GPGPU Computing for Microscopic Simulations of Crowd Dynamics

We compare GPGPU implementations of two popular models of crowd dynamics. Specifically, we consider a continuous social force model, based on differential equations (molecular dynamics) and a discrete social distances model based on non-homogeneous cellular automata. For comparative purposes both models have been implemented in two versions: on the one hand using GPGPU technology, on the other hand using CPU only. We compare some significant characteristics of each model, for example: performance, memory consumption and issues of visualization. We also propose and test some possibilities for tuning the proposed algorithms for efficient GPU computations

Evaluating Dynamic Signage for Emergency Evacuation using an Immersive Video Environment

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.There are numerous reasons to evacuate a building in case of emergency; generally evacuation runs in case of constraints as fire, earthquake, indoor air pollution incidents, terrorist attacks and so on. There was a fire tragedy reported on January 28, 2013 in a night club in Brazil that many victims confused the exit sign with that for the toilet sign, where 50 bodies were found dead in toilet. It is reported that the victims lost their sense of direction due to the smoke [1]. Consequently the traditional static emergency signs are no longer effective especially in a complex building. They are not intelligent to decide how many people are using different exit, where the fire is and how much it may spread or how the evacuee will decide and think while they are in panic. They are several attempts to simulate the evacuation area and create a better model to dynamically lead the evacuee to exit. However creating such system is difficult because the prediction of behaviors in emergency incidents, modeling and examination in the real scenario are the biggest problems. Evacuation exercise are expensive and time consuming, as a result Virtual Environment (VEs) might be the feasible solution to create the emergency scenario and to study the physical, cognitive, and perceptual capabilities of the evacuees, letting them to experience and feel the emergency incident that are impossible to apply in the real world. This project presents the use of VE, called Immersive Video Environment (IVE) [2] to investigate and evaluate the possible dynamic signage inside a building to guide the evacuees to safety and exit. IVE system contains three screens with 140 degree from each other using 3 back projected wall at the same time. In this study dynamic signs inform the evacuee by following the exit signs cause of fire emergency and move towards the exit. Generally the user of VE is disoriented or discomforted due to navigation (Travel) part. As a result, following factors are evaluated by using some pre-defined questionnaire such as Simulator Sickness Questionnaire and NASA TLX: 1. The pre-movement time or response time to the dynamic signs. 2. Panic behavior or Decision making 3. Comfort of the system due to navigation part. 4. Performance of IVE 5. Realism of the simulation 8 scenarios have been managed for this experiment in which each of them last around 30 to 40 seconds for a trip from start point to the exit door. In the entire scenario, the exit signs will be varied. The test participants were 10 people (5 Female, 5 Male) who come from different countries not specially Germany. There were great considerable results of decision making in this study for example, there were several errors for the fire sign during the experiment besides the response time for the fire sign were highly more than the other designs. From the evaluator recognition, it is said that their response has been influenced by the exit door or the design of sign. Generally the performance and the comfort of the system show interesting results in the emergency simulation and footage video for VE. There were a significant different in term of discomfort between men and women and the results of their response time had significant difference. By users rating, the realism of the simulation has been confirmed. For response time experiment, some errors and significant variation were observed during the individual test. The IVE can be used for future experiment investigation such as way finding. The proposed system shall help to yield more reliable information about human behavior and decision making in emergency egress and creating a model. Locations, timing, duration and speed, helping from dynamic signs can be considered as decision-making process subject to emergency evacuation

"Last-Mile" preparation for a potential disaster

Extreme natural events, like e.g. tsunamis or earthquakes, regularly lead to catastrophes with dramatic consequences. In recent years natural disasters caused hundreds of thousands of deaths, destruction of infrastructure, disruption of economic activity and loss of billions of dollars worth of property and thus revealed considerable deficits hindering their effective management: Needs for stakeholders, decision-makers as well as for persons concerned include systematic risk identification and evaluation, a way to assess countermeasures, awareness raising and decision support systems to be employed before, during and after crisis situations. The overall goal of this study focuses on interdisciplinary integration of various scientific disciplines to contribute to a tsunami early warning information system. In comparison to most studies our focus is on high-end geometric and thematic analysis to meet the requirements of small-scale, heterogeneous and complex coastal urban systems. Data, methods and results from engineering, remote sensing and social sciences are interlinked and provide comprehensive information for disaster risk assessment, management and reduction. In detail, we combine inundation modeling, urban morphology analysis, population assessment, socio-economic analysis of the population and evacuation modeling. The interdisciplinary results eventually lead to recommendations for mitigation strategies in the fields of spatial planning or coping capacity

Developing an agent-based evacuation simulation model based on the study of human behaviour in fire investigation reports

