Desain Sistem Pengatur Lampu Lalu Lintas dengan Identifikasi Kepadatan Kendaraan Menggunakan Metode Subtraction
Autor: | Geminiesty Lathifasari Djavendra, Siti Aisyah, Eko Rudiawan Jamzuri |
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Jazyk: | English<br />Indonesian |
Rok vydání: | 2018 |
Předmět: | |
Zdroj: | Jurnal Nasional Teknik Elektro, Vol 7, Iss 2, Pp 130-137 (2018) |
Druh dokumentu: | article |
ISSN: | 2302-2949 2407-7267 |
Popis: | The increasing number of vehicle causes the increasing of traffic density in which one of the main factors of congestion. Traffic density is usually alocated at certain points of roads, one at the instersection. In the novel technology, traffic in the crossroads had been controlled by traffic light using a traffic density prediction system. This prediction system would determine the duration of active green lights and red lights at each intersection. One of the most common prediction systems is a statistical estimation of vehicle density. Other method at controlling traffic density such as visually monitoring system might be implemented to increase system performance. Therefore, this research proposes an automatically traffic control system by predicting traffic density using image processing techniques. The proposed system is using a camera to visually monitor traffic condition. The image data obtained from the camera would be processed using an image processing and background subtraction techniques. This technique compared an the captured-image with a reference image to result a subtracted-image depicted the traffic density which is represented by the number of white pixels. Based on the number of white pixels that have been obtained, the percentage of vehicle queue length and vehicle density can be determine. The percentage then sent to the microcontroller in order to control the duration of the active green light. The traffic light control system using traffic density calculation has an accuracy of up to 77.03% while using the calculation of vehicle queue length reached 91.18%. |
Databáze: | Directory of Open Access Journals |
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