research-article

Generalized Microscropic Crowd Simulation using Costs in Velocity Space

Authors:

Wouter van Toll,

Fabien Grzeskowiak,

Axel López Gandía,

Florian Berton,

Julien Bruneau,

Beatriz Cabrero Daniel,

Alberto Jovane,

Julien PettréAuthors Info & Claims

I3D '20: Symposium on Interactive 3D Graphics and Games

Article No.: 6, Pages 1 - 9

https://doi.org/10.1145/3384382.3384532

Published: 05 May 2020 Publication History

Abstract

To simulate the low-level (‘microscopic’) behavior of human crowds, a local navigation algorithm computes how a single person (‘agent’) should move based on its surroundings. Many algorithms for this purpose have been proposed, each using different principles and implementation details that are difficult to compare.

This paper presents a novel framework that describes local agent navigation generically as optimizing a cost function in a velocity space. We show that many state-of-the-art algorithms can be translated to this framework, by combining a particular cost function with a particular optimization method. As such, we can reproduce many types of local algorithms using a single general principle.

Our implementation of this framework, named umans(Unified Microscopic Agent Navigation Simulator), is freely available online. This software enables easy experimentation with different algorithms and parameters. We expect that our work will help understand the true differences between navigation methods, enable honest comparisons between them, simplify the development of new local algorithms, make techniques available to other communities, and stimulate further research on crowd simulation.

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Cited By

Li YLiu JGuan XHou HHuang T(2025)Introducing anisotropic fields for enhanced diversity in crowd simulationThe Visual Computer10.1007/s00371-025-03831-xOnline publication date: 18-Feb-2025
https://doi.org/10.1007/s00371-025-03831-x
Gomez-Nogales GPrieto-Martin MRomero CComino-Trinidad MRamon-Prieto POlivier AHoyet LOtaduy MPettre JCasas D(2024)Resolving Collisions in Dense 3D Crowd AnimationsACM Transactions on Graphics10.1145/368726643:5(1-14)Online publication date: 6-Sep-2024
https://dl.acm.org/doi/10.1145/3687266
Talukdar BZhang YWeiss T(2024)Learning Crowd Motion Dynamics with CrowdsProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36513027:1(1-17)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3651302
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cover image ACM Conferences

I3D '20: Symposium on Interactive 3D Graphics and Games

May 2020

156 pages

ISBN:9781450375894

DOI:10.1145/3384382

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 05 May 2020

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I3D '20: Symposium on Interactive 3D Graphics and Games

May 5 - 7, 2020

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Cited By

Li YLiu JGuan XHou HHuang T(2025)Introducing anisotropic fields for enhanced diversity in crowd simulationThe Visual Computer10.1007/s00371-025-03831-xOnline publication date: 18-Feb-2025
https://doi.org/10.1007/s00371-025-03831-x
Gomez-Nogales GPrieto-Martin MRomero CComino-Trinidad MRamon-Prieto POlivier AHoyet LOtaduy MPettre JCasas D(2024)Resolving Collisions in Dense 3D Crowd AnimationsACM Transactions on Graphics10.1145/368726643:5(1-14)Online publication date: 6-Sep-2024
https://dl.acm.org/doi/10.1145/3687266
Talukdar BZhang YWeiss T(2024)Learning Crowd Motion Dynamics with CrowdsProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36513027:1(1-17)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3651302
Leblong EGrzeskowiak FThomas SDevigne LBabel MOlivier A(2024)Wheelchair Proxemics: interpersonal behaviour between pedestrians and power wheelchair drivers in real and virtual environmentsProceedings of the 30th ACM Symposium on Virtual Reality Software and Technology10.1145/3641825.3687709(1-12)Online publication date: 9-Oct-2024
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Martin JHoyet LPinsard EPaillat JPettré J(2024)Virtual Crowds Rheology: Evaluating the Effect of Character Representation on User Locomotion in CrowdsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.345618330:11(7008-7019)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TVCG.2024.3456183
Yin THoyet LChristie MCani MPettré J(2024)With or Without You: Effect of Contextual and Responsive Crowds on VR-based Crowd Motion CaptureIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.337203830:5(2785-2795)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1109/TVCG.2024.3372038
Cabrero-Daniel BAbdelkarim ABroberg A(2024)Digital Twins for Early Verification and Validation of Autonomous Driving Features: Open-source Tools and Standard Formats2024 IEEE Intelligent Vehicles Symposium (IV)10.1109/IV55156.2024.10588808(2477-2482)Online publication date: 2-Jun-2024
https://doi.org/10.1109/IV55156.2024.10588808
Vuong ANguyen TVu MHuang BBinh HVo TNguyen A(2024)HabiCrowd: A High Performance Simulator for Crowd-Aware Visual Navigation2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS58592.2024.10801823(5821-5827)Online publication date: 14-Oct-2024
https://doi.org/10.1109/IROS58592.2024.10801823
Allcock RSiebers P(2024)Crowd Health Encoding, for Crowd Simulations Using the Smoothed Particle Hydrodynamics Computational MethodAdvances in Social Simulation10.1007/978-3-031-57785-7_3(21-33)Online publication date: 21-Jul-2024
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Weiss T(2023)Fast Position-based Multi-Agent Group DynamicsProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/35855076:1(1-15)Online publication date: 16-May-2023
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