Obstacle Optimization for Panic Flow - Reducing the Tangential Momentum Increases the Escape Speed

A disastrous form of pedestrian behavior is a stampede occurring in an event involving a large crowd in a panic situation. To deal with such stampedes, the possibility to increase the outflow by suitably placing a pillar or some other shaped obstacles in front of the exit has been demonstrated. We present a social force based genetic algorithm to optimize the best design of architectural entities to deal with large crowds. Unlike existing literature, our simulation results indicate that appropriately placing two pillars on both sides but not in front of the door can maximize the escape efficiency. Human experiments using 80 participants correspond well with the simulations. We observed a peculiar property named tangential momentum, the escape speed and the tangential momentum are found to be negatively correlated. The idea to reduce the tangential momentum has practical implications in crowd architectural design.     

Experimental study of the behavioural mechanisms underlying self-organization in human crowds

In animal societies as well as in human crowds, many observed collective behaviours result from self-organized processes based on local interactions among individuals. However, models of crowd dynamics are still lacking a systematic individual-level experimental verification, and the local mechanisms underlying the formation of collective patterns are not yet known in detail. We have conducted a set of well-controlled experiments with pedestrians performing simple avoidance tasks in order to determine the laws ruling their behaviour during interactions. The analysis of the large trajectory dataset was used to compute a behavioural map that describes the average change of the direction and speed of a pedestrian for various interaction distances and angles. The experimental results reveal features of the decision process when pedestrians choose the side on which they evade, and show a side preference that is amplified by mutual interactions. The predictions of a binary interaction model based on the above findings were then compared with bidirectional flows of people recorded in a crowded street. Simulations generate two asymmetric lanes with opposite directions of motion, in quantitative agreement with our empirical observations. The knowledge of pedestrian behavioural laws is an important step ahead in the understanding of the underlying dynamics of crowd behaviour and allows for reliable predictions of collective pedestrian movements under natural conditions.     

Nest architecture and traffic flow: large potential effects from small structural features

1. Research on human pedestrian dynamics predicts that seemingly small architectural features of the surroundings can have large effects on the behaviour of crowds and the flow of pedestrian traffic, particularly when a crowd is panicked. This theoretical framework might usefully be applied to the study of collective movement within subterranean nests of social insects. 2. We examined the rate of egress from artificial nests by alarmed Linepithema humile ants. In accord with model predictions, but counter to intuition, we found that a partially obstructed exit enhanced the average rate of escape from the nest. 3. The study of traffic flows in subterranean nests is almost non‐existent, but it would be worth studying the effect of nest design elements on collective movements, given the great variety of nest forms among ants and termites.     

Computer Simulation of Leadership,Consensus Decision Making and Collective Behaviour in Humans

The aim of this study is to evaluate the reliability of a crowd simulation model developed by the authors by reproducing Dyer et al.''s experiments (published in Philosophical Transactions in 2009) on human leadership and consensus decision making in a computer-based environment. The theoretical crowd model of the simulation environment is presented, and its results are compared and analysed against Dyer et al.''s original experiments. It is concluded that the simulation results are largely consistent with the experiments, which demonstrates the reliability of the crowd model. Furthermore, the simulation data also reveals several additional new findings, namely: 1) the phenomena of sacrificing accuracy to reach a quicker consensus decision found in ants colonies was also discovered in the simulation; 2) the ability of reaching consensus in groups has a direct impact on the time and accuracy of arriving at the target position; 3) the positions of the informed individuals or leaders in the crowd could have significant impact on the overall crowd movement; and 4) the simulation also confirmed Dyer et al.''s anecdotal evidence of the proportion of the leadership in large crowds and its effect on crowd movement. The potential applications of these findings are highlighted in the final discussion of this paper.     

Disentangling the Impact of Social Groups on Response Times and Movement Dynamics in Evacuations

Crowd evacuations are paradigmatic examples for collective behaviour, as interactions between individuals lead to the overall movement dynamics. Approaches assuming that all individuals interact in the same way have significantly improved our understanding of pedestrian crowd evacuations. However, this scenario is unlikely, as many pedestrians move in social groups that are based on friendship or kinship. We test how the presence of social groups affects the egress time of individuals and crowds in a representative crowd evacuation experiment. Our results suggest that the presence of social groups increases egress times and that this is largely due to differences at two stages of evacuations. First, individuals in social groups take longer to show a movement response at the start of evacuations, and, second, they take longer to move into the vicinity of the exits once they have started to move towards them. Surprisingly, there are no discernible time differences between the movement of independent individuals and individuals in groups directly in front of the exits. We explain these results and discuss their implications. Our findings elucidate behavioural differences between independent individuals and social groups in evacuations. Such insights are crucial for the control of crowd evacuations and for planning mass events.     

