Implementation of a Vehicle Traffic and Speed Estimation System Using Faster R-CNN 


Vol. 44,  No. 9, pp. 1754-1758, Sep.  2019
10.7840/kics.2019.44.9.1754


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  Abstract

In this paper, a method to obtain the traffic volume and speed from road control CCTV is presented and implemented. The proposed method detects the vehicle objects and obtain vehicle types through the deep learning algorithm (Faster R-CNN) and uses a tracking algorithm to obtain vehicle traffic volume, and vehicle speed. Applying the proposed method to the CCTV installed on the expressway provided by Korea Expressway Corporation, 98.3% traffic detection accuracy and 93.8% traffic speed accuracy were obtained.

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  Cite this article

[IEEE Style]

J. Kim and D. Choi, "Implementation of a Vehicle Traffic and Speed Estimation System Using Faster R-CNN," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 9, pp. 1754-1758, 2019. DOI: 10.7840/kics.2019.44.9.1754.

[ACM Style]

Jung-Hun Kim and Doo-Hyun Choi. 2019. Implementation of a Vehicle Traffic and Speed Estimation System Using Faster R-CNN. The Journal of Korean Institute of Communications and Information Sciences, 44, 9, (2019), 1754-1758. DOI: 10.7840/kics.2019.44.9.1754.

[KICS Style]

Jung-Hun Kim and Doo-Hyun Choi, "Implementation of a Vehicle Traffic and Speed Estimation System Using Faster R-CNN," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 9, pp. 1754-1758, 9. 2019. (https://doi.org/10.7840/kics.2019.44.9.1754)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880