An automatic traffic density estimation using Single Shot Detection (SSD)and MobileNet-SSD

Physics and Chemistry of the Earth

Volumn 110, Issue , 2019, Pages 176-184

  Biswas, Debojit ^a   Su, Hongbo ^a   Wang, Chengyi ^b   Stevanovic, Aleksandar ^a   Wang, Weimin ^c  

^a Florida Atlantic University   (United States)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^c Shenzhen Center for ADR Monitoring   (China)

Author keywords

Convolution neural network; Feature maps; MobileNet; Single shot detection; Traffic density; Visual Geometry Group

Indexed keywords

STREET TRAFFIC CONTROL;

CONVOLUTION NEURAL NETWORK; FEATURE MAP; MOBILENET; SINGLE SHOTS; TRAFFIC DENSITIES; VISUAL GEOMETRY GROUP;

TRAFFIC CONGESTION;

ACCURACY ASSESSMENT; ALGORITHM; DETECTION METHOD; ESTIMATION METHOD; MONITORING SYSTEM; PLANNING METHOD; TRAFFIC CONGESTION; TRAFFIC MANAGEMENT; TRANSPORTATION PLANNING; URBAN AREA;

EID: 85058693500     PISSN: 14747065     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.pce.2018.12.001     Document Type: Article

References (21)

1. Anand, R.A., Vanajakshi, L., Subramanian, S.C., Traffic density estimation under heterogeneous traffic conditions using data fusion. IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, Germany, June 5-9, 2011.
2. Artimy, M., Local density estimation and dynamic transmission-range assignment in vehicular ad hoc networks. IEEE Trans. Intell. Transport. Syst. 8:3 (2007), 400–412.
3. Biswas, D., Su, H., Wang, C., Blankenship, J., Stevanovic, A., An automatic car counting system using OverFeat framework. Sensors, 17, 2017, 1535.
4. Buch, N., Velastin, S.A., Orwell, J., A review of computer vision techniques for the analysis of urban traffic. IEEE Trans. Intell. Transport. Syst. 12:3 (2011), 920–939.
5. Howard, A.G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., Adam, H., MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. 2017 1704.04861.
6. Ioffe, S., Szegedy, C., Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. 2015 1502.03167.
7. LabelImg. (accessed on 5 March 2018), Available online: https://github.com/tzutalin/labelImg.
8. Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.Y., Berg, A.C., SSD: Single Shot MultiBox Detector. 2016 1512.02325.
9. th International IEEE Conference on Intelligent Transportation Systems (ITSC), 2011, 771–776.
10. Morarescu, I.C., Canudas-de, C.W., Highway traffic model-based density estimation. American Control Conference (ACC), 2011, 2012–2017.
11. Ramezani, A., Moshiri, B., Abdulhai, B., Kian, A.R., Estimation of free flow speed and critical density in a segmented freeway using missing data and Monte Carlo-based expectation maximisation algorithm. IET Control Theory & Appl. 5:1 (2011), 123–130.
12. Ramezani, A., Moshiri, B., Abdulhai, B., Kian, A.R., Distributed maximum likelihood estimation for flow and speed density prediction in distributed traffic detectors with Gaussian mixture model assumption. IET Intell. Transp. Syst. 6:2 (2012), 215–222.
13. Singh, K., Baibing, L., Estimation of traffic densities for multilane roadways using a markov model approach. IEEE Trans. Ind. Electron. 59:11 (2012), 4369–4376.
14. Tabibiazar, A., Basir, O., Kernel-based optimization for traffic density estimation. IEEE Vehicular Technology Conference (VTC Fall), 2011, 1–5.
15. Traffic Scorecard, INRIX. 2018 Available online: http://inrix.com/.
16. Tyagi, V., Kalyanaraman, S., Krishnapuram, R., Vehicular traffic density state estimation based on cumulative road acoustics. IEEE Trans. Intell. Transport. Syst.(99), 2012, 1–11.
17. Uddin, M.S., Das, A.K., Md Taleb, A., Real-time area based traffic density estimation by image processing for traffic signal control system: Bangladesh perspective. 2nd Int'l Conf. On Electrical Engineering and Information & Communication Technology (ICEEICT), 2015.
18. van Hinsbergen, C.P.I.J., Schreiter, T., Zuurbier, F.S., van Lint, J.W.C., van Zuylen, H.J., Localized extended kalman filter for scalable real-time traffic state estimation. IEEE Trans. Intell. Transport. Syst. 13:1 (2012), 385–394.
19. VGG architecture. (accessed on 10 February 2018). Available online: https://www.cs.toronto.edu/∼frossard/post/vgg16/.
20. VGG Feature Map Visualization. (accessed on 15 February 2018). Available online: http://vision03.csail.mit.edu/cnn_art/index.html.
21. Yufei, Y., van Lint, J.W.C., Wilson, R.E., van Wageningen-Kessels, F., Hoogendoorn, S.P., Real-time Lagrangian traffic state estimator for freeways. IEEE Trans. Intell. Transport. Syst. 13:1 (2012), 59–70.