Similar Crowd Behavior in Organisms of Vastly Different Body Size

Crowd behaviors can have large fitness consequences for social organisms. Here we ask if there are similarities in the crowd dynamics of organisms that differ in body size, manner of locomotion, cognitive abilities, and state of alarm. Existing models of human crowd behavior have not been tested for their generality across species and body size nor across routine and emergency movements. We explore this issue by comparing the traffic dynamics of humans and of Argentine ants (Linepithema humile) to the predictions of our own model which was designed to simulate pedestrian movement. Some parameter values in the model were directly measured on ants but others were allometrically scaled from the human values to ant values based on the body mass difference. The model, with appropriately scaled parameters, correctly predicted two important properties of crowd behaviour for both organisms in a variety of circumstances: the flow rates and the distribution of time headways between successive ants in the escape sequence. The ability of a model of human pedestrian dynamics to predict behaviours of ant aggregations through allometric scaling of some parameter values suggests that there are fundamental features of crowd behavior that transcend the biological idiosyncrasies of the organisms involved.     

Mutual information for the detection of crush

Fatal crush conditions occur in crowds with tragic frequency. Event organizers and architects are often criticised for failing to consider the causes and implications of crush, but the reality is that both the prediction and prevention of such conditions offer a significant technical challenge. Full treatment of physical force within crowd simulations is precise but often computationally expensive; the more common method of human interpretation of results is computationally "cheap" but subjective and time-consuming. This paper describes an alternative method for the analysis of crowd behaviour, which uses information theory to measure crowd disorder. We show how this technique may be easily incorporated into an existing simulation framework, and validate it against an historical event. Our results show that this method offers an effective and efficient route towards automatic detection of the onset of crush.     

The effect of visitors on the behavior of zoo-housed western lowland gorillas (Gorilla gorilla gorilla)

Primates, especially apes, are popular with the public, often attracting large crowds. These crowds could cause behavioral change in captive primates, whether positive, neutral, or negative. We examined the impact of visitors on the behavior of six western lowland gorillas (Gorilla gorilla gorilla), observing the troop over 6 weeks during high season (4.5 hr/day, 35 days, May–July 2016). We used focal scan sampling to determine activity budget and enclosure usage, and focal continuous sampling to identify bouts of anxiety-related behavior (visitor-directed vigilance, self-scratching, and aggression). Both daily zoo-entry numbers (V_GATE) and instantaneous crowds at the exhibit (V_DENSITY) were measured. Overall, V_GATE had little effect across behaviors. However, consistent with the more acute time frame of measurement, V_DENSITY was a better predictor of behavior; at high crowd volumes, we observed significant group-level changes in activity budget (increased inactivity, increased locomotion, and decreased environment-related behaviors), increase in some anxiety-related behaviors, and decreased enclosure usage. Although contributing similar effects, it could not be determined if crowd numbers, composition, or noise most affected the troop, nor any chronic effects of exposure to large crowds. Nevertheless, our findings suggest that measures to minimize the impacts of large crowds at the exhibit would be beneficial. Furthermore, we highlight potential discrepancies between common methods for measuring visitor numbers: V_GATE is less sensitive to detecting visitor effects on behavioral indices than V_DENSITY. Future studies should appropriately match the biological time frame of welfare indicators and visitor measures used to ensure the reliability of findings.     

A Bio-Inspired,Motion-Based Analysis of Crowd Behavior Attributes Relevance to Motion Transparency,Velocity Gradients,and Motion Patterns

The analysis of motion crowds is concerned with the detection of potential hazards for individuals of the crowd. Existing methods analyze the statistics of pixel motion to classify non-dangerous or dangerous behavior, to detect outlier motions, or to estimate the mean throughput of people for an image region. We suggest a biologically inspired model for the analysis of motion crowds that extracts motion features indicative for potential dangers in crowd behavior. Our model consists of stages for motion detection, integration, and pattern detection that model functions of the primate primary visual cortex area (V1), the middle temporal area (MT), and the medial superior temporal area (MST), respectively. This model allows for the processing of motion transparency, the appearance of multiple motions in the same visual region, in addition to processing opaque motion. We suggest that motion transparency helps to identify “danger zones” in motion crowds. For instance, motion transparency occurs in small exit passages during evacuation. However, motion transparency occurs also for non-dangerous crowd behavior when people move in opposite directions organized into separate lanes. Our analysis suggests: The combination of motion transparency and a slow motion speed can be used for labeling of candidate regions that contain dangerous behavior. In addition, locally detected decelerations or negative speed gradients of motions are a precursor of danger in crowd behavior as are globally detected motion patterns that show a contraction toward a single point. In sum, motion transparency, image speeds, motion patterns, and speed gradients extracted from visual motion in videos are important features to describe the behavioral state of a motion crowd.     

