xv

xiv

49 Figure 1.3.6 Hudson Yards Rendering by KPF, 2019

By Kohn Pedersen Fox (KPF), “Hudson Yards,” accessed December 19, 2019, https://www.kpf.com/projects/hudson-yards.

51 Figure 1.3.7 “An abstract model of how an engine might be put together”

By Björn Nilson and Martin Söderberg, “Game Engine Architecture,” (May 26, 2007): 3-6, accessed December 19, 2019, http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.459.9537&rep=rep1&type=pdf.

53 Figure 1.3.8 Grand Theft Auto 3, DMA Design, 2001

From AndromedaDude, trimmed by Author, “Grand Theft Auto III Gameplay (Playstation 2),” YouTube, 10:39, accessed December 19, 2019, https://www.youtube.com/watch?v=jONTvpvj7DM.

53 Figure 1.3.9 The Witcher 3, CD Projekt, 2015

From Im Qith, trimmed by Author, “The Witcher 3, Entering Novigrad (No Commentary),” YouTube, 8:09, accessed December 19, 2019, https://www.youtube.com/watch?v=MTrxkDLi6sg.

55 Figure 1.3.10 Rendering a frame from Vray

By Jordivdm, trimmed by Author, “FullHD 3D VRay Render at I7-5820k 6 Cores (12 Virtual Cores),” YouTube, 0:58, accessed December 19, 2019, https://www.youtube.com/watch?v=rjvimjwhams.

55 Figure 1.3.11 Rendering Frames from Unreal Engine 4

Screen-captured by Author.

57 Figure 1.3.12 Ray tracing

By Henrik, “File:Ray trace diagram.svg,” This Diagram Illustrates the Ray Tracing Algorithm for Rendering an Image, April 12, 2008, Wikimedia Commons, accessed December 19, 2019, https://commons.wikimedia.org/wiki/File:Ray_trace_diagram.svg.

57 Figure 1.3.13 Rasterization

From “Rasterization: A Practical Implementation,” Scratchapixel, accessed December 19, 2019, https://www.scratchapixel.com//lessons/3d-basic-rendering/rasterization-practical-implementation.

58 Figure 1.3.14 CPU vs GPU Processing

From Gino Baltazar, “CPU vs GPU in Machine Learning,” September 13, 2018, Oracle Data Science Blog, accessed December 19, 2019, https://blogs.oracle.com/datascience/cpu-vs-gpu-in-machine-learning.

59 Figure 1.3.15 Texture Baking utilizes normal maps to preserve detail without the additional polygons

By fra3point, “Total Baker - Texture Baking System,” Unity Forum, accessed December 19, 2019, https://forum.unity.com/threads/total-baker-texture-baking-system.546341/.

61 Figure 1.3.16 A traditional desktop setup with a monitor and various input devices such as mouse and keyboard, game controller, and joysticks

By WeazelBear, “I Built My Own Live Edge Desk out of Teak. I Hope You All like It. Album in Comments,” Reddit, accessed December 19, 2019, https://www.reddit.com/r/battlestations/comments/7wlsp6/i_built_my_own_live_edge_desk_out_of_teak_i_hope/.

61 Figure 1.3.17 Possible VR setup with various trackers for interactive inputs

From “Fully immersive VR Entertainment Solutions,” Cyberith, accessed December 19, 2019, https://www.cyberith.com/entertainment/.

61 Figure 1.3.18 Architectural Rendering by HOK

From Ken Pimentel, trimmed by Author, “HOK on Architectural Visualization: Aggregate, Iterate, Communicate,” Unreal Engine, accessed December 19, 2019, https://www.unrealengine.com/en-US/spotlights/hok-architectural-visualization-aggregate-iterate-communicate.

63 Figure 1.4.1 Massive

From Film Radar, trimmed by Author, “Special Effects in The Lord of the Rings: The Essence of Movie Magic,” YouTube, 12:08, accessed December 18, 2019, https://www.youtube.com/watch?v=p6M8Yem5j0s&vl=en.

63 Figure 1.4.2 Golaem

By Golaem, trimmed by Author, “Golaem Crowd 4: Take Control of Your Crowds,” YouTube, 3:17, accessed December 19, 2019, https://www.youtube.com/watch?v=rr6tDBeNEv0.

63 Figure 1.4.3 Miarmy

From Basefount, trimmed by Author, “Miarmy 3 Crowd Simulation DEMO 8,” YouTube, 3:12, accessed December 19, 2019, https://www.youtube.com/watch?v=3wjCwtc_-hk.

65 Figure 1.4.4 Oasys mass motion

By TheOasysSoftware, trimmed by Author, “Oasys Software - MassMotion, The World’s Most Advanced Crowd Simulation Software,” YouTube, 2:30, accessed December 19, 2019, https://www.youtube.com/watch?v=dR5G5SNI5T4.

65 Figure 1.4.5 A crowd Visualization Tool in Autodesk 3ds Max

From sanvfx, trimmed by Author, “Creating Crowd Simulation in 3ds Max,” YouTube, 23:09, accessed December 19, 2019, https://www.youtube.com/watch?v=h-PMBi8gze4&t=454s.

Part 2 | Technical Research

71 Figure 2.1.1 Various wave patterns seen on-top of the ocean surface

From Alex Green, “An Aerial Birds Eye Shot Of The Ocean and Waves,” YouTube, 0:10, accessed December 25, 2019, https://www.youtube.com/watch?v=1jUnZ4VnoD4.

