80 research outputs found

    Parameter Calibration in Crowd Simulation Models using Approximate Bayesian Computation

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    Simulation models for pedestrian crowds are a ubiquitous tool in research and industry. It is crucial that the parameters of these models are calibrated carefully and ultimately it will be of interest to compare competing models to decide which model is best suited for a particular purpose. In this contribution, I demonstrate how Approximate Bayesian Computation (ABC), which is already a popular tool in other areas of science, can be used for model fitting and model selection in a pedestrian dynamics context. I fit two different models for pedestrian dynamics to data on a crowd passing in one direction through a bottleneck. One model describes movement in continuous-space, the other model is a cellular automaton and thus describes movement in discrete-space. In addition, I compare models to data using two metrics. The first is based on egress times and the second on the velocity of pedestrians in front of the bottleneck. My results show that while model fitting is successful, a substantial degree of uncertainty about the value of some model parameters remains after model fitting. Importantly, the choice of metric in model fitting can influence parameter estimates. Model selection is inconclusive for the egress time metric but supports the continuous-space model for the velocity-based metric. These findings show that ABC is a flexible approach and highlights the difficulties associated with model fitting and model selection for pedestrian dynamics. ABC requires many simulation runs and choosing appropriate metrics for comparing data to simulations requires careful attention. Despite this, I suggest ABC is a promising tool, because it is versatile and easily implemented for the growing number of openly available crowd simulators and data sets

    Effect of Grazing-Mediated Dimethyl Sulfide (DMS) Production on the Swimming Behavior of the Copepod Calanus helgolandicus

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    Chemical interactions play a fundamental role in the ecology of marine foodwebs. Dimethyl sulfide (DMS) is a ubiquitous marine trace gas that acts as a bioactive compound by eliciting foraging behavior in a range of marine taxa including the copepod Temora longicornis. Production of DMS can rapidly increase following microzooplankton grazing on phytoplankton. Here, we investigated whether grazing-induced DMS elicits an increase in foraging behavior in the copepod Calanus helgolandicus. We developed a semi-Automated method to quantify the effect of grazing-mediated DMS on the proportion of the time budget tethered females allocate towards slow swimming, typically associated with feeding. The pooled data showed no differences in the proportion of the 25 min time budget allocated towards slow swimming between high (23.6 ± 9.74%) and low (29.1 ± 18.33%) DMS treatments. However, there was a high degree of variability between behavioral responses of individual copepods. We discuss the need for more detailed species-specific studies of individual level responses of copepods to chemical signals at different spatial scales to improve our understanding of chemical interactions between copepods and their prey. © 1996-2013 MDPI AG

    Towards a Reference Database for Pedestrian Destination Choice Model Development

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    The move towards publishing research data openly has led to the formation of reference databases in many fields. The benefits of such resources are numerous, particularly in the development of models. While these exist in research on other aspects of pedestrian behaviour, no reference database is available for modelling pedestrian destination choice, the process by which pedestrians choose where they wish to visit next. This work seeks to construct such a database from the literature. The resulting data obtained are described and potential ways in which they could be used to calibrate a simple pedestrian destination choice model are presented. It contains four datasets that include destination choices for hundreds of pedestrians in settings ranging from university campuses and music festivals to highly structured stated preference surveys. A case study using one of these datasets to calibrate a simple pedestrian destination choice model is provided. These efforts highlight some general issues from creating and using reference data openly. Discussing these issues will hopefully guide the development of reference data and accelerate the development of accurate pedestrian destination choice models that can be applied generally

    The Effect of Social Groups and Gender on Pedestrian Behaviour Immediately in Front of Bottlenecks

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    A virtual experiment on pedestrian destination choice:the role of schedules, the environment and behavioural categories

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    Which locations pedestrians decide to visit and in what order drives circulation patterns in pedestrian infrastructure. Destination choice is understood to arise from individuals trading off different factors, such as the proximity and busyness of destinations. Here, a virtual experiment is used to investigate whether this behaviour depends on the layout of buildings, whether planned or imposed destination schedules influence decisions and whether it is possible to distinguish different choice behaviour strategies in pedestrian populations. Findings suggest that virtual experiments can consistently elicit a range of destination choice behaviours indicating the flexibility of this experimental paradigm. The experimental approach facilitates changing the environment layout while controlling for other factors and illustrates this in itself can be important in determining destination choice. Destination schedules are found to be relevant both when imposed or generated by individuals, but adherence to them varies across individuals and depends on prevailing environmental conditions, such as destination busyness. Different destination choice behaviour strategies can be identified, but their properties are sensitive to the detection methods used, and it is suggested such behaviour classification should be informed by specific use-cases. It is suggested that these contributions present useful starting points for future research into pedestrian destination choice
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