Desain Sistem Pengatur Lampu Lalu Lintas dengan Identifikasi Kepadatan Kendaraan Menggunakan Metode Subtraction

Geminiesty Lathifasari Djavendra, Siti Aisyah, Eko Rudiawan Jamzuri

Abstract


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%.

Keywords : Image processing, image subtraction, light control system, traffic density, dilation, erosion


Abstrak

Bertambahnya jumlah kendaraan menyebabkan meningkatnya kepadatan lalu lintas yang menjadi salah satu faktor utama penyebab kemacetan. Kepadatan lalu lintas biasanya teralokasi di beberapa titik-titik tertentu di ruas jalan, salah satunya di persimpangan. Saat ini lalu lintas di persimpangan jalan diatur oleh lampu lalu lintas menggunakan sistem prediksi kepadatan lalu lintas. Sistem prediksi ini nantinya akan menentukan lama aktifnya lampu hijau dan lampu merah di setiap persimpangan. Salah satu sistem prediksi yang banyak digunakan adalah metode estimasi stastistik kepadatan kendaraan. Metode lain pengontrolan kepadatan lalu lintas seperti sistem pemantauan secara visual memungkinkan untuk diterapkan guna menambah performansi sistem. Untuk itu penelitian ini mengusulkan pembuatan sebuah sistem pengontrolan lampu lalu lintas secara otomatis dengan prediksi kepadatan kendaraan menggunakan teknik pengolahan citra. Sistem yang dibangun menggunakan kamera untuk memantau kondisi kendaraan di jalan raya. Data gambar yang didapat dari kamera kemudian diolah menggunakan teknik pengolahan citra dan teknik pengurangan citra. Teknik ini membandingkan citra objek dengan citra referensi sehingga dapat diketahui jumlah piksel putih pada citra hasil pengurangan citra. Berdasarkan jumlah piksel putih yang telah diperoleh tersebut dapat diketahui persentase panjang antrian kendaraan dan kepadatan kendaraan. Data persentase yang diperoleh kemudian dikirim ke mikrokontroler untuk mengontrol durasi nyala lampu hijau. Pengontrolan lampu lalu lintas dengan perhitungan kepadatan kendaraan memiliki akurasi hingga 77.03% sedangkan dengan perhitungan panjang antrian kendaraan mencapai 91.18%.

 

Kata Kunci : Pengolahan citra, pengurangan citra, sistem kontrol lampu, kepadatan kendaraan, dilation, erosion



Full Text:

PDF

References


Jatmika Sunu, dan Indra Andiko, Simulasi Pengaturan Lampu Lalu Lintas Berdasarkan Data Image Processing Kepadatan Kendaraan Berbasis Mikrokontroler Atmega16, Jurnal Ilmiah Teknologi dan Informasi ASIA, Vol.8, No.2, pp.81, Agustus 2014.

M. Chandrasekhar, etc., Traffic Control Using Digital Image Processing, International Journal Of Advanced Electrical and Electronics Engineering,Vol.2, No.5, pp.96, 2013.

Gaikwad Omkar Ramdas, etc., Image Processing Based Traffic Light Control, International Journal of Science, Engineering and Technology Research (IJSETR), Vol. 3, Issue 4, April 2014.

Fitria Rahmadina dan Zaini, Sistem Informasi Kepadatan Lalu Lintas Berbasis Raspberry pi PC Board, Jurnal Nasional Teknik Elektro, Vol: 5, No. 1, Maret 2016.

Kasdianto dan Siti Aisyah, Desain Sistem Pendeteksi untuk Citra Base Sub-Assembly dengan Algoritma Backpropagation, Jurnal Rekayasa Elektrika, Vol. 13, No. 1, April 2017, hal. 1-7.

Wan Yi, Xie Qisong, A Novel Framework for Optimal RGB to Grayscale Image Conversion, International Conference on Intelligent Human-Machine Systems and Cybernetics, 2016.

Praba D. Surya daoold & Kumar J. Satheesh, Performance Analysis of Image Smoothing Methods for Low Level of Distortion, IEEE International Conference on Advances in Computer Applications (ICACA), 2016.

Wang Yuan-Kai, Chen Hung-Yu, The Design of Background Subtraction on Reconfigurable Hardware, Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IEEE (2012).

Putra Darma, Pengolahan Citra Digital, Penerbit Andi, 2010.




DOI: https://doi.org/10.25077/jnte.v7n2.541.2018

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

 

  

.
Statistic and Traffic