Now showing 1 - 2 of 2
ItemCollective movement of merging pedestrian crowdsShahhoseini, Zahra ( 2018)Modelling pedestrian crowd movement and behaviour has emerged in the recent years in the literature as a new research topic. This topic has become important to an increasing extent due to the growth of populations of urban areas and mass events as well as an increase in the frequency of crowd-related incidents in venues that host a large number of people. Emergency incidents are considered as infrequent occurrences with safety-related ramifications and probable high effect. Although some attempts of modelling and simulating pedestrian movement have been around for decades, this field of research has recently received an apparent boost in attention in a variety of disciplines, notably in transport. The research on this subject eventually intends to develop forecasts tools that could assist in planning and optimisation for evacuation situations by providing measures including total evacuation times for each given circumstance. This would facilitate planners and authorities with the useful information required for evaluating the efficiency of their evacuation strategies in terms of time takes to vacate venues, placing potentially problematic locations and identifying weaknesses in their venues and recommend measures that can expedite the discharge of individuals should normal or emergency evacuation arise. Applications of these prediction tools could range vastly from merely guiding occupants as to in what way they should behave and manage themselves in case of occurrence of an incident, to assessing the safe density rate of venues especially in large special events and mass gatherings, too complicated optimising the design of the environments in ways that best increase the efficiency with which individuals move. The interdisciplinary problem has drawn the attention of researchers in numerous fields such as applied physics, fire safety, mathematics, ergonomics and transport engineering. The most critical element of this practice is potentially the accurateness of modelling that is inextricably linked with the behaviour of humans and extent to which their behaviour can be replicated by the proposed models. Considering implications of evacuation prediction tools and models in terms of safety, it is of major importance to reduce the possibility of imprecise estimates that could possibly culminate in inaccurate designs or misguided management policies. In order to address the challenges involved in reproducing pedestrian crowd motion, broad research has been undertaken. As stated by literature, however, most of studies has centred on understanding a class of models which we refer to as “walking-behaviour” or “next-step” models. In contrast, there has been very little knowledge as to the understanding of a higher scale of pedestrian decision making which we refer to as “route/exit” choice. Implementation of some plausible criteria which can reproduce peoples’ exit decision in an egress situation while taking into account the dynamic changes of the exit characteristics would be part and parcel of any simulated evacuation from a geometrically complex facility. I state that the experimental information in this field of research has dropped behind the mathematical progressions and model specifications. Therefore, more extensive empirical research and experimental studies in this topic are required in order to bridge this existing gap. Also, by exploring the current empirical literature, it can be concluded that the research in this field has been distributed in a comparatively unbalanced way in terms of addressing a variety of factors influencing on humans’ movements pattern. More empirical insights have been obtained related to the walking behaviour of individuals, particularly in simple experimental layouts. However, the impact of space particularly complex architectural settings on individuals’ interactions are relatively less explored. investigating this effect experimentally pose additional levels of difficulty for data collection, data extraction and drawing behavioural insights. Whereas, it is evident that acquiring a precise and comprehensive understanding of this impact and developing behavioural models that are capable of capturing this effect is of paramount importance. This research is proposed to address some of the knowledge gaps we identified with respect to the impact of space on movement dynamics of human crowds under the various level of stress. To our knowledge, the literature lacks an extensive understanding as well as robust models of the effect of geometrical features of movement area on movement pattern of individuals for egress situation. Therefore, this study primarily aims to provide an understanding of this effect particularly presence of merging corridors on egress behaviour through the provision of data obtained from a vast number of experimentations which is called for in the literature. Novel conditions and experimental layouts are to be considered as well as an advanced micro-level/ macro-level analysis are to be performed to elicit individuals’ behaviour. In addition, we analyse and present the observed interactions between occupants and their surrounding environment in a way that could be utilised for various mathematical models and simulation tools. I investigate the problem utilising two sources of experimental observations: data gained from non-human experimentation and data extracted from field-type experiments in controlled laboratory conditions with human subjects. Animal experiments data was collected by utilising