Self-organized crowd dynamics : research on earthquake emergency response patterns of drill-trained individuals based on GIS and multi-agent systems methodology

Predicting evacuation patterns is useful in emergency management situations such as an earthquake. To find out how pre-trained individuals interact with one another to achieve their own goal to reach the exit as fast as possible firstly, we investigated urban people’s evacuation behavior under earthquake disaster conditions, established crowd response rules in emergencies, and described the drill strategy and exit familiarity quantitatively through a cellular automata model. By setting different exit familiarity ratios, simulation experiments under different strategies were conducted to predict people’s reactions before an emergency. The corresponding simulation results indicated that the evacuees’ training level could affect a multi-exit zone’s evacuation pattern and clearance time. Their exit choice preferences may disrupt the exit options’ balance, leading to congestion in some of the exits. Secondly, due to people’s rejection of long distances, congestion, and unfamiliar exits, some people would hesitant about the evacuation direction during the evacuation process. This hesitation would also significantly reduce the overall evacuation efficiency. Finally, taking a community in Zhuhai City, China, as an example, put forward the best urban evacuation drill strategy. The quantitative relation between exit familiar level and evacuation efficiency was obtained. The final results showed that the optimized evacuation plan could improve evacuation’s overall efficiency through the self-organization effect. These studies may have some impact on predicting crowd behavior during evacuation and designing the evacuation plan

Inundation resilience analysis of metro-network from a complex system perspective using the grid hydrodynamic model and FBWM approach : a case study of Wuhan

The upward trend of metro flooding disasters inevitably brings new challenges to urban underground flood management. It is essential to evaluate the resilience of metro systems so that efficient flood disaster plans for preparation, emergency response, and timely mitigation may be developed. Traditional response solutions merged multiple sources of data and knowledge to support decision-making. An obvious drawback is that original data sources for evaluations are often stationary, inaccurate, and subjective, owing to the complexity and uncertainty of the metro station’s actual physical environment. Meanwhile, the flood propagation path inside the whole metro station network was prone to be neglected. This paper presents a comprehensive approach to analyzing the resilience of metro networks to solve these problems. Firstly, we designed a simplified weighted and directed metro network module containing six characteristics by a topological approach while considering the slope direction between sites. Subsequently, to estimate the devastating effects and details of the flood hazard on the metro system, a 100-year rainfall–flood scenario simulation was conducted using high-precision DEM and a grid hydrodynamic model to identify the initially above-ground inundated stations (nodes). We developed a dynamic node breakdown algorithm to calculate the inundation sequence of the nodes in the weighted and directed network of the metro. Finally, we analyzed the resilience of the metro network in terms of toughness strength and organization recovery capacity, respectively. The fuzzy best–worst method (FBWM) was developed to obtain the weight of each assessment metric and determine the toughness strength of each node and the entire network. The results were as follows. (1) A simplified three-dimensional metro network based on a complex system perspective was established through a topological approach to explore the resilience of urban subways. (2) A grid hydrodynamic model was developed to accurately and efficiently identify the initially flooded nodes, and a dynamic breakdown algorithm realistically performed the flooding process of the subway network. (3) The node toughness strength was obtained automatically by a nonlinear FBWM method under the constraint of the minimum error to sustain the resilience assessment of the metro network. The research has considerable implications for managing underground flooding and enhancing the resilience of the metro network

An efficient decision support system for flood inundation management using intermittent remote-sensing data

