social Force ◽  
Social Force Model ◽  
Shared Spaces
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