Passive and active navigation of virtual environments vs. traditional printed evacuation maps: A comparative evaluation in the aviation domain

Printed maps are the most common tool to prepare people for emergency evacuation in contexts such as public buildings or transportation. Unfortunately, they are poorly understood and often ignored by people. Virtual environments (VEs) could be a more effective method to support people in acquiring spatial knowledge about the real-world environment to evacuate. This paper pursues three main goals. First, we propose a VE-based tool to support spatial knowledge acquisition for evacuation purposes, using aviation as a real-world domain in which such knowledge is crucial for passengers’ safety. Second, we study in detail one of the VE design choices (active or passive navigation), comparing a version of our tool in which users navigate by actively controlling their position with another version in which users are passively led along pre-defined routes. Third, we contrast the two versions of the tool with the traditional, printed diagrammatic map provided to passengers by airlines. Results of our study show that the VE-based approach produces objectively better spatial knowledge when users are asked to pinpoint their assigned position in the environment, and that active navigation produces a performance improvement in a subsequent virtual evacuation. Moreover, the VE-based approach is perceived as more enjoyable, easier to comprehend and more effective than printed maps when active navigation is available.     

基于本体论的应急系统知识表示的研究

论文在对知识表示及国内外有关本体库研究的基础上,提出将知识表示方法中的框架与谓词逻辑相结合,作为本体知识的一种描述方法,去定义国防动员应急决策支持系统中通信内容的共享本体,给出基于OWL+RDF+XML的形式化描述。并利用本体对知识进行领域分类,同时对决策者的查询信息进行规范。     

Scalable evacuation routing in a dynamic environment

In emergency management, tools are needed so we can take the appropriate action at different stages of an evacuation. Recent wildfires in California showed how quickly a natural disaster can affect a large geographical area. Natural disasters can create unpredicted traffic congestion or can temporarily block urban or rural roads. Evacuating a large area in an emergency situation is not possible without prior knowledge of the road network and the ability to generate an efficient evacuation plan. An ideal evacuation routing algorithm should be able to generate realistic and efficient routes for each evacuee from the source to the closest shelter. It should also be able to quickly update routes as the road network changes during the evacuation. For example, if a main road is blocked during a flood, the evacuation routing algorithm should update the plan based on this change in the road network. In this article major works in evacuation routing have been studied and a new algorithm is developed that is faster and can generate better evacuation routes. Additionally, it can quickly adjust the routes if changes in the road network are detected. The new algorithm's performance and running time are reported.     

Decision support system for in-flight emergency events

Medical problems during flight have become an important issue as the number of passengers and miles flown continues to increase. The case of an incident in the plane falls within the scope of the healthcare management in the context of scarce resources associated with isolation of medical actors working in very complex conditions, both in terms of human and material resources. Telemedicine uses information and communication technologies to provide remote and flexible medical services, especially for geographically isolated people. Therefore, telemedicine can generate interesting solutions to the medical problems during flight. Our aim is to build a knowledge-based system able to help health professionals or staff members addressing an urgent situation by given them relevant information, some knowledge, and some judicious advice. In this context, knowledge representation and reasoning can be correctly realized using an ontology that is a representation of concepts, their attributes, and the relationships between them in a particular domain. Particularly, a medical ontology is a formal representation of a vocabulary related to a specific health domain. We propose a new approach to explain the arrangement of different ontological models (task ontology, inference ontology, and domain ontology), which are useful for monitoring remote medical activities and generating required information. These layers of ontologies facilitate the semantic modeling and structuring of health information. The incorporation of existing ontologies [for instance, Systematic Nomenclature Medical Clinical Terms (SNOMED CT)] guarantees improved health concept coverage with experienced knowledge. The proposal comprises conceptual means to generate substantial reasoning and relevant knowledge supporting telemedicine activities during the management of a medical incident and its characterization in the context of air travel. The considered modeling framework is sufficiently generic to cover complex medical situations for isolated and vulnerable populations needing some care and support services.     

