The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Partitioning rectilinear figures into rectangles
CSC '88 Proceedings of the 1988 ACM sixteenth annual conference on Computer science
An algorithm to minimally decompose a rectilinear figure into rectangles (abstract only)
CSC '87 Proceedings of the 15th annual conference on Computer Science
Multidimensional binary search trees used for associative searching
Communications of the ACM
Spatial databases with application to GIS
Spatial databases with application to GIS
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Hierarchical Model for Real Time Simulation of Virtual Human Crowds
IEEE Transactions on Visualization and Computer Graphics
New Linear Node Splitting Algorithm for R-trees
SSD '97 Proceedings of the 5th International Symposium on Advances in Spatial Databases
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Agent-based human behavior modeling for crowd simulation
Computer Animation and Virtual Worlds - CASA'2008 Special Issue
Virtual Crowds: Methods, Simulation, and Control (Synthesis Lectures on Computer Graphics and Animation)
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Modeling and simulation of pedestrian behaviors in crowded places
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Transactions on computational science XII
A Computational Model of Emotions for Agent-Based Crowds in Serious Games
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Rectangular decomposition of binary images
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
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Crowd modeling and simulation has become a critical tool for understanding crowds and predicting their behaviours. This is accomplished by modelling the characteristics and behaviours of large groups of people, as well as their interactions. Agent-based crowd simulation may involve thousands of complex agents interacting in sophisticated ways, in close spatial proximity, with each other. A key challenge to the development of agent-based crowd simulation is the inherent complexity that is required to model all its necessary elements. A necessary feature of such a simulation is spatial indexing. This refers to the use of data structures to organize collections of simulation entities (e.g., agents and obstacles) in a manner which allows for efficient spatial querying. This is especially pertinent for large-scale crowd simulation with agents that sense their surrounding environment periodically, as the cost of spatial querying becomes computationally expensive if done naively. In this paper, we will describe our experience in improving the existing grid-based spatial indexing approach in our agent-based crowd simulation. Also, we will explore the integration of the adaptive spatial indices (e.g., R-tree and quad-tree) into our system. The performances of various spatial indexing techniques are examined in terms of efficiency and scalability.