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Observability in traffic networks. Plate scanning added by counting information

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  • Enrique Castillo
  • Ana Rivas
  • Pilar Jiménez
  • José Menéndez

Abstract

The paper deals with the observability problem in traffic networks, including route, origin–destination and link flows, based on number plate scanning and link flow observations. A revision of the main observability concepts and methods is done using a small network. Starting with the full observability of the network based only on number plate scanning on some links, the number of scanned links is reduced and replaced by counted link flows, but keeping the full observability of all flows in the network. In this way, the cost can be substantially reduced. To this end, several methods are given and discussed, and two small and one real case of networks are used to illustrate the proposed methodologies. Finally, some conclusions and final recommendations are included. Copyright Springer Science+Business Media, LLC. 2012

Suggested Citation

  • Enrique Castillo & Ana Rivas & Pilar Jiménez & José Menéndez, 2012. "Observability in traffic networks. Plate scanning added by counting information," Transportation, Springer, vol. 39(6), pages 1301-1333, November.
  • Handle: RePEc:kap:transp:v:39:y:2012:i:6:p:1301-1333
    DOI: 10.1007/s11116-012-9390-0
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    References listed on IDEAS

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    1. 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.
    2. Maher, Michael J. & Zhang, Xiaoyan & Vliet, Dirck Van, 2001. "A bi-level programming approach for trip matrix estimation and traffic control problems with stochastic user equilibrium link flows," Transportation Research Part B: Methodological, Elsevier, vol. 35(1), pages 23-40, January.
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    4. Maher, M. J., 1983. "Inferences on trip matrices from observations on link volumes: A Bayesian statistical approach," Transportation Research Part B: Methodological, Elsevier, vol. 17(6), pages 435-447, December.
    5. K. Ashok & M. E. Ben-Akiva, 2000. "Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin–Destination Flows," Transportation Science, INFORMS, vol. 34(1), pages 21-36, February.
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    Cited by:

    1. Fu, Chenyi & Zhu, Ning & Ling, Shuai & Ma, Shoufeng & Huang, Yongxi, 2016. "Heterogeneous sensor location model for path reconstruction," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 77-97.
    2. Alex A. Kurzhanskiy, 2022. "A Methodology for Estimating Vehicle Route Choice from Sparse Flow Measurements in a Traffic Network," Mathematics, MDPI, vol. 10(3), pages 1-11, February.
    3. Fu, Chenyi & Zhu, Ning & Ma, Shoufeng, 2017. "A stochastic program approach for path reconstruction oriented sensor location model," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 210-237.

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