Research Article
Traffic Saturation Detection using Hough Transform and VANET
@INPROCEEDINGS{10.4108/eai.24-11-2022.2329807, author={Dekpeltaki\^{e} Augustin Metouale Somda and Abdoulaye Sere}, title={Traffic Saturation Detection using Hough Transform and VANET}, proceedings={Proceedings of the 5th edition of the Computer Science Research Days, JRI 2022, 24-26 November 2022, Ouagadougou, Burkina Faso}, publisher={EAI}, proceedings_a={JRI}, year={2023}, month={5}, keywords={smart city hough transform traffic saturation vanet}, doi={10.4108/eai.24-11-2022.2329807} }- Dekpeltakié Augustin Metouale Somda
Abdoulaye Sere
Year: 2023
Traffic Saturation Detection using Hough Transform and VANET
JRI
EAI
DOI: 10.4108/eai.24-11-2022.2329807
Abstract
The main objective is to solve the problem of traffic congestion, using GPS (Global Positioning System) on board vehicles and servers in a control station, reducing the number of cameras to be deployed or additional hardware on the roads. This paper discusses the application of the Hough transformation method in VANET(Vehicular Ad-Hoc Network) to facilitate traffic congestion detection and monitoring. The VANET network allows sharing of safety information between vehicles to ensure the safety of road users. In response to the problem of traffic congestion and the increase in road accidents by vehicles, we designed and tested various traffic scenarios. We simulated the placement of RSUs (Road Side Units) in each scenario and analyzed the delay and packet delivery ratios (PDRs) in each scenario.
