TY - GEN
T1 - A modular framework for adaptive agent-based steering
AU - Singh, Shawn
AU - Kapadia, Mubbasir
AU - Hewlett, Billy
AU - Reinman, Glenn
AU - Faloutsos, Petros
PY - 2011
Y1 - 2011
N2 - Next-generation steering algorithms will need to support thousands of believable individual agents, capable of steering in very challenging situations with low-latency reactions. In this paper we propose a steering framework that offers three key contributions: (a) It integrates several models of steering into a single steering decision, (b) it employs a novel space-time planning approach to allow agents to steer during complex local interactions, and (c) it varies the frequency of update of each component (phase) of the framework to drastically improve performance. We demonstrate the versatility and robustness of our framework using a large number of test cases. We also show that the frequency of updates for each phase of the framework can be " decimated" by a surprisingly large amount before resulting steering behaviors degrade. This technique achieves more than a 5× performance improvement, allowing the use of better, more costly algorithms for robust steering, while supporting thousands of agents with low-latency reactions in real-time.
AB - Next-generation steering algorithms will need to support thousands of believable individual agents, capable of steering in very challenging situations with low-latency reactions. In this paper we propose a steering framework that offers three key contributions: (a) It integrates several models of steering into a single steering decision, (b) it employs a novel space-time planning approach to allow agents to steer during complex local interactions, and (c) it varies the frequency of update of each component (phase) of the framework to drastically improve performance. We demonstrate the versatility and robustness of our framework using a large number of test cases. We also show that the frequency of updates for each phase of the framework can be " decimated" by a surprisingly large amount before resulting steering behaviors degrade. This technique achieves more than a 5× performance improvement, allowing the use of better, more costly algorithms for robust steering, while supporting thousands of agents with low-latency reactions in real-time.
KW - Autonomous agents
KW - Pedestrian simulation
KW - Steering behaviors
UR - http://www.scopus.com/inward/record.url?scp=79952715125&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952715125&partnerID=8YFLogxK
U2 - 10.1145/1944745.1944769
DO - 10.1145/1944745.1944769
M3 - Conference contribution
AN - SCOPUS:79952715125
SN - 9781450305655
T3 - Proceedings of the Symposium on Interactive 3D Graphics
SP - 141
EP - 150
BT - Symposium on Interactive 3D Graphics and Games, I3D'11
T2 - 2011 15th ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, I3D'11
Y2 - 18 February 2011 through 20 February 2011
ER -