Communications - Scientific Letters of the University of Zilina 2009, 11(4):61-64 | DOI: 10.26552/com.C.2009.4.61-64

A Contribution to the Traffic State Estimation by Means of Image Processing

Marija Kopf1, Petr Cenek1
1 Department of Transportation Networks, Faculty of Management Science and Informatics, University of Zilina, Slovakia

The success of traffic simulations depends largely on the simulation model validity and on accuracy of input data. For input data acquisition, video cameras are used to survey the traffic at junctions or at other places along the road to collect video data. The velocity, distance between the vehicles, acceleration and other relevant parameters can be extracted from the collected data. The estimated values are used for calibration of the simulation model. The data that has to be collected for calibration or validation of the simulation system, differ from country to country and reflects the driver behavior. For that reason, the data collection must be performed and the simulation system calibrated, each time when modeling a different traffic area. The more accurate the obtained parameters, the more accurate the traffic simulation would be. The image processing methods and the expected accuracy of traffic state estimation, such as vehicle position, speed and acceleration, is discussed in the paper and applied to the evaluation of driver behavior necessary for the calibration of the microscopic simulation systems.

Keywords: microscopic systems, transportation simulation, error estimation, image processing

Published: December 31, 2009  Show citation

ACS AIP APA ASA Harvard Chicago IEEE ISO690 MLA NLM Turabian Vancouver
Kopf, M., & Cenek, P. (2009). A Contribution to the Traffic State Estimation by Means of Image Processing. Communications - Scientific Letters of the University of Zilina11(4), 61-64. doi: 10.26552/com.C.2009.4.61-64
Download citation

References

  1. CENEK, P.: Models and Optimization in Transports and Logistics. University of Zilina, 2008
  2. PURSULA, M.: Simulation of Traffic Systems - An Overview. Journal of Geographic Information and Decision Analysis, vol.3, 1/1999, pp.1-8
  3. BAYARRI, B.: Assessing Uncertainties in Traffic Simulation: A Key Component in Model Calibration and Validation. TRB 83rd Annual Meeting, pp. 32-40, January 2004 Go to original source...
  4. SEUL, M.: Practical Algorithms for Image Analysis. Cambridge University Press, 2000, ISBN-10: 052188411X
  5. JIMINEZ, T.: A Road Traffic Simulator: Car-Following and Lane-Changing. Proceedings of the 14th European Simulation Multiconference on Simulation and Modelling, 2000
  6. KUMAR, P.: Framework for Real-Time Behavior Interpretation From Traffic Video. IEEE Transactions on Intelligent Transportation Systems, Vol. 6, 1/2005 Go to original source...
  7. GRAMMATIKOPOULOS, L., KARRAS, G., PETSA, E.: Automatic Estimation of Vehicle Speed from Uncalibrated Video Sequences, International Symposium on Modern Technologies, Education and Professional Practice in Geodesy and Related Fields, Sofia 2005
  8. ZHANG, Z.X., LI, M., HUANG, K.Q., TAN, T. N.: Robust automated ground plane rectification based on moving vehicles for traffic scene surveillance, 15th IEEE International Conference on Image Processing, 2008
  9. BOSE, B., GRIMSON, E.: Ground Plane Rectification by Tracking Moving Objects, Proc. of Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, 2003
  10. H. RAKHA, B. HELLINGA, M. VAN AERDE, W. PEREZ: Systematic Verification, Validation and Calibration of Traffic Simulation Models, Annual Meeting, TRB, Washington, DC, 1996
  11. MASOUD, O., ROGERS, S., PAPANIKOLOPOULOS, N.: Monitoring Weaving Sections, Report no. CTS 01-06, University of Minnesota, USA, October 2001
  12. GONZALES, R., R. WOODS, R., EDDINS, S.: Digital Image Processing, 2nd Edition, Prentice Hall; 2nd edition (January 15, 2002), ISBN-10: 0201180758
  13. SEUL, M. et al.: Practical Algorithms for Image Analysis, Cambridge University Press, 2000, ISBN-10: 0521660653.

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.