Group differences in captive gorillas’ reaction to large crowds

The impact of visitor crowd size on captive animal behaviour can be difficult to interpret in many institutions due to the lack of variation in crowd size over short periods of time. In attempts to compare greater variation in crowd size, animal behaviour is often compared over conditions that create additional confounds, such as day of week or season. Fluctuations in attendance over the holiday season at Disney's Animal Kingdom^® Theme Park provided an opportunity to examine the impact of variation in crowd size on gorilla behaviour without the confounds found in many other studies. Ten western lowland gorillas (Gorilla g. gorilla) in a bachelor group (n = 4) and a family group (n = 6) were observed over a period of 8 weeks in late 2005. Observations were classified into Large Crowd and Small Crowd days and a repeated-measures ANOVA procedure was conducted to determine the effects of crowd size and social group on gorilla behaviour patterns. Few overall differences were found in behaviour during the Large Crowd and Small Crowd conditions. However, similar to previous research, gorillas were less visible during the Large Crowd condition (F_1,8 = 14.15, P = 0.01). There was also an interaction of crowd size and group (F_1,8 = 7.58, P = 0.01), indicating the bachelor group of gorillas was more aggressive during the Large Crowd condition, whereas the family group showed no increase in aggression with large crowds. These results indicate the importance of providing complex enclosures with visual barriers to allow animals to move away from large crowds if they choose. Future research should focus on the individual characteristics of animals and enclosures that may contribute to behavioural differences in visitor–animal interaction research, as well as the proximate cues associated with behaviour change when exposed to large crowds.     

Traffic instabilities in self-organized pedestrian crowds

In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds.     

The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics

Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behaviour consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium-scale aggregated structures and their impact on crowd dynamics is still largely unknown. In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its “non-aerodynamic” shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange. These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.     

Distributed denial-of-service attacks against HTTP/2 services

HTTP/2 is the second major version of the HTTP protocol published by the internet engineering steering group. The protocol is designed to improve reliability and performance Such enhancements have thus delineated the protocol as being more vulnerable to distributed denial-of-service (DDoS) attacks when compared to its predecessor. Recent phenomenon showed that legitimate traffic or flash crowds could have high-traffic flow characteristics as seen in DDoS attacks. In this paper, we demonstrate that legitimate HTTP/2 flash crowd traffic can be launched to cause denial of service. To the best of our knowledge, no previous study has been conducted to analyse the effect of both DDoS as well as flash crowd traffic against HTTP/2 services. Results obtained prove the effect of such attacks when tested under four varying protocol-dependant attack scenarios.     

Lessons Learned from Crowdsourcing Complex Engineering Tasks

Crowdsourcing

Crowdsourcing is the practice of obtaining needed ideas, services, or content by requesting contributions from a large group of people. Amazon Mechanical Turk is a web marketplace for crowdsourcing microtasks, such as answering surveys and image tagging. We explored the limits of crowdsourcing by using Mechanical Turk for a more complicated task: analysis and creation of wind simulations.

Harnessing Crowdworkers for Engineering

Our investigation examined the feasibility of using crowdsourcing for complex, highly technical tasks. This was done to determine if the benefits of crowdsourcing could be harnessed to accurately and effectively contribute to solving complex real world engineering problems. Of course, untrained crowds cannot be used as a mere substitute for trained expertise. Rather, we sought to understand how crowd workers can be used as a large pool of labor for a preliminary analysis of complex data.

Virtual Wind Tunnel

We compared the skill of the anonymous crowd workers from Amazon Mechanical Turk with that of civil engineering graduate students, making a first pass at analyzing wind simulation data. For the first phase, we posted analysis questions to Amazon crowd workers and to two groups of civil engineering graduate students. A second phase of our experiment instructed crowd workers and students to create simulations on our Virtual Wind Tunnel website to solve a more complex task.

Conclusions

With a sufficiently comprehensive tutorial and compensation similar to typical crowd-sourcing wages, we were able to enlist crowd workers to effectively complete longer, more complex tasks with competence comparable to that of graduate students with more comprehensive, expert-level knowledge. Furthermore, more complex tasks require increased communication with the workers. As tasks become more complex, the employment relationship begins to become more akin to outsourcing than crowdsourcing. Through this investigation, we were able to stretch and explore the limits of crowdsourcing as a tool for solving complex problems.     

