Road traffic management based on self-load-balancing approach

Abstract

Traffic congestion is one of the most challenging problems for nowadays cities. Several contributions mainly based on V2V (Vehicle-to-Vehicle) communication have been published, but most of them have never been applied due to their communication related problems and costs. In this article, a novel cost-effective approach is introduced inspired by social life of insects where direct (V2V) communication does not exist anymore. Vehicles are equipped with devices that perform simple tasks, but their interactions with the environment through RSUs (Road Side Units) allow the creation of an intelligence which notifies drivers about congested road segments to avoid them. We call this emerging behavior self-load balancing. Description of the fundamentals of this approach and its performance are detailed in this work.

Keywords

• Congestion detection
• Traffic management
• Traffic data optimization
• Emergent intelligence
• Density estimation
• Collective intelligence