panicked ants as experimental subject evacuating from various conflicting layouts. The impact of physical factors of movement environments on dynamics of the crowd was imitated in real actions where occupants were required to interact with their surrounding areas while evacuating under various levels of emergency. Their movement pattern was extracted at the level of individuals from raw footage of pedestrians. Data obtained from both sets of experiments were analysed undertaking macroscopic and microscopic measurements. While the above-mentioned problem is the primary purpose of this research, as a second question, this proposed study also intends to investigate the effect of the level of emergency on evacuees’ discharge behaviour in terms of observing “faster is slower “phenomenon. There are some merely simulated approaches as well as experimentation with non-human subjects proposed in the literature suggesting “faster is slower “ phenomenon under an emergency condition, validation of which have been primarily impeded by the scarcity of reliable explanatory data. Furthermore, to our knowledge, the impact of architectural design of egress area particularly presence of merging corridors on evacuation behaviour of the crowd has been barely examined in connection with the level of vigour to evacuate. Although the scarcity of pertinent data will still hinder us to address this problem under the extreme level of emergency situations, this study proposes some experiments under which the effect of extreme conditions is to be explored to bring to light any potential difference between the impact of space on evacuees’ behaviour under normal and emergency conditions The connection recognized between the findings obtained from experimentation with non-human organisms and humans also provided motivating insights into how the influence of the presence of conflicting layouts particularly merging corridors on the collective movement of non-human organisms is similar to that effect on the motion of human subjects. This connection led to findings that not only did offer insight into the possible relevance of collective behaviour of non-human subjects to what human occupants do in escape scenarios.
ItemHumans’ decision-making during emergency evacuations of crowded environments: behavioural analyses and econometric modelling perspectivesHaghani, Milad ( 2017)Modelling evacuation behaviour of humans has become an increasingly important topic due to the growth of urban populations and mass gatherings as well as the increasing frequency of emergency incidents in environments that host large numbers of humans. Emergencies are relatively rare occurrences with high potential impact and safety-related implications. Thus, preparedness for them has the potential to save lives by preventing injuries during the evacuation process and accelerating the overall process and leading people to safety in the least possible amount of time. The research on this topic ultimately aims at developing predictions tools that could facilitate evacuation planning and optimisation by producing measures such as total evacuation times for each given condition. This would enable authorities and planners to evaluate the effectiveness of their evacuation policies, identify potentially problematic locations and vulnerabilities in their venues and propose measures that can accelerate the discharge of occupants should an incidents occurs in the environment. Such applications could range from simply advising occupants as to how they should conduct themselves in case of an incident, to estimating the safe occupancy rate of venues (particularly in mass gatherings and special events) and thus managing the demand accordingly, to optimising the architectural design of the environments in ways that best support the efficient discharge of occupants. The problem is interdisciplinary by nature and has attracted the attention of researchers in various fields, including ergonomics and fire safety, applied physics and mathematics, behavioural sciences and transport engineering. The problem at hand is also highly multifaceted and entails many aspects such as computational capacities and the versatility of the models. The most crucial component of such practice is arguably the accuracy of modelling that is inextricably linked with the humans’ behaviour element and how accurately it can be replicated by the models. Given the safety-related implications of evacuation models, it is of paramount importance to minimise the extent and likelihood of inaccurate estimates that could potentially culminate in misguided designs or suboptimal policies (contradicting the primary purpose for which such models are intended). Ensuring that the behaviour of evacuees in simulated practices are replicated accurately enough is, however, a highly challenging task. The modeller deals with a problem related to humans’ decision-making behaviour which is intrinsically complex, in addition to the fact that the behaviour is this context is particularly rare and is not observed on a day to day basis. This leaves modellers with a paucity of data for model development, calibration and verification purposes. Given that the human behaviour in emergencies is not yet well understood, more often than not, the modellers have resorted to formulating “intuitive” assumptions whose accuracy have yet to be scrutinised based on empirical observations. This has left a range of mysterious theoretical assumptions in this field of research largely unverified and thus subject to debate and scepticism. I argue that the empirical knowledge in this research