A hybrid hierarchical agent-based simulation approach for buildings indoor layout evaluation based on the post-earthquake evacuation

In the aftermath of severe earthquakes, building occupants evacuation behaviour is a vital indicator of the performance of an indoor building design. However, earthquake evacuation has been systematically neglected in the current building design practice. Arguably, one of the primary reasons for this is that post-earthquake evacuation behaviour is complex and distinct from all other types of evacuation behaviours such as fire. Thus, a comprehensive approach to considering the integration of human evacuation behaviour and a building's indoor layout design, mainly focused on non-structural damage, has been consistently neglected in the literature. In this paper, a hierarchical hybrid Agent-Based Model (ABM) framework integrated with a Cellular Automata (CA) and a 2D Building Information Model (BIM) damage visualisation to consider an approximation of non-structural damage has been developed. The proposed ABM incorporates learning mechanisms and human psychological aspects influencing evacuees' utility during the navigation process. The proposed approach was verified by comparing the results to previous real-life post-earthquake evacuation data and a “model to model” comparison of results from the existing relevant studies. The model prototype was successfully tested to simulate the pedestrian evacuation process from one floor of the new engineering building at The University of Auckland, New Zealand. The proposed simulation approach has been carried out for two different internal layout design alternatives where five population sizes are evacuated through different scenarios. The outputs from this study can be used to improve the design's compatibility of the building's indoor layout with the occupants' post-earthquake evacuation behaviour.     

An immersive virtual reality serious game to enhance earthquake behavioral responses and post-earthquake evacuation preparedness in buildings

Enhancing the earthquake behavioral responses and post-earthquake evacuation preparedness of building occupants is beneficial to increasing their chances of survival and reducing casualties after the mainshock of an earthquake. Traditionally, training approaches such as seminars, posters, videos or drills are applied to enhance preparedness. However, they are not highly engaging and have limited sensory capabilities to mimic life-threatening scenarios for the purpose of training potential participants. Immersive Virtual Reality (IVR) and Serious Games (SG) as innovative digital technologies can be used to create training tools to overcome these limitations. In this study, we propose an IVR SG-based training system to improve earthquake behavioral responses and post-earthquake evacuation preparedness. Auckland City Hospital was chosen as a case study to test our IVR SG training system. A set of training objectives based on best evacuation practice has been identified and embedded into several training scenarios of the IVR SG. Hospital staff (healthcare and administrative professionals) and visitors were recruited as participants to be exposed to these training scenarios. Participants’ preparedness has been measured along two dimensions: 1) Knowledge about best evacuation practice; 2) Self-efficacy in dealing with earthquake emergencies. Assessment results showed that there was a significant knowledge and self-efficacy increase after the training. In addition, participants acknowledged that it was easy, helpful, and engaging to learn best evacuation practice knowledge through the IVR SG training system.     

An intelligent simulation system for earthquake disaster assessment

This paper presents an intelligent simulation system for an earthquake disaster assessment system based on a development platform of a Geographic Information System (GIS) and Artificial Intelligence (AI). This system is designed to identify the weakness of the structure and infrastructure system in pre-earthquake conditions, quickly assess earthquake damage and make an intelligent emergency response for the public and government during the earthquake and post-earthquake. The system includes the following functions: intelligent seismic hazard assessment, earthquake damage and loss evaluation, optimizing emergency response and post-earthquake recovering plan. The principle, design criteria, structure, functions and test results of this system are described in this paper. Based on its functional characteristics, this system is composed of four parts: an information database, analytical modules, an intelligent decision-making sub-system and a friendly user interface. There are 132 coverages and 78 analytical modules included in the information database and analytical modules. With this system, seismic disaster mitigation strategies can be verified during a pre-earthquake, and be executed at the time of an earthquake and post-earthquake; the earthquake resisting capacities for an entire city and all of its communities can be greatly enhanced. To check its reliability and its efficiency, this system has been tested based on a scenario earthquake event in one city, and the related results have also been given in this paper. At the present, this system has been installed and used in Daqing City, China. After running for almost 10 years, this system has successfully been used in rehearsing of seismic disaster mitigation and post-earthquake emergency response. Simultaneously, an optimizing aseismic retrofitting plan in Daqing City has been executed based on results from this system.     

