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Transportation System Intelligence: Performance Measurement and Real-Time Traffic Estimation and Prediction in a Day-to-Day Learning Framework

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Advances in Control, Communication Networks, and Transportation Systems

Part of the book series: Systems and Control: Foundations & Applications ((SCFA))

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References

  1. K. Ashok, Estimation and Prediction of Time-Dependent Origin-Destination Flows, Ph.D. Dissertation, MIT, 1996.

    Google Scholar 

  2. K. Ashok and M. Ben-Akiva, Dynamic origin-destination matrix estimation and prediction for real-time traffic management systems, Proceedings of the 12th International Symposium on Transportation, C. Daganzo (ed), Elsevier, 1993.

    Google Scholar 

  3. K. Ashok and M. Ben-Akiva, Alternative approaches for real-time estimation and prediction of time-dependent origin-destination flows, Transportation Science, 34(1):21–36, 2000.

    Article  MATH  Google Scholar 

  4. M. Broucke and P. Varaiya, A theory of traffic flow for automated highway systems, Transportation Research, Part C, 4(4):181–210, 1996.

    Article  Google Scholar 

  5. E. Cascetta, D. Inaudi and G. Marquis, Dynamic estimators of origindestination matrices using traffic counts, Transportation Science, 27(4):363–373, 1993.

    MATH  Google Scholar 

  6. G.L. Chang and X.D. Tao, An integrated model for estimating time-varying network origin-destination distributions, Transportation Research, 33A(5):381–399, 1999.

    Google Scholar 

  7. G.L. Chang and J. Wu, Recursive estimation of time-varying origin-destination flows from traffic counts in freeway corridors, Transportation Research, 28B(2):141–160, 1994.

    MathSciNet  Google Scholar 

  8. C. Chen, A. Skabardonis and P. Varaiya, Travel-time reliability as a measure of service, Transportation Research Record, 1855:74–79, 2003.

    Google Scholar 

  9. C. Chen, A. Skabardonis and P. Varaiya, Systematic identification of freeway bottlenecks, Transportation Research Record, 1867:46–52, 2004.

    Google Scholar 

  10. C. Chen, Z. Jia and P. Varaiya, Causes and cures of highway congestion, IEEE Control Systems Magazine, 21(6):26–32, 2002.

    Article  MATH  Google Scholar 

  11. C. Chen, K. Petty, A. Skabardonis, P. Varaiya and Z. Jia, Freeway performance measurement system: mining loop detector data, Transportation Research Record, 1748:96–102, 2001.

    Google Scholar 

  12. C. Chui and G. Chen, Kalman Filtering with Real-Time Applications, Springer-Verlag, 1991.

    Google Scholar 

  13. D.N. Godbole, F. Eskafi, E. Singh and P. Varaiya, Design of entry and exit maneuvers for IVHS, Proceedings of the American Control Conference, 5:3576–3580, 1995.

    Google Scholar 

  14. M. Cremer and H. Keller, Dynamic identification of flows from traffic counts at complex intersections, In: E. Hauer and V. Hurdle, Eds., Proceedings of the 8th International Symposium on Transportation and Traffic Theory, 1981.

    Google Scholar 

  15. M. Cremer and H. Keller, A new class of dynamic methods for the identification of origin-destination flows, Transportation Research, 21B(2):117–132, 1987.

    Google Scholar 

  16. A.C. Harvey, Forecasting Structural Time Series Models and the Kalman Filter, Cambridge University Press, 1989.

    Google Scholar 

  17. J.K. Hedrick, M. Tomizuka and P. Varaiya, Control issues in automated highway systems, IEEE Control Systems Magazine, 14(6):21–32, 1994.

    Article  Google Scholar 

  18. R. Herman, Technology, human interaction, and complexity: reflections on vehicular traffic science, Operations Research, 40:199–212, 1992.

    Article  Google Scholar 

  19. R. Horowitz and P. Varaiya, Control design of an automated highway system, Proceedings of the IEEE, 88(7), 2000.

    Google Scholar 

  20. R. Jayakrishnan, H.S. Mahmassani and T-Y. Hu, An evaluation tool for advanced traffic information and management systems in urban networks, Transportation Research, 2C(3):129–147, 1994.

