Road Traffic Parameters Estimation by Dynamic Scene Analysis: A Systematic Review

Road Traffic Parameters Estimation by Dynamic Scene Analysis: A Systematic Review

H. S. Mohana (Malnad College of Engineering, India) and M. Ashwathakumar (M. S. Ramaiah Institute of Technology, India)
Copyright: © 2010 |Pages: 15
DOI: 10.4018/jghpc.2010040106

Abstract

Traffic congestion and violation of traffic rules are very common in most of the road transport system. Continuous monitoring is becoming difficult. To improve the quality of road transport monitoring and control, the best possible alternative is machine vision. In this review, several works by researchers on traffic analysis are detailed, studied and reviewed critically for the purpose. Further, an attempt is made to classify the different road traffic analysis approaches available in the literature. Classification is based on principle used, algorithm adopted, techniques used, technology behind and other special considerations of the researchers.
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Traffic Flow

Traffic flow / Traffic flux is a generic term used to describe vehicle movement and volume over a transportation network. Two important parameters of traffic flow are average annual daily traffic (AADT) and Vehicle miles traveled.

These are long term flow patterns. Short term pattern includes daily or hourly parameters broken down to vehicle categories are also of high interest. This data can be acquired only with limited spatial extent with traditional techniques. The use of airborne / satellite imagery, however offers an excellent temporal and spatial resolution that can easily provide for sizable area of sight coverage at fast sampling rates. This definitely makes the whole system uneconomical and complex because of satellites and allied infrastructure. Answer to this data acquisition with digital cameras and analysis through the computer/machine vision technique/algorithms.

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