Abstract: Timely acquisition of spatial flood distribution is an essential basis for flood-disaster monitoring and management. Remote-sensing data have been widely used in water-body surveys. However, due to the cloudy weather and complex geomorphic environment, the inability to receive remote-sensing images throughout the day has resulted in some data being missing and unable to provide dynamic and continuous flood inundation process data. To fully and effectively use remote-sensing data, we developed a new decision support system for integrated flood inundation management based on limited and intermittent remote-sensing data. Firstly, we established a new multi-scale water-extraction convolutional neural network named DEU-Net to extract water from remote-sensing images automatically. A specific datasets training method was created for typical region types to separate the water body from the confusing surface features more accurately. Secondly, we built a waterfront contour active tracking model to implicitly describe the flood movement interface. In this way, the flooding process was converted into the numerical solution of the partial differential equation of the boundary function. Space upwind difference format and the time Euler difference format were used to perform the numerical solution. Finally, we established seven indicators that considered regional characteristics and flood-inundation attributes to evaluate flood-disaster losses. The cloud model using the entropy weight method was introduced to account for uncertainties in various parameters. In the end, a decision support system realizing the flood losses risk visualization was developed by using the ArcGIS application programming interface (API). To verify the effectiveness of the model constructed in this paper, we conducted numerical experiments on the model’s performance through comparative experiments based on a laboratory scale and actual scale, respectively. The results were as follows: (1) The DEU-Net method had a better capability to accurately extract various water bodies, such as urban water bodies, open-air ponds, plateau lakes etc., than the other comparison methods. (2) The simulation results of the active tracking model had good temporal and spatial consistency with the image extraction results and actual statistical data compared with the synthetic observation data. (3) The application results showed that the system has high computational efficiency and noticeable visualization effects. The research results may provide a scientific basis for the emergency-response decision-making of flood disasters, especially in data-sparse regions

Vision-based methods for relative sag measurement of suspension bridge cables

Main cables, comprising a number of wire strands, constitute a vital element in long-span suspension bridges. The determination of their alignment during construction is of great importance, and relative sag is commonly measured for the efficient sag adjustment of general strands. The conventional approach uses the caterpillar method, which is inconvenient, difficult-to-implement, and potentially dangerous. In order to realize the high-precision measurement of cable alignment in a strong wind environment, a vision-based method for relative sag measurement of the general cable strands is proposed in this paper. In the proposed measurement system, images of pre-installed optical targets are collected and analyzed to realize the remote, automatic, and real-time measurement of the relative sag. The influences of wind-induced cable shaking and camera shaking on the accuracy of the height difference measurement are also theoretically analyzed. The results show that cable strand torsion and camera roll have a great impact on the measurement accuracy, while the impacts of the cable strand swing and vibration, camera swing and vibration, and camera pitch and yaw are insignificant. The vision-based measurement system tested in the field experiment also shows a measurement error within 3 mm, which meets the requirements for cable adjustment construction. At the same time, the vision-based measurement method proposed and validated in this paper can improve the measurement accuracy and efficiency of strand alignment in a strong wind environment. Potential risks involved in the manual measurement, e.g., working at heights and in strong wind environments, can be eliminated, facilitating the automation of the cable erection process

Vision-based pavement marking detection and condition assessment : a case study

Pavement markings constitute an effective way of conveying regulations and guidance to drivers. They constitute the most fundamental way to communicate with road users, thus, greatly contributing to ensuring safety and order on roads. However, due to the increasingly extensive traffic demand, pavement markings are subject to a series of deterioration issues (e.g., wear and tear). Markings in poor condition typically manifest as being blurred or even missing in certain places. The need for proper maintenance strategies on roadway markings, such as repainting, can only be determined based on a comprehensive understanding of their as-is worn condition. Given the fact that an efficient, automated and accurate approach to collect such condition information is lacking in practice, this study proposes a vision-based framework for pavement marking detection and condition assessment. A hybrid feature detector and a threshold-based method were used for line marking identification and classification. For each identified line marking, its worn/blurred severity level was then quantified in terms of worn percentage at a pixel level. The damage estimation results were compared to manual measurements for evaluation, indicating that the proposed method is capable of providing indicative knowledge about the as-is condition of pavement markings. This paper demonstrates the promising potential of computer vision in the infrastructure sector, in terms of implementing a wider range of managerial operations for roadway management

Integrating virtual reality and Building Information Modeling for improving highway tunnel emergency response training

During the last two decades, managers have been applying Building Information Modeling (BIM) to improve the quality of management as well as operation. The effectiveness of applications within a BIM environment is restrained by the limited immersive experience in virtual environments. Defined as the immersive visualization of virtual scenes, Virtual Reality (VR) is an emerging technology that can be actively explored to expand BIM to more usage. This paper highlights the need for a structured methodology for the integration of BIM/VR and gives a generic review of BIM and VR in training platforms for management in infrastructures. The rationales for fire evacuation training were formed based on the review. Then, methods of configuring BIM + VR prototypes were formulated for emergency response in highway tunnels. Furthermore, a conceptual framework integrating BIM with VR was proposed to enable the visualization of the physical context in real-time during the training. The result indicated that, extended to the training system of highway management via the “hand” of BIM, the VR solution can benefit more areas, such as the cost of fire evacuation drills in highway tunnels and the tendency of accidents to occur in the emergency response

