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Wouter G. van Toll

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Title: MSc Thesis Presentation Subject: A navigation mesh for efficient density-based crowd simulation in multi-layered environments Author: Wouter van Toll – PowerPoint PPT presentation

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Title: Wouter G. van Toll


1
Realistic Crowd Simulationwith Density-Based
Path Planning
  • Wouter G. van Toll
  • Atlas F. Cook IV
  • Roland Geraerts

ICT.OPEN / ASCI October 22nd, 2012
2
Introduction
  • Path planning in virtual environments (e.g.
    games)
  • Global planning find a main route
  • Local planning variety, collision avoidance
  • Many characters at once crowd simulation
  • Problem in a crowd, short routes are not always
    good
  • Collision avoidance cannot solve everything
  • Other routes are unused

3
Overview
  • We use crowd density information for global
    planning
  • Stored in a navigation mesh (Explicit Corridor
    Map)
  • Planning algorithm time-based A
  • Periodic replanning
  • Results
  • Characters take detours around congested areas
  • Crowd spreads over different routes
  • Efficient tens of thousands of characters in
    real-time

4
Sneak preview
  • Before After

5
Preliminaries
  • Navigation Meshes / Crowd Density

6
Navigation meshes
  • Characters need to find paths through an
    environment
  • Navigation graph 1D edges
  • Not flexible enough for crowds
  • Navigation mesh 2D polygons
  • Global path sequence of polygons
  • Local planning during movement
  • Common in modern games / simulations
  • Crowd simulation has been solved!
  • Assumptions in the navigation mesh / crowd
  • General framework?

7
Explicit Corridor Map
  • An exact and flexible navigation mesh
  • Medial axis
  • Closest-obstacle annotations
  • A on the medial axis ? path
  • corridor
  • Shortest paths with clearance
  • Collision avoidance
  • Multi-layered environments
  • Dynamic updates

8
Crowd density
  • Fraction of a region Ri that is occupied by
    characters
  • Often in persons per m²
  • Often in levels and colors
  • For us value ?i between 0 and 1
  • (allows multiple character sizes)
  • Practical studies
  • When the density is high,people walk more slowly
  • Density-speed function v(?) 0,1 ? 0, vmax
  • Time-based path planning?

F
E
D
C
B
A
9
Method
  • Density Map / Density-Based Path Planning

10
Density map
  • ECM divides the environment into non-overlapping
    regions
  • Each region maps to an ECM edge
  • Each region stores its local density
  • Updated in real-time
  • Density of a region
  • ? Expected walking speed within the region
  • ? Expected traversal time of the edge
  • ? Expected delay

11
Density-based path planning
  • A search on the medial axis
  • A character wants a fast path, not necessarily
    the shortest
  • Each ECM edge ei has a density ?i
  • tmin(ei) traversal time at speed v(0) vmax
  • tdens(ei) traversal time at speed v(?i)
  • tdelay(ei) tmin(ei) - tdens(ei)
  • cost(ei) tmin(ei) w tdelay(ei)
  • Controlling the sensitivity to delays
  • w 0 shortest path
  • w 1 fastest path (Höcker et al., 2010)
  • w gt 1 more eager to take detours

12
Replanning
  • Densities change all the time
  • Characters should re-check their paths
  • We cannot see crowds that are far away
  • Density viewing distance D along the medial axis
  • A if the path length gt D, assume ? 0
  • ? Path has a visible and an invisible part
  • Partial replanning re-use invisible parts
  • Character has moved
  • More points are visible
  • At a mutually invisible point, A can stop
  • ? Speed vs. knowledge

13
Results
  • Realistic Crowds in Real-Time

14
Experimental results
  • Varying the cost weight w
  • w 0 ? congestions
  • w 1, no replanning ? periodic effect
  • w 1, replanning ? realistic crowd flow
  • ? longer but faster paths
  • w gt 1 ? larger detours, indecisive crowd
  • ? Useful in other environments?
  • Varying the viewing distance
  • 1 - 2 ms in a large city
  • Real-time periodic replanning
  • Multi-threading steering 50K characters in 30
    ms/frame
  • 70 ms/frame left for e.g. replanning

D 8
D 350 m
D 0 m
15
Closing Comments
  • Conclusions / Future work

16
Conclusions
  • The ECM navigation mesh serves as a density map
  • Non-overlapping, exact, always defined
  • Region densities map to edge speeds
  • Updated in real-time
  • Characters use density-based A
  • Short paths with little expected delay
  • Sensitivity to delay can be set
  • (Partial) replanning
  • Result More realistic crowds
  • Characters spread over routes
  • Characters avoid congestions
  • Emergent global effects due to individual
    choices
  • (Still) real-time performance for large crowds

17
Future work
  • New questions
  • Use flow information? (speed direction)
  • Use actual visibility?
  • Event-based vs. periodic replanning
  • Plan with terrain information?

18
More information
  • Poster
  • Contact us
  • W.G.vanToll_at_uu.nl
  • R.J.Geraerts_at_uu.nl
  • http//people.cs.uu.nl/roland/
  • Questions?
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