Problems Associated with Evacuation from the Ship in Case of an Emergency Situation

The problems associated with evacuation of people from the ship in an emergency situation are analyzed, especially passenger ships are taken under consideration. The most dangerous accidents requiring evacuation are described. Marine accidents often occur as eliminating all of the hazards to human health and life is still impossible. In every case, the evacuation process from the ship must be taken under consideration. Evacuation route arrangement should provide the possibility of safe departure from danger areas for passengers and crew members. Evacuation routes designed for human interaction within the evacuation process and other important factors are reviewed. Additipnally, the method for seeking evacuation time as a function of initial distribution of passengers and evacuation routes choosing is suggested. A genetic algorithm will be used, whilst the calculated evacuation time is connected with a fitness function. Parameters of evacuation routes topology are coded as non-binary chromosomes. Genetic operators are fitted for such types of problems to avoid receiving infeasible solutions. The objective of the proposed method is to find the evacuation time in worse case scenarios.     

Extended route choice model based on available evacuation route set and its application in crowd evacuation simulation

In this study, we propose an extended route choice model based on an available evacuation route set to simulate the selection of pedestrians in selecting an appropriate route during evacuation in emergency situations. In this model, four parameters (i.e., distance to available route, length of available route, level of congestion in available route, and capacity of available exit) affect the route choice of the pedestrian and the evacuation route set. In this study, the evacuation route set is created and optimized by a modified social force model and a route learning method. Experimental results show that the extended model can effectively reproduce crowd behavior in an emergency situation, which can assist in analyzing emergency evacuation scenarios. Moreover, two important conclusions regarding increasing evacuation efficiency show that the proposed model is in line with real-world situations.     

Multi-agent ontology-based Web 2.0 platform for medical rehabilitation

Information technologies have played key roles in a wide range of medical settings such as hospital wards, operating rooms, emergency departments, and rehabilitation centers, rendering biomedical knowledge and data more accessible for human comprehension, comparison, analysis and communication. In this context, ontology has been recognized in the bioinformatics literature as a suitable technique for advancing knowledge and data representations in biomedicine. With the enhancement of automated reasoning and graphical visualizations, ontology-technology can assist human comprehensibility as well as mitigating the complexity inherent to this domain.Rehabilitation medicine has become an important part field in medicine, as distinct from preventive medicine, health care medicine and clinical medicine. In this article, we aim to address the ontological and epistemological issues of information services through the example of OntoRis, an ontology-based rehabilitation service OntoRis is designed to assist patients in acquiring actionable knowledge about his/her prescribed rehabilitation, and to expedite recovering through providing suggestions and advice drawn from evidence-based medicine. Moreover, OntoRis can also serve as an interactive learning platform for people who are interested in rehabilitation medicine.     

Agent-based simulation of affordance-based human behaviors in emergency evacuation

Complex cognitive processes corresponding to human control behaviors cannot be easily inferred using (1) a logical rule-based model, (2) a statistical model, or (3) an analytical predictive model. Predicting human behaviors in complex and uncertain environments like emergency evacuation is considered almost impossible (at least NP hard) in systems theory. In this paper, we explore simulating human behaviors using affordance-based finite state automata (FSA) modeling, based on the ecological concept of affordance theory. To this end, we introduce the conceptual and generic framework of affordance-based human behavior simulation developed through our previous work. Following the generic framework, formal simulation models of affordance-based human behaviors are developed, especially for emergency evacuation, to mimic perception-based dynamic human actions interacting with emergent environmental changes, such as fire. A “warehouse fire evacuation” case is used to demonstrate the applicability of the proposed framework. The human action planning algorithms in the simulation model are developed and implemented using the Adjusted Floor Field Indicators, which represent not only the evacuee’s prior knowledge of the floor layout but the perceivable information about dynamic environmental changes. The results of our simulation study verify that the proposed framework accurately simulates human fire evacuation behavior. The proposed framework is expected to capture the natural manner in which humans behave in emergency evacuation and enhance the simulation fidelity of analyses and predictions of perceptual human behaviors/responses in the systems by incorporating cognitive intent into human behavior simulations.     

