Intelligent transportation algorithms for calculating quantitative road traffic parameters

Abstract

As society progresses, technology can be used in more different ways to improve the quality of life for its citizens. There is a growing need for traffic systems to improve, as human population and road usage have both been increasing over the past few decades.

While there has been research done into different processing techniques involved, it is also important to consider the financial cost of these different methods implemented. As such, research into techniques and algorithms with a lower cost of implementation is not only warranted, it could be highly beneficial.

This project aims to research the efficacy of implementing edge detection techniques on video footage that can be easily attained by laypeople. It also intends to test the vehicle classification algorithms designed, and to examine the effects of combining edge detection techniques to potentially obtain more accurate results. It will be implemented using Python.