A Predictive Collision Avoidance Model for Pedestrian Simulation

Abstract

We present a new local method for collision avoidance that is based on collision prediction. In our model, each pedestrian predicts possible future collisions with other pedestrians and then makes an efficient move to avoid them. Experiments show that the new approach leads to considerably shorter and less curved paths, ensuring smooth avoidance behaviour and visually compelling simulations. The method reproduces emergent behaviour like lane formation that have been observed in real crowds. The technique is easy to implement and is fast, allowing the simulation in real time of crowds of thousands of pedestrians.

Authors
Ioannis Karamouzas
Peter Heil
Pascal van Beek
Mark H. Overmars
Resources
 

A Predictive Collision Avoidance Model for Pedestrian Simulation,
I. Karamouzas, P. Heil, P. van Beek, M. H. Overmars
Motion in Games (MIG 2009), Lecture Notes in Computer Science (LNCS), Vol. 5884, 2009
[pdf] [bib]
 

 

Motion Planning for Human Crowds: From Individuals to Groups of Virtual Characters,
I. Karamouzas 
Ph.D. thesis, Utrecht University, The Netherlands, 2012 
[pdf] [bib]
 

  

PAM Libary,
I. Karamouzas
C++ implementation of the Predictive Collision Avoidance Model
[code]
 


Virtual Environments

 



Interactions at crosswalks
[Movie]


 



Virtual Park Scenario
[Movie]

Thesis Results

 



Diagonal Crossing - 4way Intersection - Circle
[Movie]


Other Examples
 

Comparison with Helbing's Social Force Model
[Example1] [Example2] [Example3] [Example4]

 

Comparison with Reciprocal Velocity Obstacle
[Example1] [Example2]


Support
This research has been supported by the GATE project, funded by the Netherlands Organization for Scientific Research (NWO) and the Netherlands ICT Research and Innovation Authority (ICT Regie).
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