By Topic

Vision Based Intelligent Traffic Management System

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Malhi, M.H. ; COMSATS Inst. of Inf. Technol., Lahore, Pakistan ; Aslam, M.H. ; Saeed, F. ; Javed, O.
more authors

Vision based intelligent traffic management system is a robust framework that manages the on road traffic flow in real time by estimating traffic density near traffic signals. We have proposed a simple yet efficient algorithm to calculate the number of vehicles at various signals on a road to efficiently manage the traffic by controlling traffic signals to avoid congestion and traffic jam. The proposed system works by detection of vehicles in video frames acquired by cameras installed on roads and then perform accurate counting of vehicles at the same time. Dynamic background subtraction technique and morphological operations for vehicle detection have been used to achieve better detection efficiency. In order to attain accurate vehicle count in least possible time, we have used Region of Interest based method for vehicle calculation. The proposed framework is designed and implemented in several simulation test cases. It is expected that this work will provide an insight into the design and development of traffic signaling based system and also serves as a basis for practical implementation of a computer vision technology in real-time environment. Furthermore, this work also contributes to new design schemes to increase traffic signaling system's intelligence.

Published in:

Frontiers of Information Technology (FIT), 2011

Date of Conference:

19-21 Dec. 2011