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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. [ABSTRACT FROM AUTHOR]

Computer Vision (CV) based surveillance in crowded scenes is one of the most significant and promising topics due to the increase of people gatherings in public places where the possibilities of disasters and stampedes is also high. Therefore, it is essential to develop a well established Crowd Disaster Avoidance System (CDAS) for the public safety. In general, CV-CDAS focuses on crowd scene analysis, crowd behavior analysis and crowd management. Either, a stampede may occur due to abnormal behavior of individuals in a crowd or a crowd may behave abnormally after the stampede. Even though behavior analysis of a crowd plays an essential role, it is inadequate to decide whether a stampede may occur or not at that instance. Despite significant progress and various surveys on crowd scene, crowd modeling and behavior analysis over the past few decades, the existing surveys still fail to discuss and delineate the crowd disaster analysis based on many key aspects as a whole. However, CV-CDAS needs to be developed based on the necessary factors such as the number of cameras (single/multiple), target of interest (an individual/group or crowd), crowd scene (structured/unstructured), crowd motion (static/dynamic), crowd behavior analysis, people count and crowd density estimation, person re-identification in crowd, crowd evacuation, forensic analysis on crowd disaster and computations on crowd analysis. Consequently, taking all these factors into an account, this survey aims to deliberate a road map to develop a stable CV-CDAS which includes recent trends and approaches in the crowd disaster analysis. In addition, behavior analysis plays a vital role and hence, an extended version of existing survey with the perspective of single and multiple cameras is elaborated. Besides, it summarizes the crowd disaster problem handled by various CV algorithms in the past and also paves a way to avoid this problem in future. Moreover, this survey presents the existing benchmark datasets with their specifications and performance evaluation metrics with special focus on dataset which will be suitable for specific application and it helps the researchers to select appropriate dataset for evaluation. Finally, this paper concludes with open issues and directions for future research which may further motivate and guide the academic and industrial personnel, involved in developing CV-based crowd disaster management systems. [ABSTRACT FROM AUTHOR]

Psychological factors affect the movement of people in the competitive or panic mode of evacuation, in which the density of pedestrians is relatively large and the distance among them is small. In this paper, a crowd is divided into groups according to their social relations to simulate the actual movement of crowd evacuation more realistically and increase the attractiveness of the group based on social force model. The force of group attraction is the synthesis of two forces; one is the attraction of the individuals generated by their social relations to gather, and the other is that of the group leader to the individuals within the group to ensure that the individuals follow the leader. The synthetic force determines the trajectory of individuals. The evacuation process is demonstrated using the improved social force model. In the improved social force model, the individuals with close social relations gradually present a closer and coordinated action while following the leader. In this paper, a grouping algorithm is proposed based on grid density and relationship via computer simulation to illustrate the features of the improved social force model. The definition of the parameters involved in the algorithm is given, and the effect of relational value on the grouping is tested. Reasonable numbers of grids and weights are selected. The effectiveness of the algorithm is shown through simulation experiments. A simulation platform is also established using the proposed grouping algorithm and the improved social force model for crowd evacuation simulation. [ABSTRACT FROM AUTHOR]

In the case of emergency situations, robotic systems can play a key role and save human lives in recovery and evacuation operations. To realize such a potential, we have to address many scientific and technical challenges encountered during robotic search and rescue missions. This paper reviews current state-of-the-art robotic technologies that have been deployed in the simulation of crowd evacuation, including both macroscopic and microscopic models used in simulating a crowd. Existing work on crowd simulation is analyzed and the robots used in crowd evacuation are introduced. Finally, the paper demonstrates how autonomous robots could be effectively deployed in disaster evacuation, as well as search and rescue missions. [ABSTRACT FROM AUTHOR]

The problem of evacuating crowded closed spaces, such as discotheques, public exhibition pavilions or concert houses, has become increasingly important and gained attention both from practitioners and from public authorities. This kind of problem can be modeled using Agent-Based Model techniques and consequently simulated in order to study evacuation strategies. In this paper, we show the Fira of Barcelona evacuation model implemented with Care HPS. As a main contribution: i) we extend and added new partitioning approaches and other features in Care HPS to carry on this model; and ii) we figured out that crowd evacuation problem has bottlenecks in reality, such as exits, that required more deep optimization in code in order to decrease the total execution time. Finally, we draw some conclusions and point out ways in which this work can be further extended. [ABSTRACT FROM AUTHOR]

