IDEAS home Printed from https://ideas.repec.org/p/cdl/itsrrp/qt1qn7q6zf.html
   My bibliography  Save this paper

Cartesius and CTNET Integration and Field Operational Test

Author

Listed:
  • Rindt, Craig R.
  • McNally, Michael G.

Abstract

This report describes the results of PATH Task Order 5324—the first year of a multi-year project to integrate the Cartesius incident management system with Cal-trans CTNET traffic signal management system. The results of this research are a set of software requirements for reimplementing the Cartesius to interoperate with CTNET. An analysis of the existing Cartesius prototype explains how the need to focus the system on deployment and technical shortcomings of the existing system justifies a reimplementation of the software. From here, we describe the problem to be solved by the new software implementation, including general use cases, the expected users, the systems that Cartesius will interoperate with, and the constraints that will be placed on the system. The problem statement is followed by a detailed discussion of the functional requirements, database requirements, the user interface requirements, and other external interface requirements. The report concludes with a discussion the reimplementation work to be completed under PATHTask Order 6324. This reimplementation will serve the more general purpose of making Cartesius capable of working with existing traffic management subsystems to provide multi-jurisdictional incident mitigation, thus improving its deployability and subsequent value for Caltrans.

Suggested Citation

  • Rindt, Craig R. & McNally, Michael G., 2009. "Cartesius and CTNET Integration and Field Operational Test," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1qn7q6zf, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt1qn7q6zf
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/1qn7q6zf.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Chao, 2003. "Freeway Performance Measurement System (PeMS)," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6j93p90t, Institute of Transportation Studies, UC Berkeley.
    2. Logi, Filippo, 1999. "CARTESIUS: A Cooperative Approach to Real-Time Decision Support for Multi-Jurisdictional Traffic Congestion Management," University of California Transportation Center, Working Papers qt60p449bh, University of California Transportation Center.
    3. Rindt, Craig R. & McNally, Michael G., 2007. "Field Deployment and Operational Test of an Agent-based, Multi-Jurisdictional Traffic Management System," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0nd2p0k4, Institute of Transportation Studies, UC Berkeley.
    4. Nie, Yu & Zhang, H.M. & Recker, W.W., 2005. "Inferring origin-destination trip matrices with a decoupled GLS path flow estimator," Transportation Research Part B: Methodological, Elsevier, vol. 39(6), pages 497-518, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rindt, Craig R. & McNally, Michael G., 2007. "Field Deployment and Operational Test of an Agent-based, Multi-Jurisdictional Traffic Management System," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0nd2p0k4, Institute of Transportation Studies, UC Berkeley.
    2. Jinwon Kim & Jucheol Moon & Dongyun Yang, 2024. "Pigouvian Congestion Tolls and the Welfare Gain: Estimates for California Freeways," Working Papers 2402, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    3. Maryam Abareshi & Mehdi Zaferanieh & Mohammad Reza Safi, 2019. "Origin-Destination Matrix Estimation Problem in a Markov Chain Approach," Networks and Spatial Economics, Springer, vol. 19(4), pages 1069-1096, December.
    4. Sumalee, A. & Zhong, R.X. & Pan, T.L. & Szeto, W.Y., 2011. "Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 507-533, March.
    5. Ioannou, Petros & Giuliano, Genevieve & Dessouky, Maged & Chen, Pengfei & Dexter, Sue, 2020. "Freight Load Balancing and Efficiencies in Alternative Fuel Freight Modes," Institute of Transportation Studies, Working Paper Series qt3ns4b894, Institute of Transportation Studies, UC Davis.
    6. Xie, Chi & Kockelman, Kara M. & Waller, S. Travis, 2011. "A maximum entropy-least squares estimator for elastic origin–destination trip matrix estimation," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1465-1482.
    7. Yu Nie & H. Zhang, 2010. "A Relaxation Approach for Estimating Origin–Destination Trip Tables," Networks and Spatial Economics, Springer, vol. 10(1), pages 147-172, March.
    8. McNally, M. G. & Rindt, C. & Logi, F., 2002. "TRICEPS: An ATMIS Field Implementation for Control and Evaluation: Final Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt71h9100q, Institute of Transportation Studies, UC Berkeley.
    9. Lundgren, Jan T. & Peterson, Anders, 2008. "A heuristic for the bilevel origin-destination-matrix estimation problem," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 339-354, May.
    10. 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.
    11. Hongwen He & Jinquan Guo & Nana Zhou & Chao Sun & Jiankun Peng, 2017. "Freeway Driving Cycle Construction Based on Real-Time Traffic Information and Global Optimal Energy Management for Plug-In Hybrid Electric Vehicles," Energies, MDPI, vol. 10(11), pages 1-19, November.
    12. Hongwen, He & Jinquan, Guo & Jiankun, Peng & Huachun, Tan & Chao, Sun, 2018. "Real-time global driving cycle construction and the application to economy driving pro system in plug-in hybrid electric vehicles," Energy, Elsevier, vol. 152(C), pages 95-107.
    13. Yang, Yudi & Fan, Yueyue & Royset, Johannes O., 2019. "Estimating probability distributions of travel demand on a congested network," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 265-286.
    14. Louis Grange & Felipe González & Shlomo Bekhor, 2017. "Path Flow and Trip Matrix Estimation Using Link Flow Density," Networks and Spatial Economics, Springer, vol. 17(1), pages 173-195, March.
    15. Farnaz Khaghani & Farrokh Jazizadeh, 2020. "mD-Resilience: A Multi-Dimensional Approach for Resilience-Based Performance Assessment in Urban Transportation," Sustainability, MDPI, vol. 12(12), pages 1-23, June.
    16. Abdullah Alshehri & Mahmoud Owais & Jayadev Gyani & Mishal H. Aljarbou & Saleh Alsulamy, 2023. "Residual Neural Networks for Origin–Destination Trip Matrix Estimation from Traffic Sensor Information," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    17. Ballis, Haris & Dimitriou, Loukas, 2020. "Revealing personal activities schedules from synthesizing multi-period origin-destination matrices," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 224-258.
    18. Yang, Yudi & Fan, Yueyue, 2015. "Data dependent input control for origin–destination demand estimation using observability analysis," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 385-403.
    19. Sexton, Steven E., 2010. "Rationing Public Goods by Cooperation or Pecuniary Incentives: Evidence from the Spare-the-Air Program," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt5xs9r6t8, Department of Agricultural & Resource Economics, UC Berkeley.
    20. Owais, Mahmoud & Moussa, Ghada S. & Hussain, Khaled F., 2019. "Sensor location model for O/D estimation: Multi-criteria meta-heuristics approach," Operations Research Perspectives, Elsevier, vol. 6(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:itsrrp:qt1qn7q6zf. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucbus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.