Author: Matthew Funcke Supervisor: George Wells. Many, many, models.  All different Multiple Applications.  Entertainment Industry – Movies and Games.

Slides:



Advertisements
Similar presentations
A predictive Collision Avoidance Model for Pedestrian Simulation Author: Ioannis Karamouzas et al. Presented by: Jessica Siewert.
Advertisements

Controlling Individual Agents in High Density Crowd Simulation N. Pelechano, J.M. Allbeck and N.I. Badler (2007)
Ross Creed Temple University ICAR Workshop June 20, 2011.
Crowd Simulation Sai-Keung Wong. Crowd Simulation A process of simulating the movement of a large number of entities or characters. While simulating these.
Click to edit Master subtitle style Urban Mobility: A Data-Driven Approach Anders Johansson casa.ucl.ac.uk –
Outline Objectives Related Work Modeling Framework Model Application: Tawaf in Makkah Experimental Design Results Demo.
PEDESTRAIN CELLULAR AUTOMATA AND INDUSTRIAL PROCESS SIMULATION Alan Jolly (a), Rex Oleson II (b), Dr. D. J. Kaup (c) (a,b,c) Institute for Simulation and.
SimWalk PRO – Pedestrian simulation software for urban planning, evacuation and traffic management Savannah Simulations AG / 2010.
Cellular Automaton Evacuation Model Coupled with a Spatial Game Anton von Schantz, Harri Ehtamo
John S Gero Agents – Agent Simulations AGENT-BASED SIMULATIONS.
Presenter: Robin van Olst. Professor Ariel Shamir PhD. Alan Lerner Professor Daniel Cohen-Or Assistant Professor Yiorgos Chrysanthou.
Real-time crowd motion planning: Scalable Avoidance and Group Behavior (2008) Authors: Yersin, Maïm, Morini, Thalman Presented by: Jessica Siewert.
Conformance Checking by Capturing and Simulating Human Behavior in the Built Environment B. de Vries J.J. Jessurun.
Design and Decision Support Systems in Architecture, Building and Planning B. de Vries J.J. Jessurun.
Fitting models to data. Step 5) Express the relationships mathematically in equations Step 6)Get values of parameters Determine what type of model you.
Agent Based Modeling (ABM)
CS 282 Simulation Physics Lecture 1: Introduction to Rigid-Body Simulation 1 September 2011 Instructor: Kostas Bekris Computer Science & Engineering, University.
Design and Decision Support Systems in Architecture, Building and Planning Human Behaviour Simulation B. de Vries.
Cellular Automata Avi Swartz 2015 UNC Awards Ceremony.
Generic object detection with deformable part-based models
Dr. Sana’a Wafa Al-Sayegh
ALARA Planning and Teaching Tool Based on Virtual-Reality Technologies Di Zhang 1, X. George Xu 1, D. Hussey 2, S.Bushart 2 1 Nuclear Engineering and Engineering.
Applications of Multimedia
Ioannis Karamouzas, Roland Geraerts, Mark Overmars Indicative Routes for Path Planning and Crowd Simulation.
University of Central Florida Institute for Simulation & Training Title slide Continuous time-space simulations of pedestrian crowd behavior of pedestrian.
KIP TRACKING IN MAGNETIC FIELD BASED ON THE CELLULAR AUTOMATON METHOD TRACKING IN MAGNETIC FIELD BASED ON THE CELLULAR AUTOMATON METHOD Ivan Kisel KIP,
Presented: 11/05/09http://teamcore.usc.edu Agent-based Evacuation Modeling: Simulating the Los Angeles International Airport Milind Tambe, Jason Tsai,
A Multi-Agent Systems Based Conceptual Ship Design Decision Support System The Ship Stability Research Centre Department of Naval Architecture and Marine.
REAL-TIME NAVIGATION OF INDEPENDENT AGENTS USING ADAPTIVE ROADMAPS Avneesh Sud 1, Russell Gayle 2, Erik Andersen 2, Stephen Guy 2, Ming Lin 2, Dinesh Manocha.
Who is Oasys? Wholly owned by Arup Formed in 1976 to develop software for in-house and external use Most developers are engineers.
Course Title: M.M.T Chapter No: 01 “Introduction to Multimedia”
Situation Based Approach for Virtual Crowd Simulation Ph.D Preliminary talk Mankyu Sung.
Cellular Automata Martijn van den Heuvel Models of Computation June 21st, 2011.
2.03A Evolution of Virtual Reality 2.03 Explore virtual reality design and use A.
F 1 ← y = x 2 F 2 ← y = 0.05 sin(10 x) F1 → F2F1 → F2F1 → F2F1 → F2 F1 → F2F1 → F2F1 → F2F1 → F2 To manage the robot formation, a graphical user interface.
2.03A Evolution of Virtual Reality 2.03 Explore virtual reality design and use.
In our previous work, robots are treated as cells in a 1-dimensional cellular automaton (Mead et al. 2007). Each robot “cell state” consists of its distance.
Glossary of Technical Terms Cellular Automata: A regular array of identical finite state automata whose next state is determined solely by their current.
Controlling Individual Agents in High-Density Crowd Simulation
Crowds (and research in animation and games) CSE 3541 Matt Boggus.
Architectural Cue Model in Evacuation Simulation for Underground Space Chengyu Sun Phd Candidate Tongji University, China Prof. Bauke de Vries Supervisor.
Pedro R. Andrade Münster, 2013
Computer Animation Rick Parent Computer Animation Algorithms and Techniques Behavioral Animation: Crowds.
Computer Animation Rick Parent Computer Animation Algorithms and Techniques Behavioral Animation: Crowds.
Scalable Behaviors for Crowd Simulation Mankyu Sung Michael Gleicher Stephen Chenney University of Wisconsin- Madison
Objective Understand the relationship between digital media, society, and industry certifications. Course Weight : 2%
Sébastien Paris, Anton Gerdelan, Carol O’Sullivan {Sebastien.Paris, gerdelaa, GV2 group, Trinity College Dublin.
Crowds (and research in computer animation and games)
3.01 Explore multimedia systems, elements, and presentations.
Session 14: Hybrid Quantitative Modeling
Semi-Global Matching with self-adjusting penalties
2.03A Evolution of Virtual Reality
Application of NIST Technical Note 1822 to CA crowd dynamics models
Jef Caers, Xiaojin Tan and Pejman Tahmasebi Stanford University, USA
Crowds (and research in computer animation and games)
Workshop II UU Crowd Simulation Framework
Pedro R. Andrade Münster, 2013
Physics-based simulation for visual computing applications
Industrial Training Provider ,
Multiplication Facts.
VISWALK Pedestrian Modelling
Introduction to Multimedia
2.03A Evolution of Virtual Reality
3.01 Explore multimedia systems and elements.
Maze Design Presentation Questions
3.02 Demonstrate interactive multimedia presentations
3.01 Explore multimedia systems, elements, and presentations.
Source: Pattern Recognition Vol. 38, May, 2005, pp
© The Author(s) Published by Science and Education Publishing.
3.01 Explore multimedia systems and elements.
Presentation transcript:

