Deteksi dan Estimasi Kecepatan Kendaraan dalam Sistem Pengawasan Lalu Lintas Menggunakan Pengolahan Citra

Muhammad Zulfikri; Hairani Hairani; Ahmad Ahmad; Kurniadin Abd. Latif; Rifqi Hammad; Moch. Syahrir

doi:10.33633/tc.v20i3.4588

Deteksi dan Estimasi Kecepatan Kendaraan dalam Sistem Pengawasan Lalu Lintas Menggunakan Pengolahan Citra

Muhammad Zulfikri, Hairani Hairani, Ahmad Ahmad, Kurniadin Abd. Latif, Rifqi Hammad, Moch. Syahrir

Abstract

Deteksi objek berbasis pengolahan citra digital pada kendaraan sangat penting untuk diterapkan dalam membangun sistem pengawasan atau sebagai metode alternatif dalam mengumpulkan data statistik untuk pengambilan keputusan rekaya lalu lintas yang efisien. Pada penilitian ini, dibuat sistem deteksi kendaraan berbasis video lalu lintas untuk jenis kendaraan tertentu dengan menggunakan Haar Cascade Classifier dan estimasi kecepatan kendaraan dilakukan dengan menghitung perbedaan waktu pada Region of Interest (ROI) yang telah ditentukan dan hasilnya akan ditampilkan pada Radar Speed Design. Pengujian dilakukan dengan 5 video pengujian. Hasil yang didapatkan dari deteksi kendaraan yaitu nilai rata-rata recall 0.988 dan presisi 0.97 dan dari perhitungan kecepatan didapatkan nilai Mean Squared Error (MSE) yaitu 0,6.

Keywords

deteksi, kecepatan, kendaraan, haar cascade classifier, radar speed design

Full Text:

PDF

References

S. Jeng, W. Chieng, and H. Lu, “Estimating Speed Using a Side-Looking Single-Radar Vehicle Detector,” IEEE Trans. Intell. Transp. Syst., vol. 15, no. 2, pp. 607–614, 2014.

P. K. Thadagoppula and V. Upadhyaya, “Speed detection using image processing,” Int. Conf. Comput. Control. Informatics its Appl., pp. 11–16, 2016, doi: 10.1109/IC3INA.2016.7863015.

C. Y. Ho, H. Y. Lin, and L. T. Wu, “Intelligent speed bump system with dynamic license plate recognition,” IEEE Int. Conf. Ind. Technol., pp. 1669–1674, 2016, doi: 10.1109/ICIT.2016.7475013.

L. E. Y. Mimbela, “A Summary of Vehicle Detection and Surveillance Technologies used in Intelligent Transportation Systems,” Fed. Highw. Adm. Intell. Transp. Syst. Progr. Off., 2007.

J. Damsere-Derry, R. Lumor, S. Bawa, and D. Tikoli, “Effects of Traffic Calming Measures on Mobility, Road Safety and Pavement Conditions on Abuakwa-Bibiani Highway,” Front. Sustain. Cities, vol. 2, no. June, pp. 1–9, 2020, doi: 10.3389/frsc.2020.00026.

N. Buch, S. A. Velastin, and J. Orwell, “A review of computer vision techniques for the analysis of urban traffic,” IEEE Trans. Intell. Transp. Syst., vol. 12, no. 3, pp. 920–939, 2011, doi: 10.1109/TITS.2011.2119372.

Carmanah Technologies Corp., “Radar Speed Signs Top Traffic Calming List,” Traffic Calming & Vision Zero, 2019. https://carmanah.com/articles/radar-speed-signs-top-traffic-calming-list/ (accessed Jan. 04, 2021).

M. Li, A. Faghri, and R. Fan, “Determining Ideal Locations for Radar Speed Signs for Maximum Effectiveness: A Review of the Literature,” Dep. Civ. Environ. Eng. Univ. Delaware, 2017.

L. Radarsign, “How Effective are Radar Speed Signs? | radarsign.com.” https://www.radarsign.com/how-effective-are-radar-speed-signs/ (accessed Jan. 06, 2021).

A. Varghese and G. Sreelekha, “Background Subtraction for Vehicle Detection,” Glob. Conf. Commun. Technol., pp. 380–382, 2015, doi: 10.1109/GCCT.2015.7342688.

R. A. Yuha and M. Harahap, “Deteksi Gerakan pada Kamera CCTV dengan Algoritma Frame Difference dan Frame Substraction,” Semin. Nas. Teknol. Inf. dan Komun., pp. 503–511, 2019.

Q. Wu, W. Kang, and X. Zhuang, “Real-time vehicle detection with foreground-based cascade classifier,” IET Image Process., vol. 10, no. 4, pp. 289–296, 2016, doi: 10.1049/iet-ipr.2015.0333.

P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple features,” IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., vol. 1, pp. 511–518, 2001, doi: 10.1109/CVPR.2001.990517.

D. K. Ulfa and D. H. Widyantoro, “Pelaksanaan Haar Cascade Classifier untuk Deteksi Motorcycle,” IEEE Int. Conf. Cybern. Comput. Intell., 2017.

S. Choudhury, S. P. Chattopadhyay, and T. K. Hazra, “Vehicle Detection and Counting using Haar Feature- Based Classifier,” 8th Annu. Ind. Autom. Electromechanical Eng. Conf., pp. 106–109, 2017.

M. Zulfikri, E. Yudaningtyas, K. Kendaraan, H. Cascade, and J. Teknologi, “Sistem Penegakan Speed Bump Berdasarkan Kecepatan Kendaraan yang Diklasifikasikan Haar Cascade Classifier,” J. Teknol. dan Sist. Inf., vol. 7, no. 1, pp. 12–18, 2019, doi: 10.14710/jtsiskom.7.1.2019.12-18.

D. Jomaa, S. Yella, and M. Dougherty, “A Comparative Study between Vehicle Activated Signs and Speed Indicator Devices,” Transp. Res. Procedia, vol. 22, no. 2016, pp. 115–123, 2017, doi: 10.1016/j.trpro.2017.03.017.

A. Ullah, S. Hussain, A. Wasim, and M. Jahanzaib, “Usage and impacts of speed humps on vehicles: A review,” J. Adv. Rev. Sci. Res. J. homepage, vol. 28, no. 1, pp. 1–17, 2016, [Online]. Available: www.akademiabaru.com/arsr.html.

A. Khan, D. M. S. Z. Sarker, and S. Rayamajhi, “Speed Estimation of Vehicle in Intelligent Traffic Surveillance System Using Video Image Processing,” Int. J. Sci. Eng. Res., vol. 5, no. 12, pp. 1384–1390, 2014, doi: 10.14299/ijser.2014.12.003.

H. J. Kim, “Vehicle detection and speed estimation for automated traffic surveillance systems at nighttime,” Tech. Gaz., vol. 26, no. 1, pp. 87–94, 2019, doi: 10.17559/TV-20170827091448.

DOI: https://doi.org/10.33633/tc.v20i3.4588