English

Classification and Unification of the Microscopic Deterministic Traffic Models with Identical Drivers

Adaptation and Self-Organizing Systems 2015-10-07 v2 Soft Condensed Matter

Abstract

We show that all existing deterministic microscopic traffic models with identical drivers (including both two-phase and three-phase models) can be understood as special cases from a master model by expansion around well-defined ground states. This allows two traffic models to be compared in a well-defined way. The three-phase models are characterized by the vanishing of leading orders of expansion within a certain density range, and as an example the popular intelligent driver models (IDM) is shown to be equivalent to a generalized optimal velocity (OV) model. We also explore the diverse solutions of the generalized OV model that can be important both for understanding human driving behaviors and algorithms for autonomous driverless vehicles.

Keywords

Cite

@article{arxiv.1504.02186,
  title  = {Classification and Unification of the Microscopic Deterministic Traffic Models with Identical Drivers},
  author = {Bo Yang and Christopher Monterola},
  journal= {arXiv preprint arXiv:1504.02186},
  year   = {2015}
}

Comments

4+ pages, 4 figs, minor changes updated for the accepted version

R2 v1 2026-06-22T09:13:14.034Z