Adaptive drivers in a model of urban traffic

TL;DR

This paper presents a lattice model of urban traffic where adaptive drivers optimize routes, revealing a phase transition between low and high-density traffic regimes, with counterintuitive behaviors at high densities.

Contribution

It introduces a novel lattice model incorporating adaptive driver behavior and analyzes its phase structure using simulations and mean-field theory.

Findings

Identifies a phase transition between low and high vehicle density regimes.

Adaptive drivers can perform worse than random drivers at high densities.

Provides analytical and numerical insights into traffic flow dynamics.

Abstract

We introduce a simple lattice model of traffic flow in a city where drivers optimize their route-selection in time in order to avoid traffic jams, and study its phase structure as a function of the density of vehicles and of the drivers' behavioral parameters via numerical simulations and mean-field analytical arguments. We identify a phase transition between a low- and a high-density regime. In the latter, inductive drivers may surprisingly behave worse than randomly selecting drivers.