Honors College Thesis


Believable automotive flocking model Public Deposited

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  • The high cost of manually producing background characters creates a demand for a way to automatically generate plausible behaviors. These background extras need to behave in a manner that is believable such that they do not distract the focus of the audience from the primary action occurring in the scene. Vehicles constrained to a road are the extras that are addressed in this project. Craig Reynolds’s work on automated bird flocking was a large inspiration for the general algorithms used in this project. The order of priorities in determining how to react to those objects around it are extremely similar between birds and drivers, the number one priority being not to run into anything. All of the rest of the preferences for specific types of behaviors have weights, each car containing unique preferences. With the proper distribution of personality traits, the resulting simulation produces believable traffic. This distribution has proven to be quite interesting. The most believable traffic results from a generally aggressive, impatient set of drivers.
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