Real-time road traffic awareness model based on optimal multi-channel self-organized time division multiple access algorithm. (February 2017)

• Record Type: Journal Article
• Authors: Hu, Qing; Xu, Linlin
• Is Part Of: Computers & electrical engineering. Volume 58(2017)
• Page Start: 299
• Page End: 309
• Publication Date: 2017-02
• Subjects: Awareness model -- Identification -- Road traffic status -- Time slot collision; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.07.004
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: A real-time road traffic awareness model based on the optimal multi-channel self-organized time division multiple access algorithm is proposed as a novel mode of Internet of Vehicles. A system based on the proposed model can provide the quasi-real-time road traffic conditions to drivers in any area without relying on any centers and roadside infrastructure. Time slot collision problem and identification capability of the proposed model are perfectly resolved. The system based on this model can cover a large area and identify sufficient vehicles to meet the drivers' requirement of obtaining road traffic conditions in real time. Abstract: Real-time road traffic awareness is a challenge in an intelligent transportation system or internet of vehicles. In this paper, we provide a real-time road traffic awareness model for vehicle drivers based on the optimal multi-channel self-organized time division multiple access algorithm. A system based on this model can be implemented in all kinds of road networks including urban and rural roads or highways and cover a large area. The results indicate that this system can identify more than 5000 vehicles within an identification radius of 40 km on rural roads or highways and more than 8000 vehicles within an identification radius of 8 km on urban roads. Simulation results show that a system based on this model can meet the drivers' requirement of obtaining road traffic status in real time. Graphical abstract: