Pedestrian Evacuation: Vulnerable Group Member Influence on the Group Leaders’ Decision-Making and the Impact on Evacuation Time

As pedestrian evacuations of buildings, outdoor venues, and special events occur, dynamic interactions between pedestrians and vehicles during egress are possible. To model pedestrian and vehicle evacuations, simulation models have evolved to incorporate more realistic crowd characteristics and behaviors to provide improved results. Past studies using modeling and simulation, specifically agent-based modeling, have explored pedestrian behaviors such as decision-making, navigation within a virtual environment, group formations, intra-group interactions, inter-group dynamics, crowd behaviors such as queuing and herding, and pedestrianvehicle interactions. These studies have led to relevant insights helpful to improving the accuracy of evacuation times for normal and emergency egress for preparedness and management purposes. As evacuating crowds are composed of individual pedestrians and social or familial groups, this project contributes to the study of pedestrian evacuation by exploring the incorporation of a subgroup not often considered in this area. Vulnerable individuals, such as the physically disabled, elderly, and children, can change the decision-making dynamic of a group leader while evacuating to safety. Current agent-based simulation models explore the intra- and inter- action and the effects on evacuation times; however, the vulnerable group members\u27 influence is neglected. This project presents enhancements to pedestrian evacuations with vehicle interaction using an agent-based simulation model that includes the presence of vulnerable group members and their impact on decision-making and evacuation times. This project explores how changing behaviors due to the presence of vulnerable group members can collectively cause delays and increase evacuation times. Utilizing verification and validation methods, the credibility and reliability of the simulation model and its results are increased. The results show that the group leaders\u27 decision-making differs when leading a vulnerable group versus a non-vulnerable group. Also, evacuation times increase with increased percentages of vulnerable groups within an evacuating crowd. A simulation tool can be utilized by end-users to explore specific evacuation scenarios in preparation for upcoming events and glean insight into how evacuation times may vary with differing crowd population sizes and compositions. Including vulnerable pedestrians in simulation models for evacuations would improve output accuracy and ultimately improve event training and preparation for future evacuations

Interactive Motion Planning for Multi-agent Systems with Physics-based and Behavior Constraints

Man-made entities and humans rely on movement as an essential form of interaction with the world. Whether it is an autonomous vehicle navigating crowded roadways or a simulated pedestrian traversing a virtual world, each entity must compute safe, effective paths to achieve their goals. In addition, these entities, termed agents, are subject to unique physical and behavioral limitations within their environment. For example, vehicles have a finite physical turning radius and must obey behavioral constraints such as traffic signals and rules of the road. Effective motion planning algorithms for diverse agents must account for these physics-based and behavior constraints. In this dissertation, we present novel motion planning algorithms that account for constraints which physically limit the agent and impose behavioral limitations on the virtual agents. We describe representational approaches to capture specific physical constraints on the various agents and propose abstractions to model behavior constraints affecting them. We then describe algorithms to plan motions for agents who are subject to the modeled constraints. First, we describe a biomechanically accurate elliptical representation for virtual pedestrians; we also describe human-like movement constraints corresponding to shoulder-turning and side-stepping in dense environments. We detail a novel motion planning algorithm extending velocity obstacles to generate collisionfree paths for hundreds of elliptical agents at interactive rates. Next, we describe an algorithm to encode dynamics and traffic-like behavior constraints for autonomous vehicles in urban and highway environments. We describe a motion planning algorithm to generate safe, high-speed avoidance maneuvers using a novel optimization function and modified control obstacle formulation, and we also present a simulation framework to evaluate driving strategies. Next, we present an approach to incorporate high-level reasoning to model the motions and behaviors of virtual agents in terms of verbal interactions with other agents or avatars. Our approach leverages natural-language interaction to reduce uncertainty and generate effective plans. Finally, we describe an application of our techniques to simulate pedestrian behaviors for gathering simulated data about loading, unloading, and evacuating an aircraft.Doctor of Philosoph

Multi-Scale Evacuation Models To Support Emergency And Disaster Response

Evacuation is a short-term measure to mitigate human injuries and losses by temporarily relocation of exposed population before, during, or after disasters. With the increasing growth of population and cities, buildings and urban areas are over-populated which brings about safety issues when there is a need for emergency evacuation. In disaster studies, simulation is widely used to explore how natural hazards might evolve in the future, and how societies might respond to these events. Accordingly, evacuation simulation is a potentially helpful tool for emergency responders and policy makers to evaluate the required time for evacuation and the estimated number and distribution of casualties under a disaster scenario. The healthcare system is an essential subsystem of communities which ensures the health and well-being of their residents. Hence, the resilience of the healthcare system plays an essential role in the resilience of the whole community. In disasters, patient mobility is a major challenge for healthcare systems to overcome. This is where the scientific society enters with modeling and simulation techniques to help decision-makers. Hospital evacuation simulation considering patients with different mobility characteristics, needs, and interactions, demands a microscopic modeling approach, like Agent-Based Modeling (ABM). However, as the system increases in size, the models become highly complex and intractable. Large-scale complex ABMs can be reduced by reformulating the micro-scale model of agents by a meso-scale model of population densities and partial differential equations, or a macro-scale model of population stocks and ordinary differential equations. However, reducing the size and fidelity of microscopic models to meso- or macro-scale models implies certain drawbacks. This dissertation contributes to the improvement of large-scale agent-based evacuation simulation and multi-scale hospital evacuation models. For large-scale agent-based models, application of bug navigation algorithms, popular in the field of robotics, is evaluated to improve the efficiency of such models. A candidate bug algorithm is proposed based on a performance evaluation framework, and its applicability and practicability are demonstrated by a real-world example. For hospital evacuation simulation, crowd evacuation considering people with different physical and mobility characteristics is modeled on three different scales: microscopic (ABM), mesoscopic (fluid dynamics model), and macroscopic (system dynamics model). Similar to the well-known Predator-Prey model, the results of this study show the extent to which macroscopic and mesoscopic models can produce global behaviors emerging from agents’ interactions in ABMs. To evaluate the performance of these multi-scale models, the evacuation of the emergency department at Johns Hopkins University is simulated, and the outputs and performance of the models are compared in terms of implementation complexity, required input data, provided output data, and computation time. It is concluded that the microscopic agent-based model is recommended to hospital emergency planners for long-term use such as evaluating different emergency scenarios and effectiveness of different evacuation plans. On the other hand, the macroscopic system dynamics model is best to be used as a simple tool (like an app) for rapid situation assessment and decision making in case of imminent events. The fluid dynamics model is found to be suitable only for studying crowd dynamics in medium to high densities, but it does not offer any competency as an evacuation simulation tool

