Real time traffic congestion detection using images
Date
Authors
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Authors
Research Projects
Organizational Units
Computer Science—the theory, representation, processing, communication and use of information—is fundamentally transforming every aspect of human endeavor. The Department of Computer Science at Iowa State University advances computational and information sciences through; 1. educational and research programs within and beyond the university; 2. active engagement to help define national and international research, and 3. educational agendas, and sustained commitment to graduating leaders for academia, industry and government.
History
The Computer Science Department was officially established in 1969, with Robert Stewart serving as the founding Department Chair. Faculty were composed of joint appointments with Mathematics, Statistics, and Electrical Engineering. In 1969, the building which now houses the Computer Science department, then simply called the Computer Science building, was completed. Later it was named Atanasoff Hall. Throughout the 1980s to present, the department expanded and developed its teaching and research agendas to cover many areas of computing.
Dates of Existence
1969-present
Related Units
- College of Liberal Arts and Sciences (parent college)
Journal Issue
Is Version Of
Versions
Series
Department
Abstract
There is an increasing demand to utilize modern technology in the eld of transportation to help decrease congestion on roads so that proper measures can be pursued to facilitate lower travel times and an effective utilization of the transportation network. This project aims to develop a solution for real time detection of traffic congestion on a road. The solution captures images from the live feed of traffic cameras situated at various locations and runs a deep learning algorithm to detect whether an image shows traffic congestion. Using a set of these images and a persistence check, the application identifies the time congestion started to take place and the time it has ended. For the purposes of analysis, the solution also records videos of the detected incidents.