A GPU-assisted hybrid model for real-time crowd simulations

Haciömeroğlu, Murat; Barut, Oner; Ozcan, Cumhur Yigit; Sever, Hayri

doi:10.1016/j.cag.2013.05.006

Cited by 10 publications

(8 citation statements)

References 16 publications

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“…Haciomeroglu et al [9] introduced a new concept as the second pass of their GPU clustering algorithm which resolves leadership chains of clustered agents and aggregates the properties of the cluster members. They implemented a method that utilizes GLSL geometry shader which emits vertices to the same positions calculated according to the cluster leaders and which also utilizes blending feature of the OpenGL to calculate the number of cluster members in addition to summation of their positions and velocities.…”

Section: Second Passmentioning

confidence: 99%

“…Hence, we developed a parallel algorithm consisting of only two rendering passes similar to the method proposed by Haciomeroglu et al [9] that determines the clusters of nearby agents walking with similar velocities using the GPU. The two rendering passes of the proposed algorithm are detailed in the following sections.…”

Section: Analyzing Possible Solutionsmentioning

confidence: 99%

“…In the second pass of our white pixel grouping method, we adopted the approach used by Haciomeroglu et al [9] with slight modifications. We employed a similar algorithm that runs on GLSL geometry shader which tracks each texel's leadership chain to group the texel with its real leader texel.…”

Section: Second Passmentioning

confidence: 99%

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Real-time collision-free linear trajectory generation on GPU for crowd simulations

Barut

Haciömeroğlu

2015

Vis Comput

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Crowd simulations are mostly employed to compose a background in the current scene. For such ambient crowds, it might be unnecessary to perform complex steering calculations. In this study, a steering-free crowd simulation which eliminates the computational cost arising from expensive steering maneuvers is presented. For this purpose, agents are assigned a linear trajectory that is guaranteed to be collision free before entering the simulation. These trajectories are calculated using readily available rendering pipeline of the GPU. To that end, existing agents' bounding discs are rendered in a spatio-temporal manner as each one forms a straight 3D tube and a projection from a selected initial position is captured. Using the blank areas (holes) in this image, it is possible to determine a suitable constant velocity (a goal position and a speed). In experiments, we not only assess three different methods to choose one of the candidate solutions, but also compare our approach with an existing work. Test results reveal that our technique gives better results in both populating an empty environment with agents quicker and reaching a higher maximum number of agents than the existing method.

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Section: Second Passmentioning

confidence: 99%

Section: Analyzing Possible Solutionsmentioning

confidence: 99%

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Real-time collision-free linear trajectory generation on GPU for crowd simulations

Barut

Haciömeroğlu

2015

Vis Comput

Self Cite

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“…Malinowski et al proposed to a parallel environment to simulate and visualize evacuation scenarios [Malinowski et al 2017], and other researchers used the concept of modular design [Malinowski and Czarnul 2019]. With the assistance of the GPU, the actual running speed of the environment is faster [Haciomeroglu et al 2013]. GPU instance mechanism and LOD (Levels of Detail) technology were used to achieve the real-time rendering of thousands of avatars, but the simulated avatars were homogeneous [Savoy et al 2015].…”

Section: Related Workmentioning

confidence: 99%

Towards Web3D-based Lightweight Crowd Evacuation Simulation

Piao

Xie

et al. 2020

The 25th International Conference on 3D Web Technology

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“…For example, Guy et al [7] and Golas et al [6] calculated distant agent cluster information for each individual and incorporated it into an agent-based system. Haciomeroglu et al [10] proposed a method to determine the cluster information globally at once which is then used by each individual in the simulation to determine the possible distant collisions. Still, all these studies assume that the distant agents keep their straight trajectories.…”

Section: Literature Reviewmentioning

confidence: 99%

A path-based multi-agent navigation model

Ozcan

Haciömeroğlu

2015

Vis Comput

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The quality of a crowd simulation model is determined by its agents' local and global trajectory efficiency. While an agent-based model can accurately handle the local trajectories, global decisions usually are handled by a global path planner. However, most of the global path planning techniques do not consider other agents and their possible paths and the future global flow in the environment. In this paper, we propose a composite system that takes future agent configurations into account via a modified A* algorithm to create a global path plan and combines the global path plan with a local navigation model. We show that the agents using the proposed model intelligently plan their paths based on the dynamic configuration of the environment. In order to balance the performance vs. trajectory quality trade-off, we propose a hierarchical grid structure and discuss its effects on both trajectory quality and computational performance.

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A GPU-assisted hybrid model for real-time crowd simulations

Cited by 10 publications

References 16 publications

Real-time collision-free linear trajectory generation on GPU for crowd simulations

Real-time collision-free linear trajectory generation on GPU for crowd simulations

Towards Web3D-based Lightweight Crowd Evacuation Simulation

A path-based multi-agent navigation model

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