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Spontaneous Wave Formation in Stochastic Self-Driven Particle Systems
- Source :
- SIAM Journal on Applied Mathematics. 81:853-870
- Publication Year :
- 2021
- Publisher :
- Society for Industrial & Applied Mathematics (SIAM), 2021.
-
Abstract
- Waves and oscillations are commonly observed in the dynamics of self-driven agents such as pedestrians or vehicles. Interestingly, many factors may perturb the stability of space homogeneous streaming, leading to the spontaneous formation of collective oscillations of the agents related to stop-and-go waves, jamiton, or phantom jam in the literature. In this article, we demonstrate that even a minimal additive stochastic noise in stable first-order dynamics can initiate stop-and-go phenomena. The noise is not a classic white one, but a colored noise described by a Gaussian Ornstein-Uhlenbeck process. It turns out that the joint dynamics of particles and noises forms again a (Gaussian) Ornstein-Uhlenbeck process whose characteristics can be explicitly expressed in terms of parameters of the model. We analyze its stability and characterize the presence of waves through oscillation patterns in the correlation and autocorrelation of the distance spacing between the particles. We determine exact solutions for the correlation functions for the finite system with periodic boundaries and in the continuum limit when the system size is infinite. Finally, we compare experimental trajectories of single-file pedestrian motions to simulation results.<br />Comment: Preprint, 20 pages, 5 figures
- Subjects :
- Physics
Particle system
Physics - Physics and Society
Interacting particle system
Applied Mathematics
Autocorrelation
Dynamics (mechanics)
FOS: Physical sciences
Markov process
Physics and Society (physics.soc-ph)
Space (mathematics)
90B20, 60K30, 82C22, 60H10, 34F05
01 natural sciences
Stability (probability)
Computer Science::Multiagent Systems
010101 applied mathematics
symbols.namesake
symbols
Mathematics::Metric Geometry
Statistical physics
0101 mathematics
Self driven
Subjects
Details
- ISSN :
- 1095712X and 00361399
- Volume :
- 81
- Database :
- OpenAIRE
- Journal :
- SIAM Journal on Applied Mathematics
- Accession number :
- edsair.doi.dedup.....e4dd129c5b7e3fc5e6ca042be60d05f8
- Full Text :
- https://doi.org/10.1137/20m1315567