A Comprehensive Study on Pedestrians' Evacuation

Human beings face threats because of unexpected happenings, which can be avoided through an adequate crisis evacuation plan, which is vital to stop wound and demise as its negative results. Consequently, different typical evacuation pedestrians have been created. Moreover, through applied research, these models for various applications, reproductions, and conditions have been examined to present an operational model. Furthermore, new models have been developed to cooperate with system evacuation in residential places in case of unexpected events. This research has taken into account an inclusive and a 'systematic survey of pedestrian evacuation' to demonstrate models methods by focusing on the applications' features, techniques, implications, and after that gather them under various types, for example, classical models, hybridized models, and generic model. The current analysis assists scholars in this field of study to write their forthcoming papers about it, which can suggest a novel structure to recent typical intelligent reproduction with novel features

A hybrid model for simulating crowd evacuation

Macroscopic and microscopic models are typical approaches for simulating crowd behaviour and movement to simulate crowd and pedestrian movement, respectively. However, the two models are unlikely to address the issues beyond their modelling targets (i.e., pedestrian movement for microscopic models and crowd movement for macroscopic models). In order to solve such problem, we propose a hybrid model integrating macroscopic model into microscopic model, which is capable of taking into account issues both from crowd movement tendency and individual diversity to simulate crowd evacuation. In each simulation time step, the macroscopic model is executed first and generates a course-grain simulation result depicting the crowd movement, which directs microscopic model for goal selection and path planning to generate a fine-grain simulation result. In the mean time, different level-of-detail simulation results can also be obtained due to the proposed model containing two complete models. A synchronization mechanism is proposed to convey simulation results from one model to the other one. The simulation results via case study indicate the proposed model can simulate the crowd and agent behaviour in dynamic environments, and the simulation cost is proved to be efficient

DEVELOPMENT OF A MIXED-FLOW OPTIMIZATION SYSTEM FOR EMERGENCY EVACUATION IN URBAN NETWORKS

In most metropolitan areas, an emergency evacuation may demand a potentially large number of evacuees to use transit systems or to walk over some distance to access their passenger cars. In the process of approaching designated pick-up points for evacuation, the massive number of pedestrians often incurs tremendous burden to vehicles in the roadway network. Hence, one critical issue in a multi-modal evacuation planning is the effective coordination of the vehicle and pedestrian flows by considering their complex interactions. The purpose of this research is to develop an integrated system that is capable of generating the optimal evacuation plan and reflecting the real-world network traffic conditions caused by the conflicts of these two types of flows. The first part of this research is an integer programming model designed to optimize the control plans for massive mixed pedestrian-vehicle flows within the evacuation zone. The proposed model, integrating the pedestrian and vehicle networks, can effectively account for their potential conflicts during the evacuation. The model can generate the optimal routing strategies to guide evacuees moving toward either their pick-up locations or parking areas and can also produce a responsive plan to accommodate the massive pedestrian movements. The second part of this research is a mixed-flow simulation tool that can capture the conflicts between pedestrians, between vehicles, and between pedestrians and vehicles in an evacuation network. The core logic of this simulation model is the Mixed-Cellular Automata (MCA) concept, which, with some embedded components, offers a realistic mechanism to reflect the competing and conflicting interactions between vehicle and pedestrian flows. This study is expected to yield the following contributions * Design of an effective framework for planning a multi-modal evacuation within metropolitan areas; * Development of an integrated mixed-flow optimization model that can overcome various modeling and computing difficulties in capturing the mixed-flow dynamics in urban network evacuation; * Construction and calibration of a new mixed-flow simulation model, based on the Cellular Automaton concept, to reflect various conflicting patterns between vehicle and pedestrian flows in an evacuation network

