Have a personal or library account? Click to login
Traffic Flow Variables Estimation: An Automated Procedure Based on Moving Observer Method. Potential Application for Autonomous Vehicles Cover

Traffic Flow Variables Estimation: An Automated Procedure Based on Moving Observer Method. Potential Application for Autonomous Vehicles

Open Access
|Jun 2019

References

  1. 1. Abdulrahman, H.S., Almusawi, A.A., Abubakar, M. (2017) Comparative Assessment of Macroscopic Traffic Flow Properties Estimation Methods: A Case for Moving Car Observer Method. ESTIRJ, 1(2), 11-15.
  2. 2. Barua, S., Das, A., Hossain, J. (2015) Estimation of traffic density to compare speed-density models with moving observer data. International Journal of Research in Engineering and Technology, 4(08), 471-474.10.15623/ijret.2015.0408080
  3. 3. Bennett, T.H. (1977) A further procedure for estimating speed distribution parameters in uni-directional traffic streams using the moving observer method. Transpn res., 11(3), 205-207.10.1016/0041-1647(77)90021-1
  4. 4. Bensrhair, A., Bertozzi, M., Broggi, A., Miche, P., Mousset, S., Toulminet, G. (2001) IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585), Oakland, CA, 207-212.
  5. 5. Broggi, A., Cerri, P., Antonello, P.C. (2004) Multi-Resolution Vehicle Detection Using Artificial Vision. IEEE Intelligent Vehicles Symposium, Parma, Italy, 310–314.10.1109/IVS.2004.1336400
  6. 6. Chang, W.C., Cho, C.W. (2010) Online boosting for vehicle detection. IEEE Trans. Syst. Man Cybern. Part. B Cybern., 40, 892–902.10.1109/TSMCB.2009.2032527
  7. 7. Daganzo, C.F. Fundamentals of Transportation and Traffic Operations. Pergamon, 1997.10.1108/9780585475301
  8. 8. Dollar, P., Appel, R., Belongie, S., Perona, P. (2014) Fast feature pyramids for object detection. IEEE Trans. Pattern Anal. Mach. Intell., 36, 1532–1545.10.1109/TPAMI.2014.2300479
  9. 9. Dollár, P., Belongie,S., Perona, P. (2010) The fastest pedestrian detector in the west. in BMVC. Available at: https://www.robots.ox.ac.uk/~vgg/rg/papers/DollarBMVC10FPDW.pdf.10.5244/C.24.68
  10. 10. Duncan, N.C. (1973) A method of estimating the distribution of speeds of cars on motorways. TRRL, LR 598. Transport and Road Research Laboratory, Crowthorne, Berkshire.
  11. 11. Feng, Y., Xing, C. (2013) A New Approach to Vehicle Positioning Based on Region of Interest. IEEE International Conference on Software Engineering and Service Science (ICSESS), Beijing, China, 471–474.10.1109/ICSESS.2013.6615351
  12. 12. Gerlough, D.L., Huber, M.J. Traffic flow theory; A Monograph. Special Report 165. TRB, 1975.
  13. 13. Guo, D., Fraichard, T., Xie, M., Laugier, C. (2000) Color Modeling by Spherical Influence Field. In Sensing Driving Environment. IEEE Intelligent Vehicles Symposium, Dearborn, MI, USA, 249–254.
  14. 14. Hewitt, R.H., Chambers, I.B., White, A.W. (1974) Graphical solution of moving observer surveys. The Highway Engineer, Journal of Inst, of Highway Engineers, 1(6), 12-16.
  15. 15. Hu, Q., Paisitkriangkrai, S., Shen, C., van den Hengel, A., Porikli, F. (2016) Fast Detection of Multiple Objects in Traffic Scenes With a Common Detection Framework. IEEE Transactions on Intelligent Transportation Systems, 17(4), 1002-1014.10.1109/TITS.2015.2496795
  16. 16. Janai, J., Güney, F., Behl, A., Geiger, A. (2017) Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art. ISPRS Journal of Photogrammetry and Remote Sensing. Available at: https://arxiv.org/abs/1704.05519v1.
  17. 17. Kim, J., Baek, J., Park, Y., Kim, E. (2015) New Vehicle Detection Method with Aspect Ratio Estimation for Hypothesized Windows. Sensors, 15, 30927–30941.10.3390/s151229838472175826690177
  18. 18. Lee, B.H., Brocklebank, P.J. (1993) Speed-flow-geometry Relationships for Rural Single Carriageway Roads. TRRL Contractor Report 319, Transport Research Laboratory, Crowthorne, U.K.
  19. 19. Leutzbach, W. Introduction to the Theory of Traffic Flow. Springer, 1998
  20. 20. Menze, M., Geiger, A. (2015) Object scene flow for autonomous vehicles. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, 3061-3070.10.1109/CVPR.2015.7298925
  21. 21. Sivaraman, S., Trivedi, M.M. (2013) Looking at vehicles on the road: A survey of vision-based vehicle detection, tracking, and behavior analysis. IEEE Trans. Intell. Transportation Syst., 14(4), 1773–1795.10.1109/TITS.2013.2266661
  22. 22. Southall, B., Bansal, M., Eledath, J. (2009) Real-Time Vehicle Detection for Highway Driving. IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA, 541–548.10.1109/CVPR.2009.5206597
  23. 23. Sun, Z., Bebis, G., Miller, R. (2005) On-road vehicle detection using evolutionary gabor filter optimization. IEEE Trans. Intell. Transp. Syst., 6, 125–137.10.1109/TITS.2005.848363
  24. 24. Sun, Z., Miller, R., Bebis, G., D iMeo, D. (2002) A Real-Time Precrash Vehicle Detection System. IEEE Workshop on Application of Computer Vision, Orlando, FL, USA, 171–176.
  25. 25. Tsai, L.W., Hsieh, J.W., Fan, K.C. (2007) Vehicle Detection Using Normalized Color and Edge Map. IEEE Trans. Image Proc., 16, 850–864.10.1109/TIP.2007.891147
  26. 26. Tzomakas, C., Von Seelen, W. (1998) Vehicle Detection in Traffic Scenes Using Shadows; Technical Report for Institut Fur Neuroinformatik; Ruht-Universitat: Bochum, Germany. Available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.3234
  27. 27. Wardrop, J.G., Charlesworth, G. (1954) A Method of Estimating Speed and Flow of Traffic from a Moving Vehicle. Proceedings of the Institution of Civil Engineers, 3 (1), 158-171.10.1680/ipeds.1954.11628
  28. 28. Wright, G. (1972) A Theoretical analysis of the moving observer method. Transpn Res., 7, 293-311.10.1016/0041-1647(73)90019-1
  29. 29. Yuan, Q., Ablavsky, V. (2011) Learning a family of detectors via multiplicative kernels. IEEE Trans. Pattern Anal. Mach. Intell., 33, 514–530.10.1109/TPAMI.2010.117
DOI: https://doi.org/10.2478/ttj-2019-0017 | Journal eISSN: 1407-6179 | Journal ISSN: 1407-6160
Language: English
Page range: 205 - 214
Published on: Jun 26, 2019
Published by: Transport and Telecommunication Institute
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 Marco Guerrieri, Giuseppe Parla, Raffaele Mauro, published by Transport and Telecommunication Institute
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.