Adaptive self‐organization vs static optimization: A qualitative comparison in traffic light coordination

Abstract

Purpose

The purpose of this paper is to compare qualitatively two methods for coordinating traffic lights: a static optimization “green wave” method and an adaptive self‐organizing method.

Design/methodology/approach

Statistical results were obtained from implementing a recently proposed model of city traffic based on elementary cellular automata in a computer simulation.

Findings

The self‐organizing method delivers considerable improvements over the green‐wave method. Seven dynamical regimes and six phase transitions are identified and analyzed for the self‐organizing method.

Practical implications

The paper shows that traffic light coordination can be improved in cities by using self‐organizing methods.

Social implications

This improvement can have a noticeable effect on the quality of life of citizens.

Originality/value

Understanding how self‐organization obtains adaptive solutions for complex problems can contribute to building more efficient systems.

Citation

Gershenson, C. and Rosenblueth, D.A. (2012), "Adaptive self‐organization vs static optimization: A qualitative comparison in traffic light coordination", Kybernetes, Vol. 41 No. 3/4, pp. 386-403. https://doi.org/10.1108/03684921211229479