Fire disasters happen every day all over the world. These hazardous events threaten people's lives and force an immediate movement of people wanting to escape from a dangerous area. Evacuation drills are held to encourage people to practise evacuation skills and to ensure they are familiar with the environment. However, these drills cannot accurately represent real emergency situations and, in some cases, people may be injured during practice. Therefore, modelling pedestrian motion and crowd dynamics in evacuation situations has important implications for human safety, building design, and evacuation processes. This thesis focuses on indoor pedestrian evacuation in fire disasters. To understand how humans behave in emergency situations, and to simulate more realistic human behaviour, this thesis studies human behaviour from fire investigation reports, which provide a variety details about the building, fire circumstance, and human behaviour from professional fire investigation teams. A generic agent-based evacuation model is developed based on common human behaviour that indentified in the fire investigation reports studied. A number of human evacuation behaviours are selected and then used to design different types of agents, assigning with various characteristics. In addition, the interactions between various agents and an evacuation timeline are modelled to simulate human behaviour and evacuation phenomena during evacuation. The application developed is validated using three specific real fire cases to evaluate how closely the simulation results reflected reality. The model provides information on the number of casualties, high-risk areas, egress selections, and evacuation time. In addition, changes to the building configuration, number of occupants, and location of fire origin are tested in order to predict potential risk areas, building capacity and evacuation time for different situations. Consequently, the application can be used to inform building designs, evacuation plans, and priority rescue processes

"Last-Mile" preparation for a potential disaster - Interdisciplinary approach towards tsunami early warning and an evacuation information system for the coastal city of Padang, Indonesia

Extreme natural events, like e.g. tsunamis or earthquakes, regularly lead to catastrophes with dramatic consequences. In recent years natural disasters caused hundreds of thousands of deaths, destruction of infrastructure, disruption of economic activity and loss of billions of dollars worth of property and thus revealed considerable deficits hindering their effective management: Needs for stakeholders, decision-makers as well as for persons concerned include systematic risk identification and evaluation, a way to assess countermeasures, awareness raising and decision support systems to be employed before, during and after crisis situations. The overall goal of this study focuses on interdisciplinary integration of various scientific disciplines to contribute to a tsunami early warning information system. In comparison to most studies our focus is on high-end geometric and thematic analysis to meet the requirements of smallscale, heterogeneous and complex coastal urban systems. Data, methods and results from engineering, remote sensing and social sciences are interlinked and provide comprehensive information for disaster risk assessment, management and reduction. In detail, we combine inundation modeling, urban morphology analysis, population assessment, socioeconomic analysis of the population and evacuation modeling. The interdisciplinary results eventually lead to recommendations for mitigation strategies in the fields of spatial planning or coping capacity.DFG/03G0666A-

Crowd dynamics

Crowd dynamics are complex. This thesis examines the nature of the crowd and its dynamics with specific reference to the issues of crowd safety. A model (Legion) was developed that simulates the crowd as an emergent phenomenon using simulated annealing and mobile cellular automata. We outline the elements of that model based on the interaction of four parameters: Objective, Motility, Constraint and Assimilation. The model treats every entity as an individual and it can simulate how people read and react to their environment in a variety of conditions. Which allows the user to study a wide range of crowd dynamics in different geometries and highlights the interactions of the crowd with their environment. We demonstrate that the model runs in polynomial time and can be used to assess the limits of crowd safety during normal and emergency egress. Over the last 10 years there have been many incidents of crowd related disasters. We highlight deficiencies in the existing guidelines relating to crowds. We compare and contrast the model with the safety guidelines and highlight specific areas where the guides may be improved. We demonstrate that the model is capable of reproducing these dynamics without additional parameters, satisfying Occam's Razor. The model is tested against known crowd dynamics from field studies, including Wembley Stadium, Balham Station and the Hong Kong Jockey club. We propose an alternative approach to assessing the dynamics of the crowd through the use of the simulation and analysis of least effort behaviour. Finally we test the model in a variety of applications where crowd related incidents warrant structural alterations at client sites. We demonstrate that the model explains the variance in a variety of field measurements, that it is robust and that it can be applied to future designs where safety and crowd comfort are criteria for design and cost savings

Integrated evaluation of air flow and gas dispersion for underground station safety strategies based on subway climatology

