Paper Info
Title
Urban Area Congestion Detection And Propagation Using Histogram Model
Abstract
Detecting congestion in urban areas is critical and creates a myriad of complications. Intelligent Transportation Systems (ITS), which are trending in recent years, are used by researchers to engage problems related to congestion and transportation. However, due to the open access in urban area structures, it is less feasible to handle rife data that is generated from vehicles and infrastructure. On the grounds, ITS demands a reliable methodology that uses the data's effectively to detect the congestion. In this paper, we present a novel congestion estimation model for urban areas that leads to predict the congestion propagation. It uses a histogram-based model on a window time basis to make the data transfer substantially minimum and keep the system robust. Due to its simplicity, it can be practically implemented in real time for any nature of roadways. Simulation results, with different scenarios, show that the proposed model is detecting the congestion estimation effectively and leads to predict the congestion propagation for the near future.
Year
Venue
Keywords
2016
2016 IEEE 84TH VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL)
ITS, Congestion Estimation, Histograms, Congestion Propagation
Field
DocType
ISSN
Histogram,Metre,Data transmission,Computer science,Transport engineering,Computer network,Real-time computing,Global Positioning System,Intelligent transportation system,Congestion detection,Urban area
Conference
2577-2465
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Hesham El-Sayed19919.59
Gokulnath Thandavarayan232.77