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.     

集成环境下建筑内人员的疏散模拟

针对建筑内人员疏散的问题,提出集成模拟框架,确立面向计算机辅助设计(CAD)图纸的疏散效率评估流程.基于地理信息系统(GIS)技术,实时分析场景要素的空间分布特征,模拟人员对外部环境的认知与交互.应用虚拟现实(VR)技术对建筑布局及人员行为加以表现,基于Client-Server机制实现多视图集成.应用实例表明,CAD...     

Enhancing a tsunami evacuation simulation for a multi-scenario analysis using parallel computing

The numerical investigation of tsunami evacuation is becoming a major way to assess the potential evacuation risks and consider countermeasures, but it has been mostly limited to GIS-based static analysis or macroscopic agent-based modelling due to the costs of large-scale simulations. In this paper, we propose a simplified force-based evacuation simulation model and an easy-to-implement parallelization strategy for a large-scale microscopic tsunami evacuation simulation and demonstrate its applications in an actual urban environment. First, the simulation performance was verified and validated against experimental and observational results regarding basic pedestrian movement. The test results qualitatively and quantitatively showed good agreement with real pedestrian movements. The model was then applied to a case of tsunami evacuations in Kesennuma City, where the 2011 Tohoku tsunami caused devastating damage. The model was successfully scaled up to provide urban-scale characterization. In this application, the developed simulator was implemented by a hybrid MPI/OpenMP parallelized computing technique. By utilizing the proposed model with parallel computing, we achieved an urban-scale microscopic evacuation simulation five times faster than real-time and a stochastic simulation to evaluate the uncertainty in the evacuation simulation.     

Information modeling of earthquake-damaged reinforced concrete structures

Accurate and reliable information about buildings can greatly improve post-earthquake responses, such as search and rescue, repair and recovery. Building Information Modeling (BIM), rapid scanning and other assessment technologies offer the opportunity not only to retrieve as-built information but also to compile as-damaged models. This research proposes an information model to facilitate the data flow for post-earthquake assessment of reinforced concrete structures. The schema development was based on typical damage modes and the existing Industry Foundation Class (IFC) schema. Two examples of damaged structures from recent earthquake events, compiled using an experimental damage modeling software, illustrate the use of the data model. The model introduces two new classes, one to represent segments of building elements and the other to model the relationships between segments and cracks. A unique feature is the ability to model the process of damage with a binary tree structure. Methods for exporting as-damaged instance models using IFC are also discussed.     

A comparative study of evacuation strategies for people with disabilities in high-rise building evacuation

This paper presents new evacuation strategies for a heterogeneous population in high-rise building environments and compares them with traditional simultaneous evacuation strategy. To do so, we first define the maximum comfortable structural capacity of the building as the number of people that can be evacuated without heavy congestion, and estimate it based on flow rate and move frequency ratio. Then we present several evacuation strategies to efficiently evacuate heterogeneous residents at the maximum comfortable structural capacity. The simulation results for a 24-story building suggest several implications for emergency planners. First, we find that a vertically phased evacuation strategy that varies delay times by physical location, is not useful for the simulated building. Second, a phased evacuation strategy that applies a fixed evacuation delay to residents with wheelchairs reduces the aggregated evacuation times, but delaying evacuations of a specific group of individuals may not be ethical or accepted. Finally, evacuation strategies that allows residents with wheelchairs to use elevators are effective, suggesting that emergency administrators should assess whether elevators in their buildings are appropriate for evacuation purposes with appropriate electric controls, electric power, and fire and smoke protection.     

