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Stochastic description of traffic flow

Alperovich, Timur and Sopasakis, Alexandros LU (2008) In Journal of Statistical Physics 133(6). p.1083-1105
Abstract
We propose a traffic model based on microscopic stochastic dynamics. We built a Markov chain equipped with an Arrhenius interaction law. The resulting stochastic process is comprised of both spin-flip and spin-exchange dynamics which models vehicles exiting, entering and interacting in a two-dimensional lattice environment corresponding to a multi-lane highway. The process is further equipped with a novel look-ahead type, anisotropic interaction potential which allows drivers/vehicles to ascertain local fluctuations and advance to new cells forward or sideways. The resulting vehicular traffic model is simulated via kinetic Monte Carlo and examined under both, typical and extreme traffic flow scenarios. The model is shown to correctly... (More)
We propose a traffic model based on microscopic stochastic dynamics. We built a Markov chain equipped with an Arrhenius interaction law. The resulting stochastic process is comprised of both spin-flip and spin-exchange dynamics which models vehicles exiting, entering and interacting in a two-dimensional lattice environment corresponding to a multi-lane highway. The process is further equipped with a novel look-ahead type, anisotropic interaction potential which allows drivers/vehicles to ascertain local fluctuations and advance to new cells forward or sideways. The resulting vehicular traffic model is simulated via kinetic Monte Carlo and examined under both, typical and extreme traffic flow scenarios. The model is shown to correctly predict both qualitative as well as quantitative traffic observables for any highway geometry. Furthermore it also captures interesting multi-scale phenomena in traffic flows after a simulated accident which lead to oscillatory, dissipating, traffic waves with different periods per lane. (Less)
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author
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Multi-lane traffic flow - Anisotropic look-ahead rule - Markov Chain - Spin-flip/spin-exchange dynamics - Arrhenius potential - Kinetic Monte Carlo
in
Journal of Statistical Physics
volume
133
issue
6
pages
1083 - 1105
publisher
Springer
external identifiers
  • scopus:57849103196
ISSN
1572-9613
DOI
10.1007/s10955-008-9652-6
language
English
LU publication?
no
id
5c20025a-89b4-4d7b-9799-73786b87da7d (old id 2201603)
date added to LUP
2011-12-30 14:09:30
date last changed
2017-01-01 04:52:04
@article{5c20025a-89b4-4d7b-9799-73786b87da7d,
  abstract     = {We propose a traffic model based on microscopic stochastic dynamics. We built a Markov chain equipped with an Arrhenius interaction law. The resulting stochastic process is comprised of both spin-flip and spin-exchange dynamics which models vehicles exiting, entering and interacting in a two-dimensional lattice environment corresponding to a multi-lane highway. The process is further equipped with a novel look-ahead type, anisotropic interaction potential which allows drivers/vehicles to ascertain local fluctuations and advance to new cells forward or sideways. The resulting vehicular traffic model is simulated via kinetic Monte Carlo and examined under both, typical and extreme traffic flow scenarios. The model is shown to correctly predict both qualitative as well as quantitative traffic observables for any highway geometry. Furthermore it also captures interesting multi-scale phenomena in traffic flows after a simulated accident which lead to oscillatory, dissipating, traffic waves with different periods per lane.},
  author       = {Alperovich, Timur and Sopasakis, Alexandros},
  issn         = {1572-9613},
  keyword      = {Multi-lane traffic flow - Anisotropic look-ahead rule - Markov Chain - Spin-flip/spin-exchange dynamics - Arrhenius potential - Kinetic Monte Carlo},
  language     = {eng},
  number       = {6},
  pages        = {1083--1105},
  publisher    = {Springer},
  series       = {Journal of Statistical Physics},
  title        = {Stochastic description of traffic flow},
  url          = {http://dx.doi.org/10.1007/s10955-008-9652-6},
  volume       = {133},
  year         = {2008},
}