Learning and stabilization of altruistic behaviors in multi-agent systems by reciprocity

Optimization of performance in collective systems often requires altruism. The emergence and stabilization of altruistic behaviors are difficult to achieve because the agents incur a cost when behaving altruistically. In this paper, we propose a biologically inspired strategy to learn stable altruistic behaviors in artificial multi-agent systems, namely reciprocal altruism. This strategy in conjunction with learning capabilities make altruistic agents cooperate only between themselves, thus preventing their exploitation by selfish agents, if future benefits are greater than the current cost of altruistic acts. Our multi-agent system is made up of agents with a behavior-based architecture. Agents learn the most suitable cooperative strategy for different environments by means of a reinforcement learning algorithm. Each agent receives a reinforcement signal that only measures its individual performance. Simulation results show how the multi-agent system learns stable altruistic behaviors, so achieving optimal (or near-to-optimal) performances in unknown and changing environments. Received: 1 August 1997 / Accepted in revised form: 28 November 1997     

基于“风感”的紧凑型城市开放空间风环境实测和CFD模拟比对研究

城市开放空间的风场不仅影响微环境的"风感"舒适度还影响宏观尺度的城市气候。从景感生态学的角度出发,首先阐述"风感"的定义,总结了街道峡谷空间风场的基本规律和特点。运用Kestrel NK4500手持气象站对城市开放空间的风环境进行实测,采用CFD(Computational Fluid Dynamics)模拟软件Fluent 14.0对不含绿地的同一空间进行风环境模拟,通过两者的数据比对来研究紧凑型城市开放空间内绿地对行人高度风场的实际干扰程度。结果发现,紧凑型城市开放空间的"风感"受建筑和绿地空间布局的共同影响。当建筑高于绿地时,风场受建筑的控制;当林带高于建筑时,林带对风环境的影响程度受其疏密度影响。疏密度较高的常绿林带对风向和风速影响很大,而疏密度较低的林带会影响风速,对风向影响不大。影响风速的主要因素是空间围合所形成的空气域,相比实体、多孔介质,空气域对风的阻力要小的多。如铺装、草坪上方的通风廊道是影响行人高度层通风、导风的关键因素。紧凑型空间内的绿地在行人高度应保持通畅以保证通风,并通过建立平面和竖向上的通风、导风廊道体系,促进空气循环。     

Evacuation of Pedestrians with Two Motion Modes for Panic System

In this paper, we have captured an underlying mechanism of emergence of collective panic in pedestrian evacuations by using a modification of the lattice-gas model. We classify the motion of pedestrians into two modes according to their moods. One is gentle (mode I), the other is flustered (mode II). First, to research the cause for crowd, we fix the motion modes of pedestrians and increase the proportion of pedestrians with motion mode II (ρ_II). The simulation results show that the pedestrians with motion mode II are lack of evacuation efficiency and cause more casualties. Further, we use the SIS (susceptible-infective-susceptible) model to describe the spreading of the panic mood. The system can be in the high-mix state when the infection probability λ is greater than a fuzzy threshold. In addition, the distances S from wounded people to the exit are researched, the number of wounded people gets maximum at the internal S = 5 ∼ 10, which is independent of ρ_II and λ. This research can help us to understand and prevent the emergence of collective panic and reduce wounds in the real evacuation.     

Data-oriented analyses of ciliate foraging behaviors

Optimal foraging theory states that natural selection makes foragers efficient food harvesters and maximizing a colony’s energy intake. This study presumed that the ciliates foraging trajectories follow optimal foraging theory, verified the presumption and discover specific rules and patterns hidden in the ciliate’s trajectories data using methodologies of statistical, cluster analyses, and decision tree analysis. This study examined the foraging behaviors of ciliates by video recordings and quantitative analyses of movement trajectories under four nourishment conditions (low, medium, high, and highest concentrations). Similar biological studies adopt statistical analyses to certain locomotion indices to determine the responses of plankton to various aquatic environments. In addition to statistical analyses, cluster analysis was used in this study to confirm the observations of the statistical analyses. The statistical analysis and cluster analysis results in this study revealed two distinct groups of trajectories or behaviors, which matched the optimal foraging theory. Decision tree analysis was then applied to acquire objective information regarding foraging behaviors, and further detailed the foraging behaviors with explicit classification rules using locomotion indices. The production rules can play an alternative role to assess the sustainability of an aquatic environment in terms of algae concentration.     

个体运动的病毒传播行为模拟

提出了一个基于二维规则网格的SIS(Susceptible-Infected-Susceptible)动态疾病传播模型,并用元胞自动机方法进行计算机模拟,考查该模型中感染概率、治愈概率、人群密度及人群的流动对疾病传播的影响,结果表明,系统的稳态感染比例随感染概率和人群密度的增加而增大,随治愈概率的增加而减小,同等条件下流动人群比静止人群更容易传播疾病,根据这些研究结论最后给出了对应的疾病预防和控制措施。