Journal of Korean Society of Transportation (대한교통학회지)

Korean Society of Transportation (대한교통학회)
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Prediction of Volumes and Estimation of Real-time Origin-Destination Parameters on Urban Freeways via The Kalman Filtering Approach

칼만필터를 이용한 도시고속도로 교통량예측 및 실시간O-D 추정

  • 강정규 (도로교통안접협회 교통과학연구원 수석연구원)
  • Published : 1996.09.01
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Abstract

The estimation of real-time Origin-Destination(O-D) parameters, which gives travel demand between combinations of origin and destination points on a urban freeway network, from on-line surveillance traffic data is essential in developing an efficient ATMS strategy. On this need a real-time O-D parameter estimation model is formulated as a parameter adaptive filtering model based on the extended Kalman Filter. A Monte Carlo test have shown that the estimation of time-varying O-D parameter is possible using only traffic counts. Tests with field data produced the interesting finding that off-ramp volume predictions generated using a constant freeway O-D matrix was replaced by real-time estimates generated using the parameter adaptive filter.

Keywords

References

  1. Signal Processing: The Model Based Approach Candy,J.V.
  2. Transpn. Res. v.22B A unified framework for estimating or updating origin/destination matrices from traffic counts Cascetta,E.;Nguyen,S.
  3. Transpn. Rec. Recursive estimation of time-varying O-D Flows from traffic counts in freeway corridors Chang,G.L.;Wu,J.
  4. Transpn. Res. v.32B A new class of dynamic methods for the identification of origin-destination flows Cremer,M.;Keller,H.
  5. Paper Presented at 33rd ORSA/TIMS Joint National Conference Integrated traffic assignment and flow models vial Markovian networks Davis,G.
  6. ASCE J. of Transportation Engineering v.119 no.4 Estimating freeway origin-destination parameters and impact of uncertainty on ramp control Davis,G.
  7. Transpn. Res. Rec. v.1457 Estimating destination-specific traffic densities on urban freeways for advanced traffic management Davis,G.;Kang,J.G.
  8. Intelligent Vehicle Highway System in Traffic Engineering Handbook (4th edition) Euler,G.
  9. Journal of Mathematical Sociology v.7 Approximations for interactive Markov chains in discrete and continuous time Lehoczky,J.
  10. Transpn. Res. v.21B Recursive estimation of origin-destination matrices from input/output counts Nihan,N.;Davis,G.
  11. Transpn. Science v.23 Application of prediction-error minimization and maximum like-lihood to estimate intersection O-D matrices from traffic counts Nihan,N.;Davis,G.
  12. Transportation Planning Models Estimating origin-destination matrices from observed flows Nguyen,S.;M.Florian(ed.)
  13. NAG workstation library(Version I.) Numerical Algorithms Group
  14. Transpn, and Traffic Flow Theory The Kalman filtering approaches in transportation and traffic problems Okutani,I.Gartner,N.H.(ed.);Wilson,N.H.M.(ed.)
  15. Transpn. Res. Rec. v.1306 Dynamic network traffic assignment and route guidance via feedback regulation Papageorgiou,M.;Messmer,A.
  16. Transpn. Res. Rec. v.722 FREFLO: A macroscopic simulation model of freeway traffic Payne,H.J.
  17. ASCE Journal of Transpn. Engineering v.119 no.4 Optimal control of freeway corridors Stephanedes,Y.;Chang,K.
  18. Integration-1 User's Manual Van Aerde,M.;Voss,J.
  19. Transpn. Res. Rec. v.1443 An improved Kalman filtering approach to estimate origin-destination matrices for freeway corridors Zijpp,N.;Hammerslag,R.