Multi-Agent Fitness Functions For Evolutionary Architecture

The dynamics of crowd movements are self-organising and often involve complex pattern formations. Although computational models have recently been developed, it is unclear how well their underlying methods capture local dynamics and longer-range aspects, such as evacuation. A major part of this thesis is devoted to an investigation of current methods, and where required, the development of alternatives. The main purpose is to utilise realistic models of pedestrian crowds in the design of fitness functions for an evolutionary approach to architectural design. We critically review the state-of-the-art in pedestrian and evacuation dynamics. The concept of 'Multi-Agent System' embraces a number of approaches, which together encompass important local and longer-range aspects. Early investigations focus on methods-cellular automata and attractor fields-designed to capture these respective levels. The assumption that pattern formations in crowds result from local processes is reflected in two dimensional cellular automata models, where mathematical rules operate in local neighbourhoods. We investigate an established cellular automata and show that lane-formation patterns are stable only in a low-valued density range. Above this range, such patterns suddenly randomise. By identifying and then constraining the source of this randomness, we are only able to achieve a small degree of improvement. Moreover, when we try to integrate the model with attractor fields, no useful behaviour is achieved, and much of the randomness persists. Investigations indicate that the unwanted randomness is associated with 2-lattice phase transitions, where local dynamics get invaded by giant-component clusters during the onset of lattice percolation. Through this in-depth investigation, the general limits to cellular automata are ascertained-these methods are not designed with lattice percolation properties in mind and resulting models depend, often critically, on arbitrarily chosen neighbourhoods. We embark on the development of new and more flexible methodologies. Rather than treating local and global dynamics as separate entities, we combine them. Our methods are responsive to percolation, and are designed around the following principles: 1) Inclusive search provides an optimal path between a pedestrian origin and destination. 2) Dynamic boundaries protect search and are based on percolation probabilities, calculated from local density regimes. In this way, more robust dynamics are achieved. Simultaneously, longer-range behaviours are also specified. 3) Network-level dynamics further relax the constraints of lattice percolation and allow a wider range of pedestrian interactions. Having defined our methods, we demonstrate their usefulness by applying them to lane-formation and evacuation scenarios. Results reproduce the general patterns found in real crowds. We then turn to evolution. This preliminary work is intended to motivate future research in the field of Evolutionary Architecture. We develop a genotype-phenotype mapping, which produces complex architectures, and demonstrate the use of a crowd-flow model in a phenotype-fitness mapping. We discuss results from evolutionary simulations, which suggest that obstacles may have some beneficial effect on crowd evacuation. We conclude with a summary, discussion of methodological limitations, and suggestions for future research

From mindless masses to small groups: Conceptualizing collective behavior in crowd modeling.

Computer simulations are increasingly used to monitor and predict behavior at large crowd events, such as mass gatherings, festivals and evacuations. We critically examine the crowd modeling literature and call for future simulations of crowd behavior to be based more closely on findings from current social psychological research. A systematic review was conducted on the crowd modeling literature (N = 140 articles) to identify the assumptions about crowd behavior that modelers use in their simulations. Articles were coded according to the way in which crowd structure was modeled. It was found that 2 broad types are used: mass approaches and small group approaches. However, neither the mass nor the small group approaches can accurately simulate the large collective behavior that has been found in extensive empirical research on crowd events. We argue that to model crowd behavior realistically, simulations must use methods which allow crowd members to identify with each other, as suggested by self-categorization theory

Validated force-based modeling of pedestrian dynamics

This dissertation investigates force-based modeling of pedestrian dynamics. Having the quantitative validation of mathematical models in focus principle questions will be addressed throughout this work: Is it manageable to describe pedestrian dynamics solely with the equations of motion derived from the Newtonian dynamics? On the road to giving answers to this question we investigate the consequences and side-effects of completing a force-based model with additional rules and imposing restrictions on the state variables. Another important issue is the representation of modeled pedestrians. Does the geometrical shape of a two dimensional projection of the human body matter when modeling pedestrian movement? If yes which form is most suitable? This point is investigated in the second part while introducing a new force-based model. Moreover, we highlight a frequently underestimated aspect in force-based modeling which is to what extent the steering of pedestrians influences their dynamics? In the third part we introduce four possible strategies to define the desired direction of each pedestrian when moving in a facility. Finally, the effects of the aforementioned approaches are discussed by means of numerical tests in different geometries with one set of model parameters. Furthermore, the validation of the developed model is questioned by comparing simulation results with empirical data

