Studying the impact of trained staff on evacuation scenarios by agent-based simulation

Daniel Formolo*, Tibor Bosse, Natalie van der Wal

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


Human evacuation experiments can trigger distress, be unethical and present high costs. As a solution, computer simulations can predict the effectiveness of new emergency management procedures. This paper applies multi-agent simulation to measure the influence of staff members with diverse training levels on evacuation time. A previously developed and validated model was extended with explicit mechanisms to simulate staff members helping people to egress. The majority of parameter settings have been based on empirical data acquired in earlier studies. Therefore, simulation results are expected to be realistic. Results show that staff are more effective in complex environments, especially when trained. Not only specialised security professionals but, especially, regular workers of shopping facilities and offices play a significant role in evacuation processes when adequately trained. These results can inform policy makers and crowd managers on new emergency management procedures.

Original languageEnglish
Title of host publicationSocial Informatics - 10th International Conference, SocInfo 2018, St. Petersburg, Russia, September 25 – 28, 2018 - Proceedings
EditorsSteffen Staab, Olessia Koltsova, Dmitry I. Ignatov
PublisherSpringer - Verlag
Number of pages12
ISBN (Electronic)9783030011598
ISBN (Print)9783030011581
Publication statusPublished - 2018
Event10th Conference on Social Informatics, SocInfo 2018 - Saint-Petersburg, Russian Federation
Duration: 25 Sept 201828 Sept 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11186 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th Conference on Social Informatics, SocInfo 2018
Country/TerritoryRussian Federation


  • Agent-based model
  • Crowd management
  • Evacuation
  • Staff


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