Author: Matthew Funcke Supervisor: George Wells

Many, many, models.  All different Multiple Applications.  Entertainment Industry – Movies and Games  Evacuation simulation  Architectural optimisation  Crowd Control  Training – Military and Police  Teaching – Academic Save time and effort in the future.

 Three base methods Cellular Automata Rule-based Models Social Forces Models  Hybrid models eg: MassMotion Massive HiDAC

ALLSAFE Social Distances Helbing SF Aseri Blue & Adler MassMotion Massive Legion Simwalk Simulex PathFinder Paxport PEDFLOW SGEM HiDAC F.A.S.T. TIMTEX Helios Muramatsu Burstedde ABS CA Kebel et al. OpenSteer Maïm Exodus Reactive Navigation ACUMEN Crosses Autonomous Pedestrians Space Syntax Exit89 FPETool MASCM Floor Fields Quinn SF Wagoum Reynold Kirchner

 2 of each fundamental model  2 low complexity/quality models  2 medium complexity/quality models  2 high complexity/quality models

 Massive  Massmotion  HiDAC  Helbing  Quinn  Reynolds  OpenSteer  Generic CA  ABS Hybrid Models Social Forces Models Rule-based Models Cellular Automata HHHLMLMLMHHHLMLMLM

Generic Cellular Automaton ABS Cellular Automaton

Original Social ForcesParallelised Social Forces

MassMotion Massive Software

 Several proposed methods: ◦ Visual comparison

 Several proposed methods: ◦ Visual comparison ◦ Quantitative 4D histograms

 Several proposed methods: ◦ Visual comparison ◦ Quantitative 4D histograms ◦ Literature-based scoring:  Identify common comparison factors  Weight application  Score models  Apply equations  Compare specific models based on final scores  Generalise results

ApplicationBest Model MoviesMassive GamesOpenSteer or HiDAC EvacuationMassMotion ArchitectureMassMotion Crowd ControlMassMotion TrainingMassMotion TeachingGeneric CA

ApplicationBest Model MoviesMassive GamesOpenSteer or HiDAC EvacuationMassMotion ArchitectureMassMotion Crowd ControlMassMotion TrainingMassMotion TeachingGeneric CA

ApplicationBest Model MoviesOpenSteer GamesOpenSteer EvacuationQuinn ArchitectureQuinn Crowd ControlQuinn TrainingQuinn TeachingGeneric CA

 Commercial models are generally better.  Hybrid models are generally best.  Social forces if you need accuracy.  CAs when simplicity is essential.  Rule-based models for when looks and not accuracy matter.