Crowd evacuation simulation using active route choice model based on human characteristics

Modern buildings have become larger in scale and function, and the complexity has also increased considerably. For these reasons, there are more difficulties in evacuation and rescue when an emergency occurs, so effective evacuation methods and risk should be predicted and applied to building design, safety training, and education. We have developed an active route choice model based on human body organs and characteristics that detects risks and route conditions, communicates with neighboring occupants, determines the bottleneck point, and selects evacuation routes according to each occupant's personal characteristics. In this study, we introduce the implementation process and characteristics of the active route choice model, and by applying the model to the occupants, we compared the evacuation times according to the route condition, number of occupants, and corridor width in a virtual environment. We believe that realistic and valid results can be obtained by applying the active route choice model in crowd evacuation simulation.     

Rapid entropy-based detection and properties measurement of concrete spalling with machine vision for post-earthquake safety assessments

The current procedures in post-earthquake safety and structural assessment are performed manually by a skilled triage team of structural engineers/certified inspectors. These procedures, and particularly the physical measurement of the damage properties, are time-consuming and qualitative in nature. This paper proposes a novel method that automatically detects spalled regions on the surface of reinforced concrete columns and measures their properties in image data. Spalling has been accepted as an important indicator of significant damage to structural elements during an earthquake. According to this method, the region of spalling is first isolated by way of a local entropy-based thresholding algorithm. Following this, the exposure of longitudinal reinforcement (depth of spalling into the column) and length of spalling along the column are measured using a novel global adaptive thresholding algorithm in conjunction with image processing methods in template matching and morphological operations. The method was tested on a database of damaged RC column images collected after the 2010 Haiti earthquake, and comparison of the results with manual measurements indicate the validity of the method.     

Advancing post-earthquake structural evaluations via sequential regression-based predictive mean matching for enhanced forecasting in the context of missing data

After an earthquake, every damaged building needs to be properly evaluated in order to determine its capacity to withstand aftershocks as well as to assess safety for occupants to return. These evaluations are time-sensitive as the quicker they are completed, the less costly the disaster will be in terms of lives and dollars lost. In this direction, there is often not sufficient time or resources to acquire all information regarding the structure to do a high-level structural analysis. The post-earthquake damage survey data may be incomplete and contain missing values, which delays the analytical procedure or even makes structural evaluation impossible. This paper proposes a novel multiple imputation (MI) approach to address the missing data problem by filling in each missing value with multiple realistic, valid candidates, accounting for the uncertainty of missing data. The proposed method, called sequential regression-based predictive mean matching (SRB-PMM), utilizes Bayesian parameter estimation to consecutively infer the model parameters for variables with missing values, conditional based on the fully observed and imputed variables. Given the model parameters, a hybrid approach integrating PMM with a cross-validation algorithm is developed to obtain the most plausible imputed data set. Two examples are carried out to validate the usefulness of the SRB-PMM approach based on a database including 262 reinforced concrete (RC) column specimens subjected to earthquake loads. The results from both examples suggest that the proposed SRB-PMM approach is an effective means to handle missing data problems prominent in post-earthquake structural evaluations.     

贪心选择在地铁站内行人疏散中的应用

大型室内场所空间布局较为复杂(如地铁站), 人群的高密度聚集往往存在一些潜在的风险. 本文在分析国内外人群快速疏散研究现状的基础上, 提出了一种基于贪心选择的行人疏散方法. 该方法以地铁站内复杂场景作为研究背景: 首先, 针对地铁站内的行人的行动轨迹难以获取问题, 本文利用地铁站内行人真实出站数据, 基于元胞自动机, 构建了行人疏散轨迹半仿真模型, 并利用实际流量数据优化该半仿真模型; 其次, 基于该轨迹模型, 为了满足高动态场景中的实时性, 采用复杂度较低的贪心选择策略分配最优疏散出口; 最后, 以杭州武林广场地铁站为例, 使用真实出站数据设计对比实验, 验证行人轨迹模型的有效性以及出口分配方法的性能. 结果表明, 本文所提出的行人轨迹模型能够较好的模拟行人的轨迹, 仿真中各出口疏散人数同真实出站数据拟合程度的可决系数R2达到了0.67. 相较于最短路径和最短时间出口分配方法, 本文所提出的方法在整体疏散效率上分别提高了27.2%和16.5%.     

