Road traffic management based on self-load-balancing approach

• Published in: International journal for simulation and multidisciplinary design optimization Vol. 7; p. A9
• Main Authors: Adnane, Ahmed, Sadik, Mohamed, Talal, Saida, Medromi, Hicham, Bassir, David
• Format: Journal Article
• Language: English
• Published: Les Ulis EDP Sciences 2016; EDP sciences/NPU (China)
• Subjects: Collective intelligence; Communication; Congestion detection; Density estimation; Drivers; Emergent intelligence; Engineering Sciences; Humanities and Social Sciences; Insects; Load balancing; Methods and statistics; Traffic congestion; Traffic data optimization; Traffic management
• ISSN: 1779-627X; 1779-6288; 1779-6288
• DOI: 10.1051/smdo/2016008

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.