Self-organization models of urban traffic lights based on digital infochemicals. (March 2019)

• Record Type: Journal Article
• Authors: Zou, Guangyu; Yilmaz, Levent
• Is Part Of: Simulation. Volume 95:Number 3(2019)
• Page Start: 271
• Page End: 285
• Publication Date: 2019-03
• Subjects: Intelligent traffic lights -- digital infochemicals -- complex adaptive systems; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549718777615
• Languages: English
• ISSNs: 0037-5497

Abstract

This paper presents a self-organizing model to design effective traffic signaling strategies in order to reduce traffic congestion in urban areas. The proposed traffic signaling system is based on a pattern model of self-organization, i.e., digital infochemicals (DIs), which are analogous to chemical substances that convey information between interactive elements mediated via the environment. In the context of traffic systems, the DIs refer to information generated by vehicles and dissipated by the urban transportation infrastructure. Based on the exploratory analysis with one single intersection, we demonstrate that the DI-based strategy performs significantly better than both the fixed and trigger-based scheduling strategies in terms of queue length and waiting time under both fixed and dynamic traffic demands.