A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations

Many computational tools for the simulation and design of emergency evacuation and egress are now available. However, due to the scarcity of human and social behavioral data, these computational tools rely on assumptions that have been found inconsistent or unrealistic. This paper presents a multi-agent based framework for simulating human and social behavior during emergency evacuation. A prototype system has been developed, which is able to demonstrate some emergent behaviors, such as competitive, queuing, and herding behaviors. For illustration, an example application of the system for safe egress design is provided.     

An image-based seismic damage assessment system

Surveillance systems are commonly used by command centers to monitor and assess seismic damage inside buildings, such as schools, shopping malls, office buildings and skyscrapers. It is expected that checking camera images manually on monitors can be a very time-consuming and inefficient process, especially for a large surveillance system. One of the alternative ways is to first deploy sensors to monitor objects inside buildings, such as tables, cabinets, bookcases and so on, and, after fusing sensor data, to assess damage. However, deploying sensors can be impractical and costly when there are too many objects needed to be monitored. In this paper, we present IDEAS, an image-based disaster damage assessment system, to evaluate seismic damage inside buildings. IDEAS first compares images taken inside a building before and after an earthquake, it then maps the damage to a Mercalli intensity scale. In order to investigate the effectiveness and accuracy of IDEAS, we collect over forty pairs of closed-circuit television (CCTV) images from Youtube website. Each pair of images represents a real scenario of an earthquake inside a building. Our results show that IDEAS performs better than existing methods and can achieve an average accuracy of 97.6 % in mapping Mercalli intensity scale.     

Towards a customizable immersive virtual reality serious game for earthquake emergency training

Earthquake emergencies require a variety of behavioral responses in order to ensure the safety of occupants, which is different from simply exiting a building in fire emergencies. This makes it more complex to train building occupants in order to acquire skills that align to best practices for immediate earthquake response and post-earthquake evacuation. In recent years, Immersive Virtual Reality (IVR) and Serious Games (SGs) have become popular as training tools for earthquake emergencies. IVR SGs have been introduced to train individuals for specific building layouts or settings with fixed training objectives. However, the lack of flexibility in existing IVR SGs makes it challenging to have widespread uptake as trainees require different training objectives, pedagogical strategies, context, and content. As a result, the effectiveness of IVR SGs training is jeopardized if the customization ability is limited. To overcome this limitation, this paper presents a customization framework for IVR SGs suited to earthquake emergency training, using the concept of adaptive game-based learning. Trainees can receive training in context by customizing virtual environments, storylines, and teaching methods. A case study was undertaken to validate the proposed framework. Results showed the potential to carry out the customization process with ease, to generate a customized training experience, and to deliver the customized training for optimum learning.     

SEEVis: A Smart Emergency Evacuation Plan Visualization System with Data-Driven Shot Designs

Despite the significance of tracking human mobility dynamics in a large-scale earthquake evacuation for an effective first response and disaster relief, the general understanding of evacuation behaviors remains limited. Numerous individual movement trajectories, disaster damages of civil engineering, associated heterogeneous data attributes, as well as complex urban environment all obscure disaster evacuation analysis. Although visualization methods have demonstrated promising performance in emergency evacuation analysis, they cannot effectively identify and deliver the major features like speed or density, as well as the resulting evacuation events like congestion or turn-back. In this study, we propose a shot design approach to generate customized and narrative animations to track different evacuation features with different exploration purposes of users. Particularly, an intuitive scene feature graph that identifies the most dominating evacuation events is first constructed based on user-specific regions or their tracking purposes on a certain feature. An optimal camera route, i.e., a storyboard is then calculated based on the previous user-specific regions or features. For different evacuation events along this route, we employ the corresponding shot design to reveal the underlying feature evolution and its correlation with the environment. Several case studies confirm the efficacy of our system. The feedback from experts and users with different backgrounds suggests that our approach indeed helps them better embrace a comprehensive understanding of the earthquake evacuation.     