PhD ThesisRail underground systems are seen as a way to overcome traffic congestion in city environments. Many new subways are being built in China and developing countries. Recent studies have however shown that the ventilation of subway systems is poorly understood. There is significant danger to life if a fire occurs or toxins such as chemical or biological agents are released in a subway. Understanding the air flow inside a subway and how this is affected by the local environment is key in establishing effective evacuation strategies. A series of tracer gas experiments conducted as part of this research have been carried out. To expand the subway climatology from an experimental framework into a virtual and simulation environment, 3D Computational Fluid Dynamic models have been developed, which include the simulation of local microclimate and air movement inside the station respectively. The station CFD model has allowed the analysis of the air flow inside the station under the prevailing external weather condition. Results show promising links between external climatic factors, the subway climatology and the ability to predict the dispersal of smoke/toxins. The local weather pattern has a large influence on the background airflow inside a station and dominated the flow direction at station exits which is been used to evaluate the efficiency of pedestrian evacuation and also determine the safer evacuation route and exit. The possibilities of integrating these findings will allow for a more holistic safety assessment to be carried out that could reduce the loss of life or mitigate harmful effects on public health. It also fills a knowledge gap in design guidelines from a safety perspective underground station construction and ventilation

An operational research-based integrated approach for mass evacuation planning of a city

Large-scale disasters are constantly occurring around the world, and in many cases evacuation of regions of city is needed. ‘Operational Research/Management Science’ (OR/MS) has been widely used in emergency planning for over five decades. Warning dissemination, evacuee transportation and shelter management are three ‘Evacuation Support Functions’ (ESF) generic to many hazards. This thesis has adopted a case study approach to illustrate the importance of integrated approach of evacuation planning and particularly the role of OR/MS models. In the warning dissemination phase, uncertainty in the household’s behaviour as ‘warning informants’ has been investigated along with uncertainties in the warning system. An agentbased model (ABM) was developed for ESF-1 with households as agents and ‘warning informants’ behaviour as the agent behaviour. The model was used to study warning dissemination effectiveness under various conditions of the official channel. In the transportation phase, uncertainties in the household’s behaviour such as departure time (a function of ESF-1), means of transport and destination have been. Households could evacuate as pedestrians, using car or evacuation buses. An ABM was developed to study the evacuation performance (measured in evacuation travel time). In this thesis, a holistic approach for planning the public evacuation shelters called ‘Shelter Information Management System’ (SIMS) has been developed. A generic allocation framework of was developed to available shelter capacity to the shelter demand by considering the evacuation travel time. This was formulated using integer programming. In the sheltering phase, the uncertainty in household shelter choices (either nearest/allocated/convenient) has been studied for its impact on allocation policies using sensitivity analyses. Using analyses from the models and detailed examination of household states from ‘warning to safety’, it was found that the three ESFs though sequential in time, however have lot of interdependencies from the perspective of evacuation planning. This thesis has illustrated an OR/MS based integrated approach including and beyond single ESF preparedness. The developed approach will help in understanding the inter-linkages of the three evacuation phases and preparing a multi-agency-based evacuation planning evacuatio

Modeling and estimation of pedestrian flows in train stations

This thesis addresses two modeling problems related to pedestrian flows in train stations, namely that of estimating pedestrian origin-destination demand in rail access facilities, and that of describing the propagation of pedestrians in walking facilities. For both problems, a mathematical framework is developed at the aggregate level, describing pedestrians in terms of groups with the same departure time, origin and destination. The proposed demand estimator is probabilistic and accounts for within-day dynamics as well as for natural fluctuations across days. It is inspired by estimation methodologies that are used in the context of vehicular traffic. Critically, the proposed methodology takes the train timetable and ridership data into account, significantly improving the accuracy of the estimates. Other information sources, such as link flows or sales data, can also be incorporated. To describe the propagation of pedestrians, walkable space is considered as a network of pedestrian streams that interact locally. Based on the continuum theory for pedestrian flow and the cell transmission model, a computationally efficient model is obtained that can be used under a wide range of traffic conditions. An optional extension allows considering anisotropic flow, where the walking speed depends on the walking direction. Such a formulation is advantageous in particular at high densities. Throughout the thesis, a case study of Lausanne railway station is considered. A detailed discussion of the usage and level-of-service of its rail access facilities is provided, underlining the performance and practical applicability of the proposed modeling framework. The contribution of the thesis is fourfold. First, it provides a dedicated estimation methodology for pedestrian OD demand in train stations. Second, it proposes a novel macroscopic network loading model for congested and multi-directional pedestrian flows. Third, it presents a detailed case study of a Swiss train station, for which a rich data set is collected. Finally, it applies the aforementioned modeling framework to that case study, and provides practical guidance for its use in the planning and dimensioning of rail access facilities. Beyond train stations, the developed modeling framework can be readily applied to various other pedestrian facilities, such as airports, shopping malls, stadiums or urban walking areas. For instance, it may be used to support the organization, planning and design of such facilities, to safely and efficiently manage pedestrian flows using real-time monitoring and control, or to assess and optimize the safety both during normal use and in case of emergency