IDEAS home Printed from https://ideas.repec.org/a/eee/retrec/v8y2004i1p215-241.html
   My bibliography  Save this article

Estimation Of Economic Impact Of Vms Route Guidance Using Microsimulation

Author

Listed:
  • Ozbay, Kaan
  • Bartin, Bekir

Abstract

Intelligent Transportation Systems (ITS) aim at reducing travel times by making more efficient use of the existing transportation infrastructure through the use of state-of-the-art information technology solutions. It is, however, important to determine the impact of these technologies before any deployment decisions are made. In this paper, we propose a new evaluation methodology that incorporates a full marginal cost (FMC) approach with microscopic simulation as the basis for comparing the effectiveness of ITS technologies. The use of the FMC approach allows us to observe the impact of an ITS technology not only on travel times but also on other cost categories such as accident costs, infrastructure and environmental costs. Our proposed methodology employs microscopic simulation as a tool for accurately estimating the impact of VMS route guidance on congestion levels that are in turn used as the input to the FMC functions. The use of microscopic simulation in the context of FMC methodology allows us to capture the real impact of ITS technologies. In this paper, a detailed case study that evaluates the effectiveness of traveler information via Variable Message Signs in a highly congested network in South Jersey (SJ) is presented. The study network is modeled and calibrated using PARAMICS simulation software. The simulation routine is modified to model a realistic VMS routing algorithm and route choice behavior using the Advanced Programming Interface (API) option of PARAMICS. The effectiveness of several VMS location scenarios is determined in this simulation model based on Full Marginal Cost reductions obtained for trips along the main route between SJ and Philadelphia CBD. Microscopic simulation based FMC values are shown to be effective measures that can be used to make sound policy decisions. This is due to the fact that the FMC values can be analyzed in terms of their individual components to understand the impact of the reductions in travel times on externalities, such as congestion, air pollution, and noise.

Suggested Citation

  • Ozbay, Kaan & Bartin, Bekir, 2004. "Estimation Of Economic Impact Of Vms Route Guidance Using Microsimulation," Research in Transportation Economics, Elsevier, vol. 8(1), pages 215-241, January.
  • Handle: RePEc:eee:retrec:v:8:y:2004:i:1:p:215-241
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0739-8859(04)08011-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Terry L. Friesz & Javier Luque & Roger L. Tobin & Byung-Wook Wie, 1989. "Dynamic Network Traffic Assignment Considered as a Continuous Time Optimal Control Problem," Operations Research, INFORMS, vol. 37(6), pages 893-901, December.
    2. Abdulhai, Baher & Sheu, Jiuh-Biing & Recker, Will, 1999. "Simulation of ITS on the Irvine FOT Area Using "Paramics 1.5" Scalable Microscopic Traffic Simulator: Phase I: Model Calibration and Validation," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2ks86938, Institute of Transportation Studies, UC Berkeley.
    3. Levinson, David & Gillen, David & Kanafani, Adib & Mathieu, Jean-michel, 1996. "The Full Cost Of Intercity Transportation - A Comparison Of High Speed Rail, Air And Highway Transportation In California," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8mm50358, Institute of Transportation Studies, UC Berkeley.
    4. Papageorgiou, Markos, 1990. "Dynamic modeling, assignment, and route guidance in traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 24(6), pages 471-495, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhong, Shiquan & Zhou, Lizhen & Ma, Shoufeng & Jia, Ning, 2012. "Effects of different factors on drivers’ guidance compliance behaviors under road condition information shown on VMS," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1490-1505.
    2. Sterle, Claudio & Sforza, Antonio & Esposito Amideo, Annunziata, 2016. "Multi-period location of flow intercepting portable facilities of an intelligent transportation system," Socio-Economic Planning Sciences, Elsevier, vol. 53(C), pages 4-13.

    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. Sheu, Jiuh-Biing, 2006. "A composite traffic flow modeling approach for incident-responsive network traffic assignment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 461-478.
    2. Lam, William H. K. & Huang, Hai-Jun, 1995. "Dynamic user optimal traffic assignment model for many to one travel demand," Transportation Research Part B: Methodological, Elsevier, vol. 29(4), pages 243-259, August.
    3. Han, Sangjin, 2007. "A route-based solution algorithm for dynamic user equilibrium assignments," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1094-1113, December.
    4. Tong, C. O. & Wong, S. C., 2000. "A predictive dynamic traffic assignment model in congested capacity-constrained road networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(8), pages 625-644, November.
    5. Kachroo, Pushkin & Özbay, Kaan, 1998. "Solution to the user equilibrium dynamic traffic routing problem using feedback linearization," Transportation Research Part B: Methodological, Elsevier, vol. 32(5), pages 343-360, June.
    6. Lei Zhang & David Levinson, 2006. "Economics of Road Network Ownership," Working Papers 200908, University of Minnesota: Nexus Research Group.
    7. Moore, II, James E. & Kim, Geunyoung & Cho, Seongdil & Hu, Hsi-hwa & Xu, Rong, 1997. "Evaluating System ATMIS Technologies Via Rapid Estimation Of Network Flows: Final Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt5c70f3d9, Institute of Transportation Studies, UC Berkeley.
    8. Gentile, Guido & Meschini, Lorenzo & Papola, Natale, 2007. "Spillback congestion in dynamic traffic assignment: A macroscopic flow model with time-varying bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1114-1138, December.
    9. Duong Viet Thong & Aviv Gibali & Mathias Staudigl & Phan Tu Vuong, 2021. "Computing Dynamic User Equilibrium on Large-Scale Networks Without Knowing Global Parameters," Networks and Spatial Economics, Springer, vol. 21(3), pages 735-768, September.
    10. Zhao, Chunxue & Fu, Baibai & Wang, Tianming, 2014. "Braess paradox and robustness of traffic networks under stochastic user equilibrium," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 135-141.
    11. Bellei, Giuseppe & Gentile, Guido & Papola, Natale, 2005. "A within-day dynamic traffic assignment model for urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 39(1), pages 1-29, January.
    12. Jin, Wen-Long, 2010. "Continuous kinematic wave models of merging traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1084-1103, September.
    13. Chu, Lianyu & Liu, Henry X. & Recker, Will & Hague, Steve, 2003. "Evaluation of Potential ITS Strategies Under Non-Recurrent Congestion Using Microscopic Simulation," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt74f7f2x0, Institute of Transportation Studies, UC Berkeley.
    14. Han, Ke & Friesz, Terry L. & Yao, Tao, 2013. "A partial differential equation formulation of Vickrey’s bottleneck model, part II: Numerical analysis and computation," Transportation Research Part B: Methodological, Elsevier, vol. 49(C), pages 75-93.
    15. Zhu, Feng & Ukkusuri, Satish V., 2017. "Efficient and fair system states in dynamic transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 272-289.
    16. Y. W. Xu & J. H. Wu & M. Florian & P. Marcotte & D. L. Zhu, 1999. "Advances in the Continuous Dynamic Network Loading Problem," Transportation Science, INFORMS, vol. 33(4), pages 341-353, November.
    17. Lei Zhang & David Levinson, 2005. "Road Pricing with Autonomous Links," Working Papers 200506, University of Minnesota: Nexus Research Group.
    18. Jiancