A grid-based spatial data model for the simulation and analysis of individual behaviours in micro-spatial environments

As crowd simulation in micro-spatial environment is more widely applied in urban planning and management, the construction of an appropriate spatial data model that supports such applications becomes essential. To address the requirements necessary to building a model of crowd simulation and people–place relationship analysis in micro-spatial environments, the concept of the grid as a basic unit of people–place data association is presented in this article. Subsequently, a grid-based spatial data model is developed for modelling spatial data using Geographic Information System (GIS). The application of the model for crowd simulations in indoor and outdoor spatial environments is described. There are four advantages of this model: first, both the geometrical characteristics of geographic entities and behaviour characteristics of individuals within micro-spatial environments are involved; second, the object-oriented model and spatial topological relationships are fused; third, the integrated expression of indoor and outdoor environments can be realised; and fourth, crowd simulation models, such as Multi-agent System (MAS) and Cellular Automata (CA), can be further fused for intelligent simulation and the analysis of individual behaviours. Lastly, this article presents an experimental implementation of the data model, individual behaviours are simulated and analysed to illustrate the potential of the proposed model.     

A Virtual Environment for the Design and Simulated Construction of Prefabricated Buildings

The construction industry has acknowledged that its current working practices are in need of substantial improvements in quality and efficiency and has identified that computer modelling techniques and the use of prefabricated components can help reduce times, costs, and minimise defects and problems of on-site construction. This paper describes a virtual environment to support the design and construction processes of buildings from prefabricated components and the simulation of their construction sequence according to a project schedule. The design environment can import a library of 3-D models of prefabricated modules that can be used to interactively design a building. Using Microsoft Project, the construction schedule of the designed building can be altered, with this information feeding back to the construction simulation environment. Within this environment the order of construction can be visualised using virtual machines. Novel aspects of the system are that it provides a single 3-D environment where the user can construct their design with minimal user interaction through automatic constraint recognition and view the real-time simulation of the construction process within the environment. This takes this area of research a step forward from other systems that only allow the planner to view the construction at certain stages, and do not provide an animated view of the construction process.     

基于高密度人群的人流行为分析

对人流分析的宏观模型、微观模型和社会力模型在某些方面都可起到模拟人群流动的作用,可在建筑设计、安全防范、灾难预警、危机处置等方面起到很好的理论指导作用。文章以实际情况中人群密度非常高情况下产生的严重后果事件为前提,在元胞自动机模型基础上,提出了一种基于高磐度人流行为的模型,该方法可更好地模拟高密度人流的现实情况。     

Crowd simulation-based knowledge mining supporting building evacuation design

Assessing building evacuation performance designs in emergency situations requires complex scenarios which need to be prepared and analysed using crowd simulation tools, requiring significant manual input. With current procedures, every design iteration requires several simulation scenarios, leading to a complicated and time-consuming process. This study aims to investigate the level of integration between digital building models and crowd simulation, within the scope of design automation. A methodology is presented in which existing ontology tools facilitate knowledge representation and mining throughout the process. Several information models are used to integrate, automate and provide feedback to the design decision-making processes. The proposed concept thus reduces the effort required to create valid simulation scenarios by applying represented knowledge, and provides feedback based on results and design objectives. To apply and test the methodology a system was developed, which is introduced here. The context of building performance during evacuation scenarios is considered, but additional design perspectives can be included. The system development section expands on the essential theoretical concepts required and the case study section shows a practical implementation of the system.     

Crowd simulation using DC model and density information

Realistic crowd simulation is an important issue for the production of virtual worlds for games, crowd management, public space design, education, entertainment or architectural and urban planning. In this paper, crowd simulation is considered from two aspects: intra-group simulation and inter-group simulation. We propose a unified framework for crowd simulation in real-time virtual environment. Based on this framework, for intra-group simulation, we propose a novel density-based information crowd simulation to collision-free. For inter-group simulation, we propose a novel discrete choice (DC) model to realistic simulation of crowds and path planning. Meanwhile, we also propose a variable bounding box method for intra-group/inter-groups intersection problem. The simulation results show that the developed framework allows different group structures to be easily modeled. And the proposed framework could be used for real-time navigation of many moving crowd in complicated virtual environments.     