In this paper, the information transmission mechanism is introduced into the social force model to simulate pedestrian behavior in an emergency, especially when most pedestrians are unfamiliar with the evacuation environment. This modified model includes a collision avoidance strategy and an information transmission model that considers information loss. The former is used to avoid collision among pedestrians in a simulation, whereas the latter mainly describes how pedestrians obtain and choose directions appropriate to them. Simulation results show that pedestrians can obtain the correct moving direction through information transmission mechanism and that the modified model can simulate actual pedestrian behavior during an emergency evacuation. Moreover, we have drawn four conclusions to improve evacuation based on the simulation results; and these conclusions greatly contribute in optimizing a number of efficient emergency evacuation schemes for large public places. [ABSTRACT FROM AUTHOR]

This study proposes an evacuation guidance model for heterogeneous populations to investigate the effects of guidance strategies on the evacuation process in large-scale pedestrian facilities with multiple exits. The guidance model integrates an exit choice model and a microscopic pedestrian simulation model with discrete space representation. The exit choice model, considering the travel distance to each exit, the level of congestion and the movement speed of pedestrians, generates the allocation of exits to pedestrians. The microscopic simulation model depicts the pedestrian movements during the evacuation under guidance. Numerical simulations are conducted to evaluate the performance of the guidance strategy. Simulation results indicate that by balancing the time interval for sending evacuation instruction and the frequency of the target exit changes, better evacuation performance can be achieved. Comparison between two cases with and without instruction reveals that the performance of the guidance strategy is closely related to the pedestrian density level and the heterogeneous speeds of pedestrians. The evacuation performance is also affected by the compliance behavior and non-compliance behavior of pedestrians. The findings can provide theoretical suggestions for the effective management of crowd movement at large events. • An evacuation guidance model is proposed to investigate the performance of guidance strategy. • The time interval for instruction and inertia to maintaining recommendation are considered. • The impact of guidance strategy on evacuation dynamics is studied. • The performance of guided evacuation is closely related to density and heterogeneity. [ABSTRACT FROM AUTHOR]

Presently, most models of crowd evacuations within a building are created manually. This is inefficient. To address this issue, this paper focuses on the differences and relationship between industry foundation classes (IFC) and the macroscopic network model for evacuation (MNME), and studies the mapping and construction methods used to convert entity objects into nodes and arcs in the MNME. Furthermore, corresponding attribute information in the MNME are established from IFC. Based on this process, the MNME is created and used as an input to EVACNET4 to obtain simulation results. Finally, the results, together with a 3D building model, are expressed in a unified environment. Our study results show that a network as well as the relevant attributes can be automatically generated from IFC, and can be adapted to different working conditions. The method proposed in this paper can automatically map the semantic information model to the MNME and the simulation result as well as the building model can be integrated in a Geographic Information System (GIS) environment.

Casualties during crowd evacuation in many unexpected events are closely related to panic behaviors. In this paper the evacuation crowd system is abstracted into a dynamic complex network composed of three types of people, namely calm people, panic people, and herding people, as well as their interactions. The mathematical model of these interactions is established based on complex network theory. Further, the evolution of herding people to panic people is interpreted by a specific concept of “herding–panic threshold,” as well as its utility threshold model, in which the own characteristics of herding people and the external pressure from the surrounding crowd are comprehensively considered. To verify the rationality of some assumption in the utility threshold model, a questionnaire survey about the evacuation psychological behaviors is carried out. Through theoretical analysis and simulation, the influence of some key parameters on the herding–panic behavior is discussed in detail, via analyzing the change of panic rate. Some safety measures to control herding–panic in evacuation are also suggested. [ABSTRACT FROM AUTHOR]

The growing need for more and more complicated underground urban systems has resulted to the development of a challenging environment for the setting up of effective evacuation procedure. The special circumstances and complexity, which characterize the underground spaces, as well as the severity of the consequences if an accident occurs, stimulated the research for different evacuation approaches in urban environments, in order to improve the efficiency of emergency evacuation and prevent crowd casualties in potential accidents, especially in the case of fire. The paper presents the most well respected standards, guidelines and regulations enforced worldwide, aiming to preserve the safeguarding of life and property against fire, explosion, and related hazards associated with developed subterranean spaces. Moreover, the evolution of underground evacuation approaches, from prescriptive methods to contemporary performance methods is displayed, followed by the examination of the approaches in crowd evacuation practices. Finally, the paper presents and analyses the factors being taken into account for planning the evacuation process, as illustrated through cases where modeling is conducted with special software codes. [ABSTRACT FROM AUTHOR]

