Characterisation of collective motion

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/226388
Download file(s):
File Description SizeFormat 
226388.pdfFulltext1.83 MBAdobe PDFView/Open
Type: Examensarbete för masterexamen
Master Thesis
Title: Characterisation of collective motion
Authors: Kjellman, Cecilia
Abstract: Self-organisation and emergence is a widespread and fundamental aspect of biological systems. Fish schools, insect swarms, bird ocks, colonies of bac- teria and human crowds are familiar examples of systems of very different levels of complexity and scale. To determine what governs interaction in the many biological systems is of importance. This thesis mainly focuses on comparing information usage for modelling collective motion, comparing using the distance to neighbouring individuals and time to collision. The thesis begins with analysing gathered sh school data in light of recent work in the eld of human crowd behaviour. The method uses a pair distribution function and a possible interaction energy to compare the two characteristics distance to neighbouring individuals and time to collision. The result differs in an interesting way from the original article on human crowd behaviour. The later part of the thesis describes existing collective behaviour models, and model adjustments, using either distance or time to collision as the most important attribute. Suitable existing measurements are touched upon. Fi- nally simulations using the included models are discussed but no conclusion regarding any decisive variable is made.
Keywords: Annan naturvetenskap;Energi;Other Natural Sciences;Energy
Issue Date: 2015
Publisher: Chalmers tekniska högskola / Institutionen för energi och miljö
Chalmers University of Technology / Department of Energy and Environment
Series/Report no.: Rapportserie för Avdelningen för fysisk resursteori : 2015:23
URI: https://hdl.handle.net/20.500.12380/226388
Collection:Examensarbeten för masterexamen // Master Theses



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.