71 Figure 2.1.2 Video showing phantom traffic jam

From New Scientist, trimmed by Author, “Shockwave Traffic Jams Recreated for First Time,” YouTube, 0:39, accessed December 25, 2019, https://www.youtube.com/watch?v=Suugn-p5C1M.

71 Figure 2.1.3 This crowded concert shows how the interaction between each individual human produces various wave patterns throughout the entire crowd.

From Australian Concert And Entertainment Security Pty Ltd, trimmed by Author, “Crowd Wave Surge Example,” YouTube, 4:56, accessed December 25, 2019, https://www.youtube.com/watch?v=BgpdmAtbhbE&t=8s.

73 Figure 2.1.4 Snowflakes

By Wilson Bentley, “File:SnowflakesWilsonBentley.jpg,” Wikimedia Commons, accessed December 25, 2019, https://commons.wikimedia.org/wiki/File:SnowflakesWilsonBentley.jpg.

73 Figure 2.1.5 Termite mount

By Brian Voon Yee Yap, from Yewenyi, “File:Termite Cathedral DSC03570.jpg,” Wikimedia Commons, accessed December 25, 2019, https://commons.wikimedia.org/wiki/File:Termite_Cathedral_DSC03570.jpg.

73 Figure 2.1.6 Starling murmurations

From National Geographic, trimmed by Author, “Flight of the Starlings: Watch This Eerie but Beautiful Phenomenon | Short Film Showcase,” YouTube, 2:00, accessed December 25, 2019, https://www.youtube.com/watch?v=V4f_1_r80RY.

75 Figure 2.1.7 Rule 30 as introduced by Stephen Wolfram, 1983

From Eric W. Weisstein, “Rule 30,” Wolfram Math World, accessed December 25, 2019, http://mathworld.wolfram.com/Rule30.html.

76 Figure 2.1.8 250 iterations of Rule 30

From Eric W. Weisstein, “Rule 30,” Wolfram Math World.

79 Figure 2.2.1 Simulation Study Diagram

From Jerry Banks et al., Discrete-Event System Simulation (Upper Saddle River, NJ: Prentice Hall, 2001), 16.

83 Figure 2.2.2 The Lagrangian description calculates the position and velocity of the individual particles within the fluid

From “Descriptions of Fluid Flows,” accessed December 25, 2019, https://www.me.psu.edu/cimbala/Learning/Fluid/Introductory/descriptions_of_fluid_flows.htm.

83 Figure 2.2.3 The Eulerian description calculates the output velocities from the input velocities, in which the space inside the control volume is assumed to be completely filled as a continuous mass

From “Descriptions of Fluid Flows.”

85 Figure 2.2.4 Much like how humans interact with spaces, Autonomous Agents act within the simulation through its perception of the environment

By Stuart Russell and Peter Novig, “Intelligent Agents - Chapter 2,” from Artificial Intelligence: A Modern Approach, obtained from “Agents: Artificial Intelligence,” accessed December 25, 2019, https://www.doc.ic.ac.uk/project/examples/2005/163/g0516334/.

86 Figure 2.2.5 2-Dimensional Cellular Automata

From Hubert Klüpfel, “A Cellular automaton model for crowd movement and egress simulation,” (July 2003): 33-35, accessed December 26, 2019, https://www.researchgate.net/publication/29800160_A_Cellular_automaton_model_for_crowd_movement_and_egress_simulation.

86 Figure 2.2.6 Social Forces

From Dirk Helbing and Péter Molnár, “Social Force Model for Pedestrian Dynamics,” Physical Review E 51, no. 5 (1995): 15-17, doi:10.1103/PhysRevE.51.4282.

87 Figure 2.2.7 Reciprocal Velocity Obstacles

From Jur Van Den Berg, Ming Lin, and Dinesh Manocha, “Reciprocal Velocity Obstacles for Real-Time Multi-Agent Navigation,” 2008 IEEE International Conference on Robotics and Automation, (May 2008): 1928-1932, https://doi.org/10.1109/robot.2008.4543489.

87 Figure 2.2.8 Adaptive Roadmaps

From Avneesh Sud et al., “Real-time Navigation of Independent Agents Using Adaptive Roadmaps,” ACM SIGGRAPH 2008, (2008): doi:10.1145/1401132.1401207.

89 Figure 2.2.9 Centroidal Particles

From Omar Hesham and Gabriel Wainer, “Centroidal Particles for Interactive Crowd Simulation,” 2016 Summer Computer Simulation Conference (SCSC 2016), (2016): https://doi.org/10.22360/summersim.2016.scsc.012.

89 Figure 2.2.10 HiDAC

From Nuria Pelechano, Jan M. Allbeck, & Norman I. Badler, “Controlling Individual Agents in High-Density Crowd Simulation,” Proceedings of the 2007 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, (2007): 99-108, http://repository.upenn.edu/hms/210.

93 Figure 2.3.1 Three hierarchical layers of motion behaviors

From Craig W. Reynolds, “Steering Behaviors For Autonomous Characters,” Reynolds Engineering & Design, accessed October 17, 2019, http://www.red3d.com/cwr/steer/gdc99/.

93 Figure 2.3.2 Three hierarchical layers of human behaviors

Illustrated by Author.

94 Figure 2.3.3 Analog to Digital

Illustrated by Author.