复杂条件下多层建筑人员协作疏散仿真

研究具有复杂多层协作过程条件下的人员疏散控制系统,就能够比较准确地模拟突发情况下人员的疏散情况。本文对元胞自动机进行了改进,综合人员个体特征和从众心理等各种复杂因素,对具有复杂障碍物的多层建筑中人员疏散过程进行了计算机仿真分析,并给出了人员疏散效率与人员的从众系数、障碍物及出口位置等因素的关系。该仿真能够很好地模拟大型公共场所发生突发事件时人员疏散的情况,对在复杂地理环境及人员特性条件下的多层建筑突发事件疏散策略制定具有一定的实际参考意义。     

Urban Walkability Design Using Virtual Population Simulation

We present a system to generate a procedural environment that produces a desired crowd behaviour. Instead of altering the behavioural parameters of the crowd itself, we automatically alter the environment to yield such desired crowd behaviour. This novel inverse approach is useful both to crowd simulation in virtual environments and to urban crowd planning applications. Our approach tightly integrates and extends a space discretization crowd simulator with inverse procedural modelling. We extend crowd simulation by goal exploration (i.e. agents are initially unaware of the goal locations), variable‐appealing sign usage and several acceleration schemes. We use Markov chain Monte Carlo to quickly explore the solution space and yield interactive design. We have applied our method to a variety of virtual and real‐world locations, yielding one order of magnitude faster crowd simulation performance over related methods and several fold improvement of crowd indicators.     

Model-based Crowd Behaviours in Human-solution Space

Realistic crowd simulation has been pursued for decades, but it still necessitates tedious human labour and a lot of trial and error. The majority of currently used crowd modelling is either empirical (model-based) or data-driven (model-free). Model-based methods cannot fit observed data precisely, whereas model-free methods are limited by the availability/quality of data and are uninterpretable. In this paper, we aim at taking advantage of both model-based and data-driven approaches. In order to accomplish this, we propose a new simulation framework built on a physics-based model that is designed to be data-friendly. Both the general prior knowledge about crowds encoded by the physics-based model and the specific real-world crowd data at hand jointly influence the system dynamics. With a multi-granularity physics-based model, the framework combines microscopic and macroscopic motion control. Each simulation step is formulated as an energy optimization problem, where the minimizer is the desired crowd behaviour. In contrast to traditional optimization-based methods which seek the theoretical minimizer, we designed an acceleration-aware data-driven scheme to compute the minimizer from real-world data in order to achieve higher realism by parameterizing both velocity and acceleration. Experiments demonstrate that our method can produce crowd animations that are more realistically behaved in a variety of scales and scenarios when compared to the earlier methods.     

基于元胞自动机和模糊理论的人群疏散仿真

基于元胞自动机和模糊理论建立了人群疏散模型,对教学楼内的人群疏散过程进行了模拟。该模型根据人员对建筑物的熟悉程度、周围人员的吸引力设计元胞行为准则,并且采用模糊隶属度定义人员的体能状态及人员对环境的熟悉程度。实验结果表明,该仿真模型能够较好地模拟紧急状况下的人群疏散过程。     

基于熵度量的人群模型评估方法

人群模型评估是虚拟人群仿真研究的关键问题,现有的研究多通过个体仿真轨迹与真实轨迹之间的误差来评估人群模型.然而人群行为本质上是复杂的随机系统,简单的轨迹对比并不能有效反映模型能力.本文应用熵度量的模型评估方法,通过估计真实人群状态与仿真人群状态的误差分布实现了精确的人群仿真定量评估.同时引入失真情况的判断和处理规则,使得评估方法在仿真失真情况下能够保持准确性.实验结果表明,本文提出的算法及规则能有效地实现人群仿真模型的定量评估并给出模型参数选择的指导.     

