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Estimation of time-varying origin-destination distributions with dynamic screenline flows

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  • Wu, Jifeng
  • Chang, Gang-Len

Abstract

A variety of methods for dynamic origin-destination (O-D) estimation is available in the transportation literature. Among those, the research direction pursued by Bell (1991)(Transpn Res. 25B, 115-125) and others in the same category offers the best promise for use in practice as it employs only link flow information from existing surveillance systems. Following the same direction, this paper presents an innovative method for estimating the dynamic network O-D matrices with time series of link and screenline flows. The proposed method takes full advantage of available link flow information, and considerably increases the observability of the dynamic interrelations between network O-D patterns and the resulting link flow distributions. Hence, one can estimate the dynamic O-D matrices with much fewer model parameters and less execution burden. With properly selected screenlines and efficient computing algorithms, the proposed model also offers the potential for real-time applications.

Suggested Citation

  • Wu, Jifeng & Chang, Gang-Len, 1996. "Estimation of time-varying origin-destination distributions with dynamic screenline flows," Transportation Research Part B: Methodological, Elsevier, vol. 30(4), pages 277-290, August.
    • Handle: RePEc:eee:transb:v:30:y:1996:i:4:p:277-290
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    References listed on IDEAS

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    1. Cascetta, Ennio & Nguyen, Sang, 1988. "A unified framework for estimating or updating origin/destination matrices from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 22(6), pages 437-455, December.
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    7. Bell, Michael G. H., 1991. "The real time estimation of origin-destination flows in the presence of platoon dispersion," Transportation Research Part B: Methodological, Elsevier, vol. 25(2-3), pages 115-125.
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    Cited by:

    1. Lin, Pei-Wei & Chang, Gang-Len, 2007. "A generalized model and solution algorithm for estimation of the dynamic freeway origin-destination matrix," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 554-572, June.
    2. Nie, Yu (Marco) & Zhang, H.M., 2008. "A variational inequality formulation for inferring dynamic origin-destination travel demands," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 635-662, August.
    3. Sun, Carlos & Porwal, Himanshu, 2000. "Dynamic Origin/Destination Estimation Using True Section Densities," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0f0711s6, Institute of Transportation Studies, UC Berkeley.
    4. A. de Palma & F. Marchal, 2000. "Dynamic traffic analysis with static data: some guidelines with an application to Paris," THEMA Working Papers 2000-55, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    5. Zhang, Michael & Nie, Yu & Shen, Wei & Lee, Ming S. & Jansuwan, Sarawut & Chootinan, Piya & Pravinvongvuth, Surachet & Chen, Anthony & Recker, Will W., 2008. "Development of A Path Flow Estimator for Inferring Steady-State and Time-Dependent Origin-Destination Trip Matrices," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3nr033sc, Institute of Transportation Studies, UC Berkeley.
    6. Wu, Jifeng, 1997. "A real-time origin-destination matrix updating algorithm for on-line applications," Transportation Research Part B: Methodological, Elsevier, vol. 31(5), pages 381-396, October.
    7. Hu, Shou-Ren & Peeta, Srinivas & Chu, Chun-Hsiao, 2009. "Identification of vehicle sensor locations for link-based network traffic applications," Transportation Research Part B: Methodological, Elsevier, vol. 43(8-9), pages 873-894, September.

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