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Adaptive Traffic Controller Based On Pre-Timed System

Journal from gdlhub / 2016-11-02 11:50:56
By : Freddy Kurniawan, Haruno Sajati, Okto Dinaryanto, Telkomnika
Created : 2016-03-01, with 1 files

Keyword : determine traffic density, standard deviation, intensity histogram, signal-timing plan, AVR microcontroller
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/2798

Adaptive traffic controller systems based on image processing have been developed widely. Nevertheless, in a developing country, the systems often could not be easily applied because all types of vehicle use the same road. Therefore, to overcome the problem, the new concept of the systems is proposed. The systems were developed from a pre-timed traffic controller system that based on AVR microcontroller. By default, the systems use the signal-timing plans to control the vehicle flow. To accommodate the traffic variations, a new method of vehicle detection has been built. The method calculated an intensity histogram standard deviation of the image representing a detection area to determine traffic density of each intersection lane. The systems modified the green-time of each lane based on the traffic density. The method could detect all types of vehicles and work properly in a day and a night time

Description Alternative :

Adaptive traffic controller systems based on image processing have been developed widely. Nevertheless, in a developing country, the systems often could not be easily applied because all types of vehicle use the same road. Therefore, to overcome the problem, the new concept of the systems is proposed. The systems were developed from a pre-timed traffic controller system that based on AVR microcontroller. By default, the systems use the signal-timing plans to control the vehicle flow. To accommodate the traffic variations, a new method of vehicle detection has been built. The method calculated an intensity histogram standard deviation of the image representing a detection area to determine traffic density of each intersection lane. The systems modified the green-time of each lane based on the traffic density. The method could detect all types of vehicles and work properly in a day and a night time

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