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U tekstu je dan popis radova koji su objavljeni u stranim časopisima

Efficient People Movement through Optimal Facility Configuration and Operation

There are a variety of circumstances in which large numbers of people gather and must disperse. These include, for example, carnivals, parades, and other situations involving entrance to or exit from complex buildings, sport stadiums, commercial malls, and other type of facilities. Under these situations, people move on foot, commonly, in groups. Other circumstances related to large crowds involve high volumes of people waiting at transportation stations, airports, and other types of high traffic generation points. In these cases, a myriad of people need to be transported by bus, train, or other vehicles. The phenomenon of moving in groups also arises in these vehicular traffic scenarios. For example, groups may travel together by carpooling or ridesharing as a cost-saving measure. The movement of significant numbers of people by automobile also occurs in emergency situations, such as transporting large numbers of carless and mobility-impaired persons from the impacted area to shelters during evacuation of an urban area. This dissertation addresses four optimization problems on the design of facilities and/or operations to support efficient movement of large numbers of people who travel in groups. A variety of modeling approaches, including bi-level and nonlinear programming are applied to formulate the identified problems. These formulations capture the complexity and diverse characteristics that arise from, for example, grouping behavior, interactions in decisions by the system and its users, inconvenience constraints for passengers, and interdependence of strategic and operational decisions. These models aim to provide: (1) estimates of how individuals and groups distribute themselves over the network in crowd situations; (2) an optimal configuration of the physical layout to support large crowd movement; (3) an efficient fleet resource management tool for ridesharing services; and (4) tools for effective regional disaster planning. A variety of solution algorithms, including a meta-heuristic scheme seeking a pure-strategy Nash equilibrium, a multi-start tabu search with sequential quadratic programming procedure, and constraint programming based column generation are developed to solve the formulated problems. All developed models and solution methodologies were employed on real-world or carefully created fictitious examples to demonstrate their effectiveness

3D GEOSPATIAL INDOOR NAVIGATION FOR DISASTER RISK REDUCTION AND RESPONSE IN URBAN ENVIRONMENT

Disaster management for urban environments with complex structures requires 3D extensions of indoor applications to support better risk reduction and response strategies. The paper highlights the need for assessment and explores the role of 3D geospatial information and modeling regarding the indoor structure and navigational routes which can be utilized as disaster risk reduction and response strategy. The reviewed models or methods are analysed testing parameters in the context of indoor risk and disaster management. These parameters are level of detail, connection to outdoor, spatial model and network, handling constraints. 3D reconstruction of indoors requires the structural data to be collected in a feasible manner with sufficient details. Defining the indoor space along with obstacles is important for navigation. Readily available technologies embedded in smartphones allow development of mobile applications for data collection, visualization and navigation enabling access by masses at low cost. The paper concludes with recommendations for 3D modeling, navigation and visualization of data using readily available smartphone technologies, drones as well as advanced robotics for Disaster Management

Applying Situational Crime Prevention to Terrorism Against Stadiums

According to recent studies, there has been increasing concern of terrorist threats to U.S. stadiums. The research problem is that existing U.S. stadium policies, procedures, and plans do not adequately address evacuation of special populations in the event of a terrorist threat. There is a particular concern regarding the adequacy of existing stadium evacuation plans for patrons with special needs. In the current study there were three research questions examining the organizational deficiencies and best practices of stadium evacuation plans currently in place to respond to terrorist threats How situational crime prevention (SCP) can help in the identification of deficiencies and best practices and what strategic deficiencies exist in current practices regarding the evacuation of special populations procedures at major sporting venues. Using a general qualitative design, interviews were conducted with 20 stadium operators, consultants, security managers, or stadium security staff members. The SCP approach was used to explore identification of deficiencies and best practices in stadium evacuation plans in the event of a terrorist attack. The results indicated that existing U.S. stadiums need to improve training, communication, and planning for evacuation of all patrons, including patrons with special needs. The results also indicated best practices that align with the SCP strategy of increased risk, the SCP technique that includes hard interventions, and SCP Pillar 2, Weapons. Ineffective stadium evacuation can result in unnecessary injury and loss of life. Implications for positive social change include improved stadium evacuation plans to assure patron safety in the event of a terrorist attack

スケーラブルなマルチエージェント大都市域避難行動シミュレータの自動車の考慮に重点をおいた拡張と適用

学位の種別: 課程博士審査委員会委員 : (主査)東京大学准教授 マッデゲダラ ラリス, 東京大学教授 堀 宗朗, 東京大学教授 大口 敬, 東京大学教授 堀田 昌英, 東京大学准教授 市村 強, 東京大学准教授 柳澤 大地University of Tokyo(東京大学