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A personality model for animating heterogeneous traffic behaviors

conference contribution
posted on 2014-01-01, 00:00 authored by Xuequan Lu, Z Wang, M Xu, W Chen, Z Deng
How to automatically generate realistic and heterogeneous traffic behaviors has been a much needed yet challenging problem for numerous traffic simulation and urban planning applications. In this paper, we propose a novel approach to model heterogeneous traffic behaviors by adapting a well-established personality trait model (i.e., Eysenck's PEN (psychoticism, extraversion and neuroticism) model) into widely used traffic simulation approaches. First, we collected a large amount of user feedback while users watch a variety of computer-generated traffic simulation video clips. Then, we trained regression models to bridge low-level traffic simulation parameters and high-level perceived traffic behaviors (i.e., adjectives according to the PEN model and the three PEN traits).We also conducted an additional user study to validate the effectiveness and usefulness of our approach, in particular, high correlation coefficients and the Pearson values between users' feedback and our model predictions prove the effectiveness of our approach. Furthermore, our approach can also produce interesting emergent traffic patterns including faster-is-slower effect and sticking-in-a-pin-wherever-there-is-room effect

History

Event

Computer Graphics Society. Conference (27th : 2014 : Houston, Tex.)

Volume

25

Issue

3-4

Series

Computer Graphics Society Conference

Pagination

361 - 371

Publisher

John Wiley & Sons

Location

Houston, Tex.

Place of publication

Chichester, Eng.

Start date

2014-05-26

End date

2014-05-28

ISSN

1546-4261

eISSN

1546-427X

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2014, John Wiley & Sons, Ltd.

Editor/Contributor(s)

N Magnenat-Thalmann, D Thalmann, T Kunii

Title of proceedings

CASA 2014 : Proceedings of the 27th Conference on Computer Animation and Social Agents 2014