Implicit Methods for Equation-Free Analysis: Convergence Results and Analysis of Emergent Waves in Microscopic Traffic Models
arXiv:1301.6044 · doi:10.1137/130913961
Abstract
We introduce a general formulation for an implicit equation-free method in the setting of slow-fast systems. First, we give a rigorous convergence result for equation-free analysis showing that the implicitly defined coarse-level time stepper converges to the true dynamics on the slow manifold within an error that is exponentially small with respect to the small parameter measuring time scale separation. Second, we apply this result to the idealized traffic modeling problem of phantom jams generated by cars with uniform behavior on a circular road. The traffic jams are waves that travel slowly against the direction of traffic. Equation-free analysis enables us to investigate the behavior of the microscopic traffic model on a macroscopic level. The standard deviation of cars' headways is chosen as the macroscopic measure of the underlying dynamics such that traveling wave solutions correspond to equilibria on the macroscopic level in the equation-free setup. The collapse of the traffic jam to the free flow then corresponds to a saddle-node bifurcation of this macroscopic equilibrium. We continue this bifurcation in two parameters using equation-free analysis.
arXiv comment35 pages
References in corpus (6)
- Traffic and Related Self-Driven Many-Particle Systems
- Coarse Brownian Dynamics for Nematic Liquid Crystals: Bifurcation Diagrams via Stochastic Simulation
- Robust oscillations in SIS epidemics on adaptive networks: Coarse-graining by automated moment closure
- A stochastic optimal velocity model and its long-lived metastability
- Analysis of the accuracy and convergence of equation-free projection to a slow manifold
- Equation-free modeling of evolving diseases: Coarse-grained computations with individual-based models
Cited by in corpus (5)
- Data-driven Control of Agent-based Models: an Equation/Variable-free Machine Learning Approach
- GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws
- Noise reduction in coarse bifurcation analysis of stochastic agent-based models: an example of consumer lock-in
- Effects of periodic forcing on a Paleoclimate delay model
- Convergence of equation-free methods in the case of finite time scale separation with application to deterministic and stochastic systems