realistic crowd simulation with density-based path planning
DESCRIPTION
Realistic Crowd Simulation with Density-Based Path Planning. Wouter G. van Toll Atlas F. Cook IV Roland Geraerts. ICT.OPEN / ASCI October 22nd, 2012. Introduction. Path planning in virtual environments (e.g. games) Global planning: find a main route - PowerPoint PPT PresentationTRANSCRIPT
Wouter G. van Toll
Atlas F. Cook IV
Roland Geraerts
Realistic Crowd Simulationwith Density-Based
Path Planning
ICT.OPEN / ASCIOctober 22nd, 2012
Realistic Crowd Simulation with Density-Based Path Planning
IntroductionPath 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
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Realistic Crowd Simulation with Density-Based Path Planning
Overview
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We use crowd density information for global planningStored in a navigation mesh (Explicit Corridor Map)
Planning algorithm: time-based A*
Periodic replanning
ResultsCharacters take detours around congested areas
Crowd spreads over different routes
Efficient: tens of thousands of characters in real-time
Realistic Crowd Simulation with Density-Based Path Planning
Sneak preview
Before: After:
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Realistic Crowd Simulation with Density-Based Path Planning
Preliminaries
Navigation Meshes / Crowd Density
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Realistic Crowd Simulation with Density-Based Path Planning
Navigation meshesCharacters need to find paths through an environment
Navigation graph: 1D edgesNot flexible enough for crowds
Navigation mesh: 2D polygonsGlobal 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?
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Realistic Crowd Simulation with Density-Based Path Planning
An exact and flexible navigation meshMedial axis
Closest-obstacle annotations
A* on the medial axis path
+ corridor
Shortest paths with clearance
Collision avoidance
Multi-layered environments
Dynamic updates
Explicit Corridor Map
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Realistic Crowd Simulation with Density-Based Path Planning
Fraction of a region Ri that is occupied by characters
Often in persons per m²
Often in levels and colors
For us: value ρi between 0 and 1
(allows multiple character sizes)
Practical studiesWhen the density is high,people walk more slowly
Density-speed function v(ρ) : [0,1] [0, vmax]
Time-based path planning?crowd density
avg.
wal
king
spe
ed
Crowd density
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F
D
E
CBA
Realistic Crowd Simulation with Density-Based Path Planning
Method
Density Map / Density-Based Path Planning
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Realistic Crowd Simulation with Density-Based Path Planning
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
Density map
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Realistic Crowd Simulation with Density-Based Path Planning
Density-based path planning
A* search on the medial axisA character wants a “fast path”, not necessarily the shortest
Each ECM edge ei has a density ρi
tmin(ei): traversal time at speed v(0) = vmax
tdens(ei): traversal time at speed v(ρi)
tdelay(ei) = tmin(ei) - tdens(ei)
cost(ei) = tmin(ei) + w • tdelay(ei)
Controlling the sensitivity to delaysw = 0: shortest path
w = 1: “fastest path” (Höcker et al., 2010)
w > 1: more eager to take detours
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Realistic Crowd Simulation with Density-Based Path Planning
ReplanningDensities 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 > D, assume ρ = 0
Path has a visible and an invisible part
Partial replanning: re-use invisible partsCharacter has moved
More points are visible
At a mutually invisible point, A* can stop
Speed vs. knowledge
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Realistic Crowd Simulation with Density-Based Path Planning
Results
Realistic Crowds in Real-Time
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Realistic Crowd Simulation with Density-Based Path Planning
Experimental resultsVarying the cost weight w
w = 0 congestions
w = 1, no replanning periodic effect
w = 1, replanning realistic crowd flow
longer but faster paths
w > 1 larger detours, indecisive crowd
Useful in other environments?
Varying the viewing distance1 - 2 ms in a large city
Real-time periodic replanningMulti-threading: steering 50K characters in 30 ms/frame
70 ms/frame left for e.g. replanning
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# path vertices
repl
anni
ng ti
me
D = ∞D = 350 mD = 0 m
Realistic Crowd Simulation with Density-Based Path Planning
Closing Comments
Conclusions / Future work
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Realistic Crowd Simulation with Density-Based Path Planning
ConclusionsThe 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 crowdsCharacters spread over routes
Characters avoid congestions
Emergent: global effects due to individual choices
(Still) real-time performance for large crowds
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Realistic Crowd Simulation with Density-Based Path Planning
Future workNew questions
Use flow information? (speed + direction)
Use actual visibility?
Event-based vs. periodic replanning
Plan with terrain information?
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Realistic Crowd Simulation with Density-Based Path Planning
More informationPoster
Contact [email protected]
http://people.cs.uu.nl/roland/
Questions?
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