BIM extension for the sustainability appraisal of conceptual steel design

Contemporary advancements in Information Technology and the efforts from various research initiatives in the AEC industry are showing evidence of progress with the emergence of building information modelling (BIM). BIM presents the opportunity of electronically modelling and managing the vast amount of information embedded in a building project, from its conception to end-of-life. Researchers have been looking at extensions to expand its scope. Sustainability is one such modelling extension that is in need of development. This is becoming pertinent for the structural engineer as recent design criteria have put great emphasis on the sustainability credentials in addition to the traditional criteria of structural integrity, constructability and cost. With the complexity of designs, there are now needs to provide decision support tools to aid in the assessment of the sustainability credentials of design solutions. Such tools would be most beneficial at the conceptual design stage so that sustainability is built into the design solution starting from its inception. The sustainability of buildings is related to life cycle and is measured using indicator-terms such as life cycle costing, ecological footprint and carbon footprint. This paper proposes a modelling framework combining these three indicators in providing sustainability assessments of alternative design solutions based on the economic and environmental sustainability pillars. It employs the principles of feature-based modelling to extract construction-specific information from product models for the purposes of sustainability analysis. A prototype system is implemented using .NET and linked to the BIM enabled software, Revit Structures™. The system appraises alternative design solutions using multi-criteria performance analysis. This work demonstrates that current process and data modelling techniques can be employed to model sustainability related information to inform decisions right from the early stages of structural design. It concludes that the utilized information modelling representations – in the form of a process model, implementation algorithms and object-based instantiations – can capture sustainability related information to inform decisions at the early stages of the structural design process.     

基于智能体方法的人群疏散三维仿真

研究建筑物在不同出口条件设置下人员的安全疏散问题。针对人群仿真中如何计算疏散路径问题,文中采用导航图技术和agent技术来对个体进行疏散路径的规划。同时为表现人群运动过程当中个体之间的相互碰撞问题,结合碰撞规避规则进行穿透矫正。并且采用三维引擎DeltaSD在Vc＋＋9．0环境下进行仿真并搭建了一套三维人群运动模拟平台。最后分别在三种不同出口条件下的虚拟场景中进行仿真。对比仿真结果表明该平台能直观地展现整个人群疏散的运动过程,并能够对建筑物出口安全设计的合理陛提供有效的数据依据。     

PERSONAF: framework for personalised ontological reasoning in pervasive computing

Pervasive computing creates possibilities for presenting highly personalised information about the people, places and things in a building. One of the challenges for such personalisation is the creation of the system that can support ontological reasoning for several key tasks: reasoning about location; personalisation of information about location at the right level of detail; and personalisation to match each person’s conceptions of the building based on their own use of it and their relationship to other people in the building. From pragmatic perspectives, it should be inexpensive to create the ontology for each new building. It is also critical that users should be able to understand and control pervasive applications. We created the PERSONAF (personalised pervasive scrutable ontological framework) to address these challenges. PERSONAF is a new abstract framework for pervasive ontological reasoning. We report its evaluation at three levels. First, we assessed the power of the ontology for reasoning about noisy and uncertain location information, showing that PERSONAF can improve location modelling. Notably, the best ontological reasoner varies across users. Second, we demonstrate the use of the PERSONAF framework in Adaptive Locator, an application built upon it, using our low cost mechanisms for non-generic layers of the ontology. Finally, we report a user study, which evaluated the PERSONAF approach as seen by users in the Adaptive Locator. We assessed both the personalisation performance and the understandability of explanations of the system reasoning. Together, these three evaluations show that the PERSONAF approach supports building of low cost ontologies, that can achieve flexible ontological reasoning about smart buildings and the people in them, and that this can be used to build applications which give personalised information that can provide understandable explanations of the reasoning underlying the personalisation.     

Incorporation of BIM-based probabilistic non-structural damage assessment into agent-based post-earthquake evacuation simulation

Earthquakes can cause severe damage to structural and non-structural elements of buildings; consequently, they pose high risks to human lives. To mitigate such risks, attention has been paid to enhancing the indoor environment for increased building safety. Yet little effort has been made to assess a building occupants' evacuation behaviors in response to damage to the indoor environment. This paper addresses this issue with a novel simulation framework that couples human behaviors with changes to the indoor building environment during post-earthquake evacuation. In particular, we present a building information modelling (BIM)-based prototype that simulates seismic damage to the non-structural indoor elements and visualizes its impacts on evacuation using a color-coded heat map. The simulated damage is then used as input to an agent-based model for post-earthquake evacuation. Using a probabilistic method to assess the non-structural elements' damage states, we are able to evaluate the impact of indoor damage on the evacuation process. We performed a trial of our prototype for a hypothetical earthquake in an educational building. The results revealed how the average evacuation time would increase as the earthquake intensity increases (from 38.6 s for the no-damage scenario to 122.9 for the highest-damage scenario). The proposed prototype has the potential to be joined with other tools, such as finite-element-based simulation, to incorporate structural analysis as well. Planners and designers can explicitly use our model's output to analyze the post-earthquake evacuation with the indoor non-structural damage to assess different building design geometries that increase the chances of a suitable evacuation process.     

