International Journal of Science , Engineering and Management (IJSEM)

Monthly Journal for Science , Engineering and Management

Volume3,April 2018,

Topic : Traffic Load Computation on Cluttered Road Scenes

Authors:V.S.Harilakshmi || P.Arockia Jansi Rani

Abstract:Automatic traffic load computation is an important aspect of today’s Intelligent Transportation Systems (ITSs). Computation of traffic load helps in better management of flow of traffic and thus can help in planning transportation infrastructure and related policy. Large urban areas are subjected to face a major problem of traffic congestion because of the increase in number of vehicles. Different techniques have been proposed to estimate the traffic load to combat traffic congestion. Most of the works detect the edge of vehicles and count the number of vehicles in the frame. The method of counting number of vehicles may give faulty results and inefficient in case of extremely overlapping vehicles in congested road. This paper proposes the method of calculating the traffic load levels based on the application of image processing techniques on the background segmented road patch. Traffic load levels are then estimated based on the careful investigation and mapping of the feature values. Proposed load computation algorithm based on segmentation of cluttered road scenes shows superior results when compared to the existing load computation algorithms. We measure the vehicle detection rate. This technique, based on video processing of traffic frames, result in about 71.65%, 81.13% and 84.19% of overall vehicle detection on cluttered roads. The technique proposed in this paper works well on cluttered roads at various weather conditions. The proposed load computation technique can be applied to better understand traffic patterns in unlaned, chaotic roads of developing countries..

Keywords: Image processing, Intelligent Transportation System (ITS), traffic congestion, traffic density.

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DOI: 01.1617/vol5/iss4/pid61834

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Editor Image

Dr.Muhammad Ishtiaq,
Mirpur University of
Science & Technology,
Mirpur, Azad Kasmir.

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ISSN(Online): 2456-1304

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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Journal Code : IJSEM
Electronic ISSN : 2456-1304
Impact Factor : 2.7
Frequency : Monthly
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