field has lagged notably behind the theoretical advancements and model formulations, calling for more extensive empirical research in this field in order to bridge this gap. Furthermore, by analysing the existing empirical literature in this field, I argue that the research has been distributed in a relatively imbalanced way in terms of addressing various aspects of human behaviour relevant to this research area. More empirical knowledge has been acquired in relation to the aspects of behaviour that are more convenient in terms of data collection, namely the “walking behaviour” and momentary “collision avoidance” decisions of people. Whereas, higher levels of escape decision making like the directional wayfinding choices or choices of activities are in comparison far less understood. These less explored aspects of behaviour often entail a heightened cognitive load (compared to instantaneous and largely subconscious walking decisions) and pose additional levels of complexity for experimentation, data extraction and modelling. However, I argue in that gaining an accurate understanding of these aspects and developing models that can echo them adequately in the modelling process is at least as important as modelling the walking behaviour from a practical standpoint. In this study, I focused on modelling and understanding the directional (or wayfinding) choices of humans during evacuations that are often referred to as “tactical decisions”. The study is predominantly empirical. In carrying pout this study, a major underlying question was to choose the experimentation method that best suits this problem. As explained in the literature review chapter, I classified the data collection and experimentation techniques in this field to seven major categories, a number of which could be potentially used for the question in hand here. Each method offered certain advantages and disadvantages. I study the problem using two general sources of empirical observations: hypothetical-choice data and data extracted from controlled laboratory experiments with actual crowds (which I refer to as “realistic” choice experiments or often as “field-type laboratory” experiments). The hypothetical-choice data was simply gathered by generating fixed sets of directional choice scenarios, visualising them in the form of simple pictures and surveying a sample of subjects one by one. The choice scenario conceptualise trade-offs between “social factors” and “physical factors” of the environment and elicit the prioritisation of respondents between these factors. This decision trade-off was then imitated in a more realistic simulated evacuation experiment where decision makers had to interact with actual crowds in an actual confining environment for making escape decisions. Their decisions were extracted at the level of individuals using the video-analyses of the experiment footage. The choice data obtained from both contexts were structured in an identical way and were analysed using econometric choice modelling techniques. The findings of this study are two-fold, divided into behavioural findings and econometric-related findings. The analysis results provided novel insight into the escape behaviour of humans, allowing me to revisit a number of conventional theoretical assumptions and statistically test them based on empirical observations. In particular, I examined the assumption of “herding behaviour” and “social attraction and repulsion effects” deeply entrenched in the literature. The conclusion was that these assumptions did not perfectly hold true and could in least terms be regarded as overgeneralisations of complex behavioural phenomena that could affect the accuracy of our predictions. Also the disaggregate nature of our data allowed me to address in depth the question of individual differences in this context that had largely been downplayed by previous studies. The close connection established between the hypothetical and realistic choice data also provided interesting findings about how the responses that people state as to what they would do in hypothetical escape scenarios could actually materialise when they make the actual decisions in more realistic contexts. This connection led to findings that not only did offer insight into the possible relevance of the hypothetical choice methods (or virtual-reality experiments in more general terms) in this particular context (with major implications for choosing research directions for future studies in this field) but also could be of the interest of the researchers in the field of experimental economics and econometrics. The modelling practices reported in this study were performed while considering the prospect of the outcomes leading to practical applications. I intended the models reported in this study to be implementable to evacuation simulation tools. The models, as a result, were kept parsimonious and the parameters were kept fully generic. As a practical application of this study, these models were integrated with a social-force model of walking. This dual-layer model is capable of simulating crowd evacuation process in complex environments that entail the choice of direction. Given that the parameters of the directional choice model convey behavioural interpretations, the model has also the potential to provide behavioural insight into the evacuation behaviour from a system perspective (i.e. based on aggregate measures) through computer simulation and manipulation of the simulated behaviour through varying the level of these parameters. A preliminary analysis of this kind has also been reported in the thesis.