Live semantic data from building digital twins for robot navigation: Overview of data transfer methods

Increasing reliance on automation and robotization presents great opportunities to improve the management of construction sites as well as existing buildings. Crucial in the use of robots in a built environment is their capacity to locate themselves and navigate as autonomously as possible. Robots often rely on planar and 3D laser scanners for that purpose, and building information models (BIM) are seldom used, for a number of reasons, namely their unreliability, unavailability, and mismatch with localization algorithms used in robots. However, while BIM models are becoming increasingly reliable and more commonly available in more standard data formats (JSON, XML, RDF), they become more promising and reliable resources for localization and indoor navigation, in particular in the more static types of existing infrastructure (existing buildings). In this article, we specifically investigate to what extent and how such building data can be used for such robot navigation. Data flows are built from BIM model to local repository and further to the robot, making use of graph data models (RDF) and JSON data formats. The local repository can hereby be considered to be a digital twin of the real-world building. Navigation on the basis of a BIM model is tested in a real world environment (university building) using a standard robot navigation technology stack. We conclude that it is possible to rely on BIM data and we outline different data flows from BIM model to digital twin and to robot. Future work can focus on (1) making building data models more reliable and standard (modelling guidelines and robot world model), (2) improving the ways in which building features in the digital building model can be recognized in 3D point clouds observed by the robots, and (3) investigating possibilities to update the BIM model based on robot feedback.     

Guided Crowd Evacuation: Approaches and Challenges

Evacuation leaders and/or equipment provide route and exit information for people and guide them to the expected destinations, which could make crowd evacuation more efficient in case of emergency. The purpose of this paper is to provide an overview of recent advances in guided crowd evacuation. Different guided crowd evacuation approaches are classified according to guidance approaches and technologies. A comprehensive analysis and comparison of crowd evacuation with static signage, dynamic signage, trained leader, mobile devices, mobile robot and wireless sensor networks are presented based on a single guidance mode perspective. In addition, the different evacuation guidance systems that use high-tech means such as advanced intelligent monitoring techniques, AI techniques, computer technology and intelligent inducing algorithms are reviewed from a system’s perspective. Future researches in the area of crowd evacuation are also discussed.      

Phenomenologial foundations of conceptual product modelling in architecture,engineering and construction

The ultimate goal of conceptual modelling in architecture, engineering and construction (AEC) has been to define the data structures that could be used to describe the entire built environment through all its life cycle stages — from inception and design to demolition. In spite of the magnitude and complexity of this task, the theoretical foundations of modelling received little attention. In this paper, the theoretical foundations of the traditional modelling approaches are questioned using phenomenology and hermeneutics as philosophical base. The author exposes the difference between the remodelling of some existing models, the modelling of physical objects and the modelling of psychical, intentional objects. The author concludes that AEC or building product and process models do not model objective reality but the modeller's partial understanding of that reality. Therefore, several correct but different models may and should exist. Future software architectures in AEC should not be built on a unified, centralized model but, on a combination of models, which may not be standardised but whose schemas are encoded in a standard manner.     

基于不确定网格地图的移动机器人导航

研究了在未知环境下的移动机器人导航问题．在分析超声传感器不确定性模型的基础上,根据模糊集理论创建网格地图来描述机器人工作环境,使用模糊隶属度表示网格占用状态．通过网格信息融合来减弱传感器测量误差,提高网格地图的精度．提出基于模糊网格地图的路径规划算法,利用重复局部优化路径搜索来实现全局路径规划．机器人通过交替进行创建地图和路径规划两个基本过程来完成导航任务．仿真结果表明创建的地图能较精确地表示环境信息。规划的路径可以使机器人安全地到达目的地．     

Guidance path scheduling using particle swarm optimization in crowd simulation

In this paper, we propose a method for using particle swarm optimization (PSO) to compute optimal guidance paths for various crowd densities in an agent‐based crowd simulation. The inputs of our system are guidance paths that provide hints for the movement directions of agents. Input guidance paths may not be located correctly (e.g., leading to congestion or high traveling cost); therefore, our method adjusts the guidance paths by using PSO. We consider several factors for evaluating the quality of a guidance path, including the average traveling time and interaction distance between agents. We apply our method in several examples. Experimental results show that our method can compute adaptive guidance paths for various crowd densities. Our system can simulate organized crowds that move in directions specified by the guidance paths. Copyright © 2015 John Wiley & Sons, Ltd.