A crowd usually tends to move in small groups during evacuation. Small group has a large proportion in crowd evacuation, and small group effect affects crowd evacuation significantly. In this work, we propose a novel methodology for calculating movement profit based on cellular automaton model. Specifically, this methodology calculates the movement profit for a target at the next moment by comprehensively combining distance profit, density profit, and average velocity profit. In particular, this paper defines three types of small-group formation with totally six different forms of small group in terms of the size, and sets the corresponding movement velocity. At last, we simulate the evacuation process of small groups, and discuss the relationship among evacuation time, average movement velocity, and pedestrian density, and analyze the efficiency of small group evacuation in terms of evacuation strategies. As the simulation results demonstrated, the evacuation efficiency of different types of small groups is greatly different, and the same type of small groups with different forms is also different. [ABSTRACT FROM AUTHOR]

First responders and security personnel face many challenges to safely evacuate crowded environments. Conducting frequent physical and table-top exercises are neither feasible nor economical. This is where modeling and simulation comes into play in providing a risk-free and economical method to practice various evacuation strategies, train first responders, and provide accurate decision-support and emergency guidance. With the aid of formal methods, here we present a suite of various egress strategies build on top of an open-source modeling and simulation environment. We use Cellular Discrete-Event System Specification (Cell-DEVS) formalism to explore emergency evacuation scenarios by building 12 egress models representing aspects of human behaviors under emergencies and the activities of authorities in guiding the crowd. The proposed framework explores random and controlled human movement, as well as implementing psychological conditions such as herd following and panicked states. We provide results analysis to compare evacuation speed under various egress methods, allowing for decision making when using the suite for training purposes. The outcome of this work is available on a public repository to serve the DEVS community, researchers, and public safety authorities interested in emergency evacuation simulations. [ABSTRACT FROM AUTHOR]

This paper presents a Cellular Automata (CA) based model that simulates movement of pedestrians with motion difficulties, such as elderly people and further focuses on how such groups can be guided within specific areas, as for example a nursing home. The model is originated by a virtual potential field. The aim of the model is to provide valuable information regarding the dynamics of their motion and to propose advanced layout settings of the corresponding places, in order to optimize the safety levels. Various scenarios are studied that include different layouts, presence of obstacles, group categorisation, crowd guiding and fire spreading. Simulation results confirm that the model can be proven a helpful tool, in order spatial parameters that affect evacuation time to be defined as well as personnel to be trained in guiding weak people. [ABSTRACT FROM AUTHOR]

This paper presents two complementary methods: an approach to compute a network data-set for indoor space of a building by using its two-dimensional (2D) floor plans and limited semantic information, combined with an optimal crowd evacuation method. The approach includes three steps: (1) generate critical points in the space, (2) connect neighbour points to build up the network, and then (3) run the optimal algorithm for optimal crowd evacuation from a room to the exit gates of the building. Triangulated Irregular Network (TIN) is used in the first two steps. The optimal evacuation crowd is not based on the nearest evacuation gate for a person but relies on optimal sorting of the waiting lists at each gate of the room to be evacuated. As an example case, a rectangular room with 52 persons with two gates is evacuated in 102 elementary interval times (one interval corresponds to the time for one step for normal velocity walking), whereas it would have been evacuated in not less than 167 elementary steps. The procedure for generating the customized network involves the use of 2D floor plans of a building and some common Geographic Information System (GIS) functions. This method combined with the optimal sorting lists will be helpful for guiding crowd evacuation during any emergency. [ABSTRACT FROM PUBLISHER]