EVAQ: Person-Specific Evacuation Simulation for Large Crowd Egress Analysis

Timely crowd evacuation in life-threatening situations such as fire emergency or terrorist attack is a significant concern for authorities and first responders. An individual’s fate in this kind of situation is highly dependent on a host of factors, especially (i) agent dynamics: how the individual selects and executes an egress strategy, (ii) hazard dynamics: how hazards propagate (e.g., fire and smoke spread, lone wolf attacker moves) and impair the surrounding environment with time, (iii) intervention dynamics: how first responders intervene (e.g., firefighters spread repellents) to recover environment. This thesis presents EVAQ, a simulation modeling framework for evaluating the impact of these factors on the likelihood of survival in an emergency evacuation. The framework captures the effect of personal traits and physical habitat parameters on occupants’ decision-making. In particular, personal (i.e., age, gender, disability) and interpersonal (i.e., agent-agent interactions) attributes, as well as an individual’s situational awareness are parameterized in a deteriorating environment considering different exit layouts and physical constraints. Further, the framework supports a variety of hazard propagation schemes (e.g., fire spreading in a given direction, lone wolf attacker targeting individuals), and intervene schemes (e.g., firefighters spreading repellents, police catch the attacker) to support a wide range of emergency evacuation scenarios. The application of EVAQ to crowd egress planning in an airport terminal and a shopping mall in the fire emergency is presented in this thesis, and results are discussed. Result shows that the likelihood of survival decreases with a decrease in availability of the nearest exits and a resulting increase in congestions in the environment. Also, it is observed that the incorporation of group behavior increases the likelihood of survival for children, as well as elderly and disabled people. In addition, several verifications and validation tests are performed to assess the reliability and integrity of EVAQ in comparison with existing evacuation modeling tools. As personalized sensing and information delivery platforms are becoming more ubiquitous, findings of this work are ultimately sought to assist in developing and executing more robust and adaptive emergency mapping and evacuation plans, ultimately aimed at promoting people’s lives and wellbeing

Optimizing Stadium Evacuation by Integrating Geo-Computation and Affordance Theory

The purpose of this project was to optimize football stadium evacuation time by integrating geo-computation with affordance theory from perceptual psychology to account for evacuee characteristics: age, gender, physical fitness, alcohol consumption, and prior experience attending football games at The University of Southern Mississippi (USM), evacuating from large, outdoor public places, and with hazard events. According to the Uniting and Strengthening America by Providing Appropriate Tools Required to Intercept and Obstruct Terrorism (USA PATRIOT) Act, football stadiums are part of the country’s critical infrastructure warranting special government protection. Evacuation modeling was identified as an important component of game day emergency preparation. Research shows that: (1) the age, gender, and physical fitness of an individual impact his/her locomotion speed; (2) evacuation route choice is influenced by the perception of its safety and effectiveness; and (3) prior evacuation experience affects evacuation decision-making processes. By including these factors, this research, conducted at USM’s M.M. Roberts Stadium, represents the reality of evacuee movement and behaviors that influence stadium evacuation time. A questionnaire-based survey was administered to game attendees prior to a USM home game to gather evacuee attribute data that influenced locomotion speed. This data, plus secondary spatial data, were used in an agent-based model to model individual evacuee movement. The time required for all evacuees to exit the stadium and campus was 165.16 minutes. This time was significantly shorter than evacuation times from the same location using non-location-specific evacuee locomotion speeds, suggesting that use of local data is vital to accurately depicting evacuation time. The findings also indicated that age and gender were the two main factors that impacted locomotion speeds. The main contributions of this study were: (1) optimizing evacuation time by using location-specific locomotion speeds and (2) providing insights into how evacuees’ physical and mental health influence their evacuation decision-making processes. The U.S. government and sports management industry could use these findings to increase game day safety and security. Due to the spatio-temporal nature of evacuation modeling and perceptions of evacuees that impact evacuation time, this research contributed to the fields of geography, computer science, sport management, psychology, and emergency management