Estimating the effects of mental disorientation and physical fatigue in a semi-panic evacuation

Understanding the impossibility of replicating a real panic emergency situation and experimenting human objects in such artificially created dangerous situation, this paper focuses on the evacuation of a heterogeneous population including people with disabilities in a semi-panic simulated situation in which people tend to hurry more than those in non-panic evacuation but exhibit less urgency than those in a panic emergency. Ultimately, we intend to estimate and quantify the effects of mental disorientation and physical fatigue on the average evacuation times of six different disability groups and the entire group in a simulated environment of a 24-story building. According to our experiments, mental disorientation due to sudden emotion escalation from the recognition of unexpected dangers increases the average evacuation times up to 25 percent depending on the complexity of evacuation routes of the simulated buildings. In addition, accumulated physical fatigue of human beings during the evacuation process could also significantly delay the evacuation time. Most of all, the impact magnitudes of these two main factors vary depending on the types of disabilities of individuals, insinuating the needs of developing evacuation plans and strategies for each group.     

基于本体的应急救援知识库构建及其应用

针对专家系统在应急救援领域应用中存在的知识表示及推理等问题,采用基于本体的知识表示方法与基于Jena的规则推理引擎,参考简单知识工程方法论与Jena规则语法建立一个高速公路应急救援本体与推理规则,实现本体知识库的推理。将该知识库应用于高速公路应急救援系统中,结果表明其具备解决实际问题的能力;有利于领域知识的共享与重用;促进了专家系统在高速公路应急救援领域的发展。     

Simulation-based evaluation of evacuation effectiveness using driving behavior sensitivity analysis

Worldwide, man-made or natural phenomena occasionally occur that create emergency conditions and require the evacuation of areas of different sizes and characteristics. Drivers’ behavior becomes a very important factor for the evacuation operations. This paper provides an analytical study of the effectiveness of evacuation according to drivers’ behavior, using the sensitivity analysis method. Collecting real-time data about this factor is a difficult to impossible task for large scale cases; therefore, traffic simulation is the most appropriate method for analysis. Our goal is to investigate how drivers’ aggressiveness affects the evacuation effectiveness. In this case, we used the AIMSUN traffic simulation model; the parameters of the driver behavior models are chosen through all-at-once sensitivity analysis of the parameters. This model is applied to different demand scenarios for well-defined parameters’ value ranges. This investigation produces estimated ranges of the evacuation duration and the number of evacuated people, both for a baseline “do-nothing” scenario, as well as the outcome of improvement actions. The sensitivity analysis results suggest that evacuation time can be significantly reduced by reversing the most congested links; furthermore, the use of a bus fleet would allow many more people to evacuate the danger zone timely, albeit with a small increase in minimum evacuation time. This methodology could be applicable to other emergency response scenarios, as it obviates the need for real-time data.     

An ontology for framing

Framing is the process of conceiving new situations which may change an organization's behaviour. These situations are often “wicked” in nature, and may be defined by reinterpreting the meaning of an organization's intent. A real-world case study is used to illustrate the framing process and derive an ontology for framing. A computer tool called FRAMER is described that implements the framing ontology and supports the framing process. A key feature of FRAMER is the ability for people to adapt and redefine knowledge representations as they articulate new theories, and extend existing theories, about an organization.     

Meta-relation and ontology closure in Conceptual Structure Theory

This paper presents an enhanced ontology formalization, combining previous work in Conceptual Structure Theory and Order-Sorted Logic. Most existing ontology formalisms place greater importance on concept types, but in this paper we focus on relation types, which are in essence predicates on concept types. We formalize the notion of ‘predicate of predicates’ as meta-relation type and introduce the new hierarchy of meta-relation types as part of the ontology definition. The new notion of closure of a relation or meta-relation type is presented as a means to complete that relation or meta-relation type by transferring extra arguments and properties from other related types. The end result is an expanded ontology, called the closure of the original ontology, on which automated inference could be more easily performed. Our proposal could be viewed as a novel and improved ontology formalization within Conceptual Structure Theory and a contribution to knowledge representation and formal reasoning (e.g., to build a query-answering system for legal knowledge).     

