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Spatiotemporal Trajectories of Pedestrian Mobility at the Train Station: evidence of 24 million trajectories
(Springer Nature, 2024-11-20) Apeltauer, Tomáš; Uhlík, Ondřej; Apeltauer, Jiří; Juřík, Vojtěch
Understanding pedestrian movement remains crucial for designing efficient and safe transportation structures such as terminals, stations, or airports. The significance of conducting a granular analysis in pedestrian mobility dynamics research is evident in refining crowd behavior modeling. It is essential for gaining insights into potential terminal layouts, crowd management strategies, and evacuation procedures, all of which enhance safety and efficiency. In this context, we offer an original empirical dataset of more than 24,000,000 samples of trajectory spatial movement at traffic terminals in Havlíčkův Brod and Pardubice, Czech Republic. The dataset was collected using a high-resolution camera system installed at the railway station. Subsequently, algorithmic post-processing was applied to extract anonymous data on the spatial movement of recorded pedestrians. Thanks to this dataset, researchers can delve into the distances between pedestrians in a transportation terminal, considering factors such as group composition, group-to-group distances, and walking speed.
Virtual reality exposure effect in acrophobia: psychological and physiological evidence from a single experimental session
(Springer Nature, 2024-07-15) Varšová, Kristína; Szitás, Dagmar; Janoušek, Oto; Jurkovičová, Lenka; Bartošová, Kateřina; Juřík, Vojtěch
In recent years, virtual reality (VR) has gained attention from researchers in diverse fields, particularly in therapy of phobias. Currently, virtual reality exposure therapy therapy (VRET) is considered a promising cognitive-behavioral therapy technique. However, specific psychological and physiological responses of VR users to virtual exposure in such a context are still only vaguely explored. In this experimental study, we mapped VR exposure in a height environment in people with a moderate fear of heights–acrophobia. Thirty-six participants were divided into experimental and control groups–with and without psychological guidance during exposure. Participants' subjective level of anxiety was examined, and objective physiological response was captured via heart rate variability (HRV) measurement. Psychological assessments recorded an anticipated rise in participant anxiety following exposure to height; nevertheless, no distinctions were observed in self-reported anxiety concerning psychological guidance. Notably, objective physiological measures revealed that VR exposure prompts physiological responses akin to real-world scenarios. Moreover, based on the analysis of heart rate variability, participants who received psychological guidance were identified as better at compensating for anxiety compared to those without such support. These findings support VRET as a promising tool for psychotherapy and advocate for psychological guidance as beneficial in reducing anxiety and managing stress during exposure. The results may help improve our understanding of anxiety during exposure to phobic stimuli.
Real-time RSET prediction across three types of geometries and simulation training dataset: A comparative study of machine learning models
(Elsevier, 2024-05-24) Uhlík, Ondřej; Okřinová, Petra; Tokarevskikh, Artem; Apeltauer, Tomáš; Apeltauer, Jiří
Agent-based evacuation models provide useful data of the evacuation process, but they are not primarily designed for use during an emergency. The paper aims to test predicting RSET using a surrogate ML model trained on a simulation dataset with 60 samples. A total of 9 machine learning algorithms were tested on 3 simple geometries: bottleneck, stairway and walkway. A set of 7 spatial features was used to train the surrogate models. The results showed a relatively good ability of Artificial Neural Network to learn in scenarios involving bottlenecks and stairways, with an R2: 0.99 on the testing dataset. In the walkway scenario, all models experienced a significant drop in performance, with Gradient Boost performing the best (R2: 0.92). The paper demonstrated ability to generalize effectively in bottleneck-type tasks with training on a relatively small dataset containing spatial parameters obtainable in real-time from camera systems.
DoE Approach to Setting Input Parameters for Digital 3D Printing of Concrete for Coarse Aggregates up to 8 mm
(MDPI, 2023-04-27) Vespalec, Arnošt; Podroužek, Jan; Koutný, Daniel
This paper is primarily concerned with determining and assessing the properties of a cement-based composite material containing large particles of aggregate in digital manufacturing. The motivation is that mixtures with larger aggregate sizes offer benefits such as increased resistance to cracking, savings in other material components (such as Portland cement), and ultimately cost savings. Consequently, in the context of 3D Construction/Concrete Print technology (3DCP), these materials are environmentally friendly, unlike the fine-grained mixtures previously utilized. Prior to printing, these limits must be established within the virtual environment's process parameters in order to reduce the amount of waste produced. This study extends the existing research in the field of large-scale 3DCP by employing coarse aggregate (crushed coarse river stone) with a maximum particle size of 8 mm. The research focuses on inverse material characterization, with the primary goal of determining the optimal combination of three monitored process parameters-print speed, extrusion height, and extrusion width-that will maximize buildability. Design Of Experiment was used to cover all possible variations and reduce the number of required simulations. In particular, the Box-Behnken method was used for three factors and a central point. As a result, thirteen combinations of process parameters covering the area of interest were determined. Thirteen numerical simulations were conducted using the Abaqus software, and the outcomes were discussed.
Experimental study on time dependent behaviour of coarse aggregate concrete mixture for 3D construction printing
(Elsevier, 2023-04-20) Vespalec, Arnošt; Podroužek, Jan; Boštík, Jiří; Miča, Lumír; Koutný, Daniel
This experimental study analyses coarse aggregate-containing and coarse aggregate-free materials from the perspective of additive manufacturing. The primary objective is to identify, through a series of experiments, the fundamental equations that characterise material behaviour at early ages in order to formulate a digital material model. During the research, a previously unreported phenomenon, namely the contradictory development of Young's modulus and cohesion, was observed. In addition, the sensitivity of buildability to changes in material properties was discussed and demonstrated with a motivating example using a spatiotemporal simulation of 3Dprinted concrete.

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