Real-Time Evacuation Simulation in Mine Interior Model of Smoke and Action

Virtual human crowd models have been used in the simulation of building and urban evacuation, but have not yet applied to underground coal mine operations and escape situations with emphasis on smoke, fires and physiological behaviors. We explore this through a real-time simulation model, MIMOSA (Mine Interior Model Of Smoke and Action), which integrates an underground coal mine virtual environment, a fire and smoke propagation model, and a human physiology and behavior model. Each individual agent has a set of physiological parameters as variables of time and environment, simulating a miner’s physiological condition during normal operations as well as during emergencies due to fire and smoke. To obtain appropriate agent navigation in the mine environment, we have extended the HiDAC framework (High- Density Autonomous Crowds) navigation from a grid-based cell-portal graph to a geometrybased portal path and integrated a novel cellportal and shortest path visibility algorithm

Pedestrian Flow Simulation Validation and Verification Techniques

For the verification and validation of microscopic simulation models of pedestrian flow, we have performed experiments for different kind of facilities and sites where most conflicts and congestion happens e.g. corridors, narrow passages, and crosswalks. The validity of the model should compare the experimental conditions and simulation results with video recording carried out in the same condition like in real life e.g. pedestrian flux and density distributions. The strategy in this technique is to achieve a certain amount of accuracy required in the simulation model. This method is good at detecting the critical points in the pedestrians walking areas. For the calibration of suitable models we use the results obtained from analyzing the video recordings in Hajj 2009 and these results can be used to check the design sections of pedestrian facilities and exits. As practical examples, we present the simulation of pilgrim streams on the Jamarat bridge. The objectives of this study are twofold: first, to show through verification and validation that simulation tools can be used to reproduce realistic scenarios, and second, gather data for accurate predictions for designers and decision makers.Comment: 19 pages, 10 figure

A spectral density approach for modelling continuous vertical forces on pedestrian structures due to walking

Existing walking models used for vibration serviceability assessment of structures carrying pedestrians are typically based on measurements of single footfalls replicated at precise intervals. This assumed perfect periodicity allows walking forces to be modelled as a Fourier series based on the walking pace and its integer multiples. This paper examines real continuous walking forces obtained from an instrumented treadmill and the effect of their random imperfections through time simulations of structural response and shows that there are significant differences between responses due to the imperfect real walking forces and the equivalent perfectly periodic simulation. These differences are most significant for higher harmonics where the simulated vibration response is overestimated. As a realistic representation of imperfect walking is an auto-spectral density function, the random character naturally leads to a stochastic approach to treatment of pedestrian loading applied in the frequency domain. The approach can be used for single pedestrians as well as crowd loading where correlation between pedestrians as well as statistics of their pacing rates is used

LCrowdV: Generating Labeled Videos for Simulation-based Crowd Behavior Learning

We present a novel procedural framework to generate an arbitrary number of labeled crowd videos (LCrowdV). The resulting crowd video datasets are used to design accurate algorithms or training models for crowded scene understanding. Our overall approach is composed of two components: a procedural simulation framework for generating crowd movements and behaviors, and a procedural rendering framework to generate different videos or images. Each video or image is automatically labeled based on the environment, number of pedestrians, density, behavior, flow, lighting conditions, viewpoint, noise, etc. Furthermore, we can increase the realism by combining synthetically-generated behaviors with real-world background videos. We demonstrate the benefits of LCrowdV over prior lableled crowd datasets by improving the accuracy of pedestrian detection and crowd behavior classification algorithms. LCrowdV would be released on the WWW

Position-Based Multi-Agent Dynamics for Real-Time Crowd Simulation (MiG paper)

Exploiting the efficiency and stability of Position-Based Dynamics (PBD), we introduce a novel crowd simulation method that runs at interactive rates for hundreds of thousands of agents. Our method enables the detailed modeling of per-agent behavior in a Lagrangian formulation. We model short-range and long-range collision avoidance to simulate both sparse and dense crowds. On the particles representing agents, we formulate a set of positional constraints that can be readily integrated into a standard PBD solver. We augment the tentative particle motions with planning velocities to determine the preferred velocities of agents, and project the positions onto the constraint manifold to eliminate colliding configurations. The local short-range interaction is represented with collision and frictional contact between agents, as in the discrete simulation of granular materials. We incorporate a cohesion model for modeling collective behaviors and propose a new constraint for dealing with potential future collisions. Our new method is suitable for use in interactive games.Comment: 9 page