GPU-ACCELERATED CROWD SIMULATION WITH USER-GUIDANCE AND MULTI-LEVEL UNCERTAINTY

A long-standing rule for evaluating the realism and robustness of the crowd simulation is whether the simulations are capable of avoiding the congestion as well as maintaining free agent-wise collision. Although a few methods solved this problem in some speci c case, no overall method has been explored. This paper proposes a new approach to simulate large-scale crowd behavior with real-world properties and without obvious artifacts. Specifi cally, we devised a lightweight user-interaction scheme to combine the navigation field and continuum crowd method. Also, the two-level uncertainty model is imposed onto the above crowd dynamic system to simulate non-goal driven behavior. All of the computations are accelerated by using GPU. Through our experiments and comparisons, we demonstrates the advantages of our approach.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Houston

Year dc:date.issued

2013

Author dc:creator

• Cheng, Xiao 1985-

Advisor dc:contributor.advisor

• Deng, Zhigang

Committee members dc:contributor.committeemember

• Chen, Guoning
• Qiu, Jingmei

• Heterogeneous crowd simulation
• Two-level uncertainty model
• Non-goal-driven navigation field
• Local collision avoidance

Statement dc:rights

• The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/10657/1238

OAI identifier oai:identifier

oai:uh-ir.tdl.org:10657/1238