Crowdsourcing emergency data in non-operational cellular networks

In overloaded or partially broken (i.e., non-operational) cellular networks, it is imperative to enable communication within the crowd to allow the management of emergency and crisis situations. To this end, a variety of emerging short-range communication technologies available on smartphones, such as, Wi-Fi Direct, 3G/LTE direct or Bluetooth/BLE, are able to enable users nowadays to shape point-to-point communication among them. These technologies, however, do not support the formation of overlay networks that can be used to gather and transmit emergency response state (e.g., transfer the location of trapped people to nearby people or the emergency response guard). In this paper, we develop techniques that generate the k-Nearest-Neighbor (kNN) overlay graph of an arbitrary crowd that interconnects over some short-range communication technology. Enabling a kNN overlay graph allows the crowd to connect to its geographically closest peers, those that can physically interact with the user and respond to an emergency crowdsourcing task, such as seeing/sensing similar things as the user (e.g., collect videos and photos). It further allows for intelligent synthesis and mining of heterogeneous data based on the computed kNN graph of the crowd to extract valuable real-time information. We particularly present two efficient algorithms, namely Akin+ and Prox+, which are optimized to work on a resource-limited mobile device. We use Rayzit, a real-world crowd messaging framework we develop, as an example that operates on a kNN graph to motivate and evaluate our work. We use mobility traces collected from three sources for evaluation. The results show that Akin+ and Prox+ significantly outperform existing algorithms in efficiency, even under a skewed distribution of users.     

Modeling emergency evacuation of individuals with disabilities (exitus): An agent-based public decision support system

In this paper, we present a public decision support system (DSS) distinguished from various DSSs in the private business sector in terms of its ownership, data scarcity, and beneficiaries. In particular, our system is intended to play a vital role in assessing and optimizing emergency response plans for rare but catastrophic events such as the September 11th attacks. While taking an agent-based microscopic simulation approach in a hierarchical framework, we used our model to estimate the effectiveness of alternative evacuation strategies to support emergency response planning as a part of business continuity planning for all private business organizations. The presented model is unique because it considers individuals with disabilities explicitly in terms of speed, ability to negotiate the environment, and normalcy bias depending on type of disability. It is also capable of classifying the environment in terms of accessibility characteristics encompassing various conditions which have been shown to have a disproportionate effect upon the behavior of individuals with disabilities during an emergency.Through a series of simulation experiments, our system identified specific locations (e.g., the NW landing) on the 3rd floor of the test bed building as possible bottleneck spots under certain conditions (e.g., the sharp increase in individuals with disabilities among residents). This way, our system provides the architect with tools to test the structure’s design to determine how well it meets the identified requirements for emergency evacuation to accommodate this shifting demographic. In particular, our system strongly demonstrated the effectiveness of new emergency evacuation strategies for individuals with disabilities such as assisted evacuations which allows other healthy people to play more active roles compared to traditional strategies in which individuals with disabilities are helplessly waiting for assistants such as fire fighters at the designated area. Our system also revealed that people using wheelchairs and those with lower stamina were at the greatest risk. People with lower stamina such as the elderly, people with chronic health conditions, or those with temporary injuries are at a greater risk mainly because they are not easily identifiable. Ultimately, the proposed DSS system can be used to inform public policy professionals of more effective, evidence-based evacuation planning and environmental design methods based on a better understanding of the behavior of individuals with disabilities.     

Efficient computation of evacuation routes on a three-dimensional geometric network

We consider a real-time emergency evacuation problem that seeks to compute a set of rapid evacuation routes in a building. Given a three-dimensional geometric structure of the evacuation network, an emergency evacuation route is a sequence of movements of people away from the threat or actual occurrence of a hazard (such as a fire, a hidden bomb) to a safe exit in the network. In such a network each room/crossing/exit in the building is designated as a node and the corridors/staircases/links between the rooms are edges. The evacuation times assigned to the edges are normally distributed random variables. This stochastic routing problem subject to deadline constraints is NP-hard. We provide a new pseudo-polynomial-time dynamic programming algorithm to solve this problem. Based on this algorithm, we construct two types of approximation algorithm, namely a fully polynomial-time approximation scheme providing “almost-optimal” solutions and a fully polynomial-time approximately feasible scheme yielding a best “almost feasible” solution. We present a case study and results of computational experiments to illustrate the working and efficacy of the proposed solution methods, respectively.     