Evacuation leaders (individuals guiding the crowd) can make crowd evacuation more efficient. Selecting their number and positions within the crowd is particularly important when the other evacuees are not familiar with the internal layout of the building. This paper investigates the effects of leadership on crowd evacuation in rooms with limited visibility range by an extended social force model. We find that, (i) For a large evacuees crowd, a small proportion of the evacuation leaders is already sufficient to guide the whole crowd efficiently, even if the visibility range of the room is very limited. And the smaller the crowd size, the larger the proportion of the leaders is needed to achieve a satisfactory evacuation guidance. (ii) The optimal proportion or number (i.e., the proportion or number that is necessary for guiding the crowd) of the leaders in an evacuees crowd to achieve a satisfactory guidance is related to the visibility range of the room and the distribution range of the evacuees crowd. (iii) Leadership is not always positive to the crowd evacuation. It may have a negative effect on crowd evacuation when the visibility range of the room and the size of the evacuees crowd are large enough. The findings provide a new insight into the effects of leadership on crowd evacuation. [ABSTRACT FROM AUTHOR]

In the case of emergency situations, robotic systems can play a key role and save human lives in recovery and evacuation operations. To realize such a potential, we have to address many scientific and technical challenges encountered during robotic search and rescue missions. This paper reviews current state-of-the-art robotic technologies that have been deployed in the simulation of crowd evacuation, including both macroscopic and microscopic models used in simulating a crowd. Existing work on crowd simulation is analyzed and the robots used in crowd evacuation are introduced. Finally, the paper demonstrates how autonomous robots could be effectively deployed in disaster evacuation, as well as search and rescue missions.

In the emergency under smoke or gas, the visual field of pedestrians is limited, unreasonable evacuation guidance methods will affect the efficiency of evacuation, and even cause evacuation failure in serious cases. Therefore, the optimized evacuation guidance strategy is investigated in this study. First, a distance factor is introduced to modify the follow-up behavior of pedestrians, which solves the problem of leaders being blocked by pedestrians. Then, a reward grid-based leader initial position optimization method is proposed to ensure the safe guidance of pedestrians. By considering the density and distance factors comprehensively, the leader's position is theoretically available by calculation. Finally, a leader exit selection strategy based on evacuation urgency degree is proposed. The leaders select exits in order of evacuation urgency degree, thus ensuring a more balanced exit utilization. The simulation results show that the proposed model can improve the safety of evacuation, and reduce the evacuation time. • The follow-up behavior of pedestrians is modified by introducing a distance factor. • A reward grid-based leader location-allocation method is proposed to optimize the initial location of leaders. • An exit selection strategy for leaders based on evacuation urgency degree is proposed. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the crowd evacuation performance in a metro fire by using the limit state equation to describe the egress process. The limit state equation is established by the available time margin in fire evacuation, which comprises the evacuee's response time, behaviour time and movement time to an exit. Here, the available time margin in a fire evacuation is determined by the duration of time the smoke takes to exceed the evacuee's respiration level, the time that the smoke is detected by fire alarm and the time that the evacuee needs to respond and move to an exit during evacuation. Further, Monte Carlo simulation approach has been employed to integrate the fatality rates and the probabilities of occurrence of different scenarios in a typical metro in Xiaobailou station of station-Tianjin Line 1. Through this case study, it is shown that the evacuee's response time, behaviour time and movement time to exits can be integrated in a stochastic process model. [ABSTRACT FROM AUTHOR]

In all the living organisms, the self-preservation behaviour is almost universal. Even the most simple of living organisms, like slime mould, is typically under intense selective pressure to evolve a response to ensure their evolution and safety in the best possible way. On the other hand, evacuation of a place can be easily characterized as one of the most stressful situations for the individuals taking part on it. Taking inspiration from the slime mould behaviour, we are introducing a computational bio-inspired model crowd evacuation model. Cellular Automata (CA) were selected as a fully parallel advanced computation tool able to mimic thePhysarum’s behaviour. In particular, the proposed CA model takes into account while mimicking thePhysarumforaging process, the food diffusion, the organism’s growth, the creation of tubes for each organism, the selection of optimum tube for each human in correspondence to the crowd evacuation under study and finally, the movement of all humans at each time step towards near exit. To test the model’s efficiency and robustness, several simulation scenarios were proposed both in virtual and real-life indoor environments (namely, the first floor of office building B of the Department of Electrical and Computer Engineering of Democritus University of Thrace). The proposed model is further evaluated in a purely quantitative way by comparing the simulation results with the corresponding ones from the bibliography taken by real data. The examined fundamental diagrams of velocity–density and flow–density are found in full agreement with many of the already published corresponding results proving the adequacy, the fitness and the resulting dynamics of the model. Finally, several realPhysarumexperiments were conducted in an archetype of the aforementioned real-life environment proving at last that the proposed model succeeded in reproducing sufficiently thePhysarum’s recorded behaviour derived from observation of the aforementioned biological laboratory experiments. [ABSTRACT FROM PUBLISHER]