[In Press] The application of simulation in lean production research : a critical review and future directions

Purpose – Simulation has attracted increasing attention in lean production research as a response to address the complexities of the production environment and difficulties of dealing with changes within a system. Considerable growth of using simulation to facilitate lean acceptance and implementation has been observed across different projects and sectors. However, a thorough review of the development and use of simulation in lean production research is limited. Design/methodology/approach – This study aims to address this gap by reviewing 311 journal papers published in the past two decades on this specific research area and identify the state-of-the-art development and propose future research directions. Findings – The review shows that current studies related to simulation in lean production research can be categorised into two major research streams, namely, simulation assisted lean facilitation and evaluation, and simulation-based lean education and training. Under the first research stream, a total of 19 application areas have been identified which applied both lean and simulation in their studies. The evolution of the simulation techniques used in these studies has been analysed as well. Meanwhile, four types of simulation games have been identified in the stream of simulation-based lean education and training and the impact and applicability of the different simulation and games have been discussed. A framework for engaging lean and simulation is suggested based on the review of the existing studies. The analysis in both streams also highlights the importance of stakeholder engagement and the utilisation of information technologies for future studies. Practical implications – The findings of this study are expected to provide useful references for the future development and application of simulation in lean production research. Originality/value – This paper conducted a broad and extensive review of simulation integrated lean production research. An in-depth examination of the retrieved papers was conducted through a structured and quantitative analysis to understand the current body of knowledge

A survey of simulation modelling techniques in lean construction research

Over the past two decades, discrete event simulation (DES) has been increasingly employed in lean construction research as a response to the requirement of evaluating the impact of the implementation of various lean initiatives. A systematic review of DES application in lean construction research is necessary to examine how DES has been implemented in lean research. This review was conducted by reviewing 49 DES papers published in peer-reviewed journals and IGLC conference between 1997 and 2018, which aims to identify the state of the art development in this specific research area and propose future research directions. The papers are analysed in terms of publications, DES techniques, value of DES, and topic coverage. 13 types of DES techniques, 6 value of DES in lean construction research, and 8 research topics are identified and summarised. The findings of this study are expected to provide useful suggestions for the future research opportunities of DES in lean construction research

A framework of total constraint management for improving work flow in liquefied natural gas construction

In complex and concurrent construction project, numerous constraints which come from engineering, supply chains and construction work face are the main factors affecting plan reliability. Effective management of these constraints is critical to improve planning reliability and work flow. However, current constraint management approach is very fragmented and heavy relies on human’s commitments and static data in constraint identification, tracking, assessment and removal. To tackle this problem, this paper proposes a framework of Total Constraint Management (TCM), which possesses four superior characteristics including: (1) collaborative constraint identification; (2) real-time constraint status tracking; (3) dynamic constraint removal; and (4) visual constraint representation. Advanced technologies, such as Building Information Modelling, barcode, and Radio Frequency Identification, are discussed to enable TCM implementation in practice. A controlled experiment was developed to demonstrate and evaluate the framework. The results showed that successful implementation of TCM could significantly improve plan reliability and construction productivity

BIM-integrated life cycle assessment in environmental analysis : current status and future development

Due to the rising recognition of environmental sustainability, environmental assessment has been a core task for construction projects. Traditional environmental assessment of construction projects follows the Life Cycle Assessment (LCA) rule and principles, which may be time consuming and require extensive manual inputs. In recent years, many studies has been initiated to use Building Information Modelling (BIM) as the platform to host LCA implementations. Benefits, including increased productivity and flexibility, have been recorded. However, some problems, such as varied scope and definition, have also been identified. It is therefore necessary for the construction industry to understand the current status and future development of BIM-integrated LCA. A systematic review shows that BIM have been used as the platform to host LCA implementations for various project life cycles (including production, transportation, construction, operation and end-of-life stages) and environmental impacts (mainly including energy, carbon emissions, water and waste). In addition, future actions are needed in the aspect of standardization, benchmarking and available of databases in order to allow accurate comparison of the environmental performance between different projects and design alternatives