    Google Scholar 

  21. Z. Jia, C. Chen, B. Coifman and P. Varaiya, The PeMS algorithms for accurate, real-time estimates of g-factors and speeds from single-loop detectors, Proceedings 2001 IEEE Intelligent Transportation Systems, 536–541, 2001.

    Google Scholar 

  22. Y. Kang, Estimation and Prediction of Dynamic Origin-Destination (O-D) Demand and System Consistency Control for Real-Time Dynamic Traffic Assignment Operation, Ph.D. Dissertation, The University of Texas at Austin, 1999.

    Google Scholar 

  23. J. Kwon, C. Chen and P. Varaiya, Statistical methods for detecting spatial configuration errors in traffic surveillance sensors, Transportation Research Record, 1870:124–132, 2004.

    Google Scholar 

  24. H.S. Mahmassani and R. Jayakrishnan, Dynamic simulation-assignment methodology to evaluate in-vehicle information strategies in urban traffic networks, Proceedings of Winter Simulation Conference, 763–769, New Orleans, LA, 1990.

    Google Scholar 

  25. H.S. Mahmassani, Dynamic network traffic assignment and simulation methodology for advanced system management applications, Networks and Spatial Economics, 1–2(3,4):267–292, 2001.

    Article  Google Scholar 

  26. H.S. Mahmassani, Y. Hawas, K. Abdelghani, A. Abdelfatah, Y.-C. Chiu and Y. Kang, DYNASMART-X; Volume II: Analytical and Algorithmic Aspects, Technical Report ST067-85-Volume II, Center for Transportation Research, The University of Texas at Austin, 1998.

    Google Scholar 

  27. I. Okutani and Y. Stephanedes, Dynamic prediction of traffic volume through Kalman filtering theory, Transportation Research, 18B(1):1–11, 1984.

    Google Scholar 

  28. S. Peeta, and A. Ziliaskopoulos, Foundations of dynamic traffic assignment: the past, the present and the future, Networks and Spatial Economics, 1–2(3,4):233–266, 2001.

    Article  Google Scholar 

  29. A. Puri, and P. Varaiya, Driving safely in smart cars, Proceedings of the American Control Conference, 5:3597–3599, 1995.

    Google Scholar 

  30. H. Tavana, Internally-Consistent Estimation of Dynamic Network Origin-Destination Flows from Intelligent Transportation Systems Data Using Bi-Level Optimization, Ph.D. Dissertation, The University of Texas at Austin, 2001.

    Google Scholar 

  31. H. Tavana and H.S. Mahmassani, Estimation of dynamic origin destination flows from sensor data using bi-level optimization method, Transportation Research Board CD-ROM Paper Preprints (TRB Paper No. 01-3241), National Research Council, Washington D.C., 2001.

    Google Scholar 

  32. P. Varaiya, Smart cars on smart roads: Problems of control, IEEE Transactions on Automatic Control, 38(2):195–207, 1993.

    Article  MathSciNet  Google Scholar 

  33. P. Varaiya, California’s performance measurement system: Improving freeway efficiency through transportation intelligence, TR News, 218:18–24, 2002.

    Google Scholar 

  34. M. West and B.J. Harrison, Bayesian Forecasting and Dynamic Models (2nd Edition), Springer-Verlag, 1997.

    Google Scholar 

  35. X. Zhou, X. Qin and H.S. Mahmassani, Dynamic origin-destination demand estimation using multi-day link traffic counts for planning applications, Transportation Research Record, 1831:30–38, 2003.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Civil and Environmental Engineering Maryland Transportation Initiative, University of Maryland, College Park, MD, 20742, USA

    Hani S. Mahmassani & Xuesong Zhou

Authors
  1. Hani S. Mahmassani
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  2. Xuesong Zhou
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Editor information

Editors and Affiliations

  1. Institute for Systems Research and Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742, USA

    E. H. Abed

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© 2005 Birkhäuser Boston

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Mahmassani, H.S., Zhou, X. (2005). Transportation System Intelligence: Performance Measurement and Real-Time Traffic Estimation and Prediction in a Day-to-Day Learning Framework. In: Abed, E.H. (eds) Advances in Control, Communication Networks, and Transportation Systems. Systems and Control: Foundations & Applications. Birkhäuser Boston. https://doi.org/10.1007/0-8176-4409-1_16

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