Behavioral modification using active instructions is a promising interventional method to optimize crowd evacuations. However, existing research efforts have been more focused on eliciting general principles of optimal behavior than providing explicit mechanisms to dynamically induce the desired behaviors, which could be claimed as a significant knowledge gap in crowd evacuation optimization. In particular, we propose using dynamic distance-keeping instructions to regulate pedestrian flows and improve safety and evacuation time. We investigate the viability of using Model Predictive Control (MPC) techniques to develop a behavioral controller that obtains the optimal distance-keeping instructions to modulate the pedestrian density at bottlenecks. System Identification is proposed as a general methodology to model crowd dynamics and build prediction models. Thus, for a testbed evacuation scenario and input–output data generated from designed microscopic simulations, we estimate a linear AutoRegressive eXogenous model (ARX), which is used as the prediction model in the MPC controller. A microscopic simulation framework is used to validate the proposal that embeds the designed MPC controller, tuned and refined in closed-loop using the ARX model as the Plant model. As a significant contribution, the proposed combination of MPC control and System Identification to model crowd dynamics appears ideally suited to develop realistic and practical control systems for controlling crowd motion. The flexibility of MPC control technology to impose constraints on control variables and include different disturbance models in the prediction model has confirmed its suitability in the design of behavioral controllers in crowd evacuations. We found that an adequate selection of output disturbance models in the predictor is critical in the type of responses given by the controller. Interestingly, it is expected that this proposal can be extended to different evacuation scenarios, control variables, control systems, and multiple-input multiple-output control structures. • System Identification for modeling Crowd Dynamics. • Model Predictive Control for behavioral modification. • Distance-keeping instructions to optimally control pedestrian flows. • Output disturbance models, a trustworthy ally of MPC control of pedestrians crowds. [ABSTRACT FROM AUTHOR]

As one of the most common self-organizing phenomena in social systems, queueing has been attracting a lot of interest. Understanding the local interaction mechanism in queueing behaviors is a critical issue in the field of crowd dynamics. However, most studies ignore the heuristic decision during queueing processes. Even less is known about the effect of queueing behaviors on the collective movement. Therefore, an extended social force queueing model is proposed, which is based on vision and morality. Guided by visual and moral information, the desired speed and direction are heuristically adjusted in the self-driven force. Numerical simulations indicate that our model constructs a more realistic and detailed framework for the interpretation of pedestrian queueing. This model successfully predicts the emergence of the "detours" phenomenon, which is beneficial for reducing crowd pressure. Furthermore, our model may provide guidance for crowd management in safety science and navigation in autonomous robots. • A queueing behavior-based social force model for crowd evacuation is proposed. • Vision and morality information are incorporated to achieve a queueing motion. • Self-organized phenomenon appeared is in agreement with empirical observations. • The queuing behavior apparently reduces the local pressure that indicates risk. [ABSTRACT FROM AUTHOR]

Small groups are a derivative of multiple social structures and relationships. Researchers have found that in natural disasters or other emergencies, people often escape as a social group. Based on this research background, we conducted an evacuation experiment to study the effect of this behavioral patterns of small groups on crowd evacuation. A total of 60 pedestrians were selected by extracting their trajectories, individual walking distances, evacuation times, and group shape. Then, we calculated and analyzed average speed and evacuation entropy. The results indicated that the presence of small groups inhibit crowd evacuation efficiency, especially when the proportion of small groups reached 30%. However, when above 30%, this degree of inhibition showed a decreasing trend, which may be caused by the regular convergence of small group members. It was also observed that although the evacuation time slightly increased when the group percentage reached 40%, but the overall evacuation became more orderly. We also observed the side-by-side structure and triangular structure of small groups in the experiment. This study deepens our understanding of crowd evacuation dynamics, reveals more information about pedestrian behavior, and proposes effective crowd guidance strategies. • The mixed crowd evacuation experiments were conducted. • Evacuation entropy was introduced and applied. • Evacuation routes and shortest path were quantified. • Side-by-side behavior and triangular patterns of behavior were observed. [ABSTRACT FROM AUTHOR]