2021
DOI: 10.3233/aic-201576
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Safety perception and pedestrian dynamics: Experimental results towards affective agents modeling

Abstract: The modeling of a new generation of agent-based simulation systems supporting pedestrian and crowd management taking into account affective states represents a new research frontier. Pedestrian behaviour involves human perception processes, based on subjective and psychological aspects. Following the concept of pedestrian environmental awareness, each walker adapts his/her crossing behaviour according to environmental conditions and his/her perception of safety. Different pedestrian behaviours can be related t… Show more

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Cited by 2 publications
(2 citation statements)
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“…Proper features were evaluated on GSR, PPG and EMG pre-processed signals and considered to perform statistical inference and to feed machine learning algorithms. To deepen the topic for the in-vitro experiment, please refer to [16] while refer to [14] for the in-vivo data acquisition and process. The obtained results can be summarized as follows:…”
Section: Resultsmentioning
confidence: 99%
“…Proper features were evaluated on GSR, PPG and EMG pre-processed signals and considered to perform statistical inference and to feed machine learning algorithms. To deepen the topic for the in-vitro experiment, please refer to [16] while refer to [14] for the in-vivo data acquisition and process. The obtained results can be summarized as follows:…”
Section: Resultsmentioning
confidence: 99%
“…One of the research areas we started approaching is the one of agent simulation: the role emotions and affect have in modeling more realistic agent behaviors is gradually being investigated more and more, given the crucial part they play in the interactions a person has with the environment and with other people around him/her. For this reason, we started contemplating how to develop an affective agent model, namely, an affective multiagent system in which the agents’ behavior is also modeled relying on data collected through experiments, both in real-life or controlled laboratory scenarios [ 94 ]. Our final goal is to use the information we obtained through the physiological and psychological data analysis to define new variables to include in the agent model, new variables that aim to influence the agents’ behavior in a much more realistic way given how they are based on genuine reactions recorded from real people.…”
Section: Discussionmentioning
confidence: 99%