Detection of collapsed buildings caused by the 1999 Izmit,Turkey earthquake through digital analysis of post-event aerial photographs

In this study, the post-earthquake aerial photographs were digitally processed and analysed to detect collapsed buildings caused by the Izmit, Turkey earthquake of 17 August 1999. The selected area of study encloses part of the city of Golcuk, which is one of the urban areas most strongly hit by the earthquake. The analysis relies on the idea that if a building is collapsed, then it will not have corresponding shadows. The boundaries of the buildings were available and stored in a Geographical Information System (GIS) as vector polygons. The vector building polygons were used to match the shadow casting edges of the buildings with their corresponding shadows and to perform analyses in a building-specific manner. The shadow edges of the buildings were detected through a Prewitt edge detection algorithm. For each building, the agreement was then measured between the shadow producing edges of the building polygons and the thresholded edge image based on the percentage of shadow edge pixels. If the computed percentage value was below a preset threshold then the building being assessed was declared as collapsed. Of the 80 collapsed buildings, 74 were detected correctly, providing 92.50% producer's accuracy. The overall accuracy was computed as 96.15%. The results show that the detection of the collapsed buildings through digital analysis of post-earthquake aerial photographs based on shadow information is quite encouraging. It is also demonstrated that determining the optimum threshold value for separating the collapsed from uncollapsed buildings is important.     

Evolutionary acquisition of behavior to build structural objects by virtual creatures

One of our purposes is to develop virtual creatures which can acquire behaviors such as building structural objects in a 3D physical simulation. In this article, we show the influences of behavior on structural objects which are built by virtual creatures. Many creatures can change their environment for the better by building structural objects, for example, spiders’ nests. In the field of artificial life, there are many studies of virtual creatures which change their bodies and behavior to suit their environments. In contrast, there are few studies about virtual creatures which build structural objects. As for natural creatures, virtual creatures need a physical interaction between their body and their environment. Therefore, our purpose is to develop a framework for the autonomous acquisition of behaviors which build structural objects in a 3D physical simulation. In order to do this, we first studied the evolutionary acquisition of behavior for building structural objects, e.g., a nest for predation, by the simple behavior of throwing blocks. As a result, we show the possibility that virtual creatures can acquire building behavior evolutionarily.     

Risk assessment in work environments: modeling and simulation

The paper proposes a characterization of risks and a service‐oriented prototype to face risky situations in work environments, such as in industrial plants or building construction areas. A risk is the overture of emergencies that produce human and/or material damages. Therefore, it is particularly critical to identify and manage risks to avoid their evolution into emergencies. In this paper, we outline the technological features of a risk environment and propose a risk model and a service‐based simulation prototype aimed to improve safety in work environments. We discuss engineering issues concerning risk modeling and management. Furthermore, we propose a risk management system solution and its related implemented prototype composed of services able to detect and also to prevent the occurrence of risk conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

An indoor location tracking based on mobile RFID for smart exhibition service

Recently, various smart application services have been developed using GPS (Global Positioning System), RFID (Radio Frequency IDentification) and sensor networks. The GPS has been successfully applied for outdoor location tracking by many applications, but it might still be insufficient in an indoor environment where GPS signals are often severely obstructed. The RFID technology has been utilized to play an important role in location tracking for indoor smart applications. Therefore, in this paper, we present the scenario and architecture of an indoor location tracking service for things or space in an exhibition environment based on mobile RFID. The RFID tags of things or spaces are identified as the locations of point being passed and we obtain the spatial data from the tags using mobile RFID readers, Web server and Database server. We have designed and implemented the prototype of location tracking system for exhibition scenario using Microsoft .NET framework. Additionally, we have verified the functionality of this system so various other indoor smart services may be provided using the proposed system.