Name
Abstract | ||
|---|---|---|
Smart traffic lights control systems started to appear in use on our roads particularly in the metropolitan areas. The technology aims to smoothen the flow of vehicles within junctions with the least waiting time and queue length which are the most popular metrics of traffic lights system. In this type of control system, traffic lights scheduling, and duration have to be dynamically controlled, which needs an intelligent traffic control scheme. In this paper, a framework of applying Vehicle-to-vehicle communications (V2V), Vehicle-to-infrastructure (V2I), Vehicle-to-everything (V2X), Internet of things (IoT) and Artificial intelligent techniques (AI) in the context of traffic lights management and control in an Internet of Things environment is introduced. Also, the dynamic scheduling of traffic lights given the real-time data from road and vehicle embedded sensors is elaborated. The paper also integrated the mathematical methods with the Neuro-Fuzzy based traffic control system for taking an intelligent decision based on the present traffic flows. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/NILES50944.2020.9257874 | 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) |
Keywords | DocType | ISBN |
Smart Traffic lights,Neuro-fuzzy,ANFIS | Conference | 978-1-7281-8227-8 |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hanaa Abohashima | 1 | 0 | 0.34 |
| Mohamed S. Gheith | 2 | 0 | 0.34 |
| amr b eltawil | 3 | 4 | 8.52 |