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Analysis of the use of behavioral data from virtual reality for calibration of agent-based evacuation models
(Elsevier, 2023-03-03) Juřík, Vojtěch; Uhlík, Ondřej; Snopková, Dajana; Kvarda, Ondřej; Apeltauer, Tomáš; Apeltauer, Jiří
Agent-based evacuation modeling represents an effective tool for making predictions about evacuation aspects of buildings such as evacuation times, congestions, and maximum safe building capacity. Collection of real behavioral data for calibrating agent-based evacuation models is time-consuming, costly, and completely impossible in the case of buildings in the design phase, where predictions about evacuation behavior are especially needed. In recent years evacuation experiments conducted in virtual reality (VR) have been frequently proposed in the literature as an effective tool for collecting data about human behavior. However, empirical studies which would assess validity of VR-based data for such purposes are still rare and considerably lacking in the agent-based evacuation modeling domain. This study explores opportunities that the VR behavioral data may bring for refining outputs of agent evacuation models. To this end, this study employed multiple input settings of agent-based evacuation models (ABEMs), including those based on the data gathered from the VR evacuation experiment that mapped out evacuation behaviors of individuals within the building. Calibration and evaluation of models was based on empirical data gathered from an original evacuation exercise conducted in a real building (N=35) and its virtual twin (N=38). This study found that the resulting predictions of single agent models using data collected in the VR environment after proposed corrections have the potential to better predict real-world evacuation behavior while offering desirable variance in the data outputs necessary for practical applications.
Seasonal Variability of Resuspension
(EDP Sciences, 2022-11-04) Linda, Jakub; Köbölová, Klaudia; Uhlík, Ondřej; Pospíšil, Jiří; Apeltauer, Tomáš
Particulate air pollution in cities is caused by a variety of sources. One of the less-studied contributors is wind-induced particle resuspension. As the wind speed increases, particles are removed from surfaces. These particles cause an increase in the total concentration in the air. It is known that particles of 10-2.5 m in size can be resuspended (PM10-2,5). Modern emission monitoring in cities also allows the monitoring of fine particles of 10, 2.5 and 1 m in size. The size fractions can then be sorted into PM10-2,5, PM2,5-1 and PM1. When breathed in, particles of different sizes cause various serious health risks. This paper focuses on the identification of the resuspension process of different particle size fractions by a data processing method. Data measured by automatic emission monitoring are used. It is confirmed that the concentration increase can be dominated by the fraction PM10-2,5. However, a concentration increase of fractions PM2,5-1 and PM1 is also evident with increasing wind speed. Although the increase in the PM1 fraction is smaller than PM10-2,5, it is more severe due to the respiratory deposition dose. The resuspension of particles of different fractions has different behaviours during the year. PM10-2,5 particles are dominantly resuspended in the summer months. In winter, on the other hand, the proportion of PM2.5-1 and PM1 particles increases, which may be related to the heating season
Reverberation measurement set for the interrupted noise method
(IOP Publishing, 2021-12-21) Jun, David; Nespěšný, Ondřej
This paper describes the methodology of measuring the sound absorption coefficient in a reverberation room. For its purpose, a measuring set was created combining professional with widely available hardware suitable for acoustic reverberation measurements. For the measurement itself, the interrupted noise method was chosen based on the standard ČSN EN ISO 354. Measurement and evaluation of data take place using scripts written in the Python programming language. An effective measuring set was developed both in terms of operation during measurement and in terms of subsequent data processing, accessing and graphical presentation.
Case Study of Selected Nature Swimming Pools in the South Moravian Region
(Sciendo, 2021-12-23) Poloprutská, Tereza; Nováček, Michal; Oppeltová, Petra
Nature swimming pools are a sought-after alternative to conventional swimming pools. Their natural water purification system, without the need for chemicals, is beneficial to health and environmentally friendly. Designing such a nature swimming pool is a complex matter because it requires coordination of a number of effects, which can easily cause an imbalance in the entire system. This work uses the case study method to analyse the overall condition of three nature swimming pools in the South Moravian Region during the second half of the swimming pool operation season.
Classification of the socio-psychological aspects of protecting soft targets: A case study for evacuation of the railway terminals
(University of Žilina, 2021-01-12) Šplíchalová, Alena; Karásek, Tomáš; Apeltauer, Tomáš
Current crisis management approaches to protect soft targets make assumptions about average visitors/listeners/viewers or passengers. They do not give much consideration to impacts of diversity of potentially evacuated persons with regard to socio-psychological parameters/factors that may lead to practical problems and complications during the evacuation itself. At the same time, the soft target operators have various means of machine vision tools at their disposal, but do not use these records for more thorough analysis of evacuation planning needs. Based on this observation, the article identifies and analyzes the socio-psychological aspects that may significantly affect behavior and decisions of persons during the evacuation and thus total evacuation time.

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