Self-Organizing Traffic Lights

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dc.creatorGershenson, Carlos
dc.date2004-11-30
dc.date2005-02-01
dc.date.accessioned2026-07-07T06:24:58Z
dc.date.available2026-07-07T06:24:58Z
dc.descriptionSteering traffic in cities is a very complex task, since improving efficiency involves the coordination of many actors. Traditional approaches attempt to optimize traffic lights for a particular density and configuration of traffic. The disadvantage of this lies in the fact that traffic densities and configurations change constantly. Traffic seems to be an adaptation problem rather than an optimization problem. We propose a simple and feasible alternative, in which traffic lights self-organize to improve traffic flow. We use a multi-agent simulation to study three self-organizing methods, which are able to outperform traditional rigid and adaptive methods. Using simple rules and no direct communication, traffic lights are able to self-organize and adapt to changing traffic conditions, reducing waiting times, number of stopped cars, and increasing average speeds.
dc.descriptionAdded new self-organizing method, compared with other methods, improved references
dc.identifierhttps://arxiv.org/abs/nlin/0411066
dc.identifierhttp://arxiv.org/abs/nlin/0411066
dc.identifierComplex Systems 16(1): 29-53. 2005
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/96720
dc.subjectAdaptation and Self-Organizing Systems
dc.subjectStatistical Mechanics
dc.subjectArtificial Intelligence
dc.subjectMultiagent Systems
dc.titleSelf-Organizing Traffic Lights
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