高铁车厢内部紧急情况下人员疏散仿真研究

在引入元胞自动机理论的基础上,模拟分析了紧急情况下人员生理及心理的不同对疏散过程的影响,通过人员动态调整自身行为,并引入人员竞争力,对人员疏散过程建立模型。在疏散过程中,根据存在着一定程度的外部干扰因素,提出疏散干扰度概念。计算机仿真的结果表明,考虑人员竞争力,以及出口疏散干扰的问题,可以更加真实地模拟人员紧急疏散过程和疏散状况。     

Decision making with a fuzzy ontology

Knowledge mobilisation is a transition from the prevailing knowledge management technology that has been widely used in industry for the last 20?years to a new methodology and some innovative methods for knowledge representation, formation and development and for knowledge retrieval and distribution. Knowledge mobilisation aims at coming to terms with some of the problems of knowledge management and at the same time to introduce new theory, new methods and new technology. More precisely, this paper presents an outline of a fuzzy ontology as an enhanced version of classical ontology and demonstrates some advantages for practical decision making. We show that a number of soft computing techniques, e.g. aggregation functions and interval valued fuzzy numbers, will support effective and practical decision making on the basis of the fuzzy ontology. We demonstrate the knowledge mobilisation methods with the construction of a support system for finding the best available wine for a number of wine drinking occasions using a fuzzy wine ontology and fuzzy reasoning methods; the support system has been implemented for a Nokia N900 smart phone.     

Investigating the influence of route turning angle on compliance behaviors and evacuation performance in a virtual-reality-based experiment

Route turning is one of the most essential and ubiquitous physical features in the complex building environment. Under the influence of route turning, evacuees’ approaching perspective to an emergency sign could vary, affecting their information perception and behavioral compliance during the evacuation. Although conventional simulation methods assess the effectiveness of the emergency sign in the visible region, they fail to consider evacuees’ wayfinding behaviors and interaction with the emergency sign. It remains unclear whether the route turning angle affects evacuees’ compliance for detecting and responding to the emergency sign. To investigate such an influence, a virtual-reality-based method for assessing human evacuation behaviors in building fire evacuations was proposed. In this study, two evacuation routes with different turning angles in a shopping mall were created and implemented in a virtual-reality environment, and 67 subjects participated in the immersive virtual-reality-based experiment. All participants took the two routes to find the nearest exit for evacuation in a fire event, aiming to evaluate the effect of the route turning angle on the evacuation process. The participants were asked to complete a questionnaire at the end of the experiment. Next, statistical analyses were conducted on evacuation results, information perception, and evacuation performance of the participants. The results indicated the route turning angle significantly affected participants' behavioral compliance with emergency signs. The results also suggested the route turning angle was influential on participants’ information perception and evacuation performance. Besides, a significant effect on rotation change, wayfinding pause, and speed deviation were observed. This study validates the effectiveness of investigating evacuees’ interaction with emergency signs using virtual-reality technology and has potential implications for complex building path planning and evacuation simulation modeling.     

基于Agent的应急疏散模型研究

根据突发事件出现的等级,选择安全区域,并采用适当的疏散方式,选择受灾区域的周边安全区域作为避难所;通过分析影响应急情况下人员选择目的地的因素,对人员疏散行为直观分析并结合人机功效评估,对疏散行为规范,建立基于Agent的应急疏散人员避难所选择模型。通过设定可能影响人员疏散的多种可能因素,该模型能够比较真实地模拟紧急情况下的人员疏散状态。仿真过程与实际情况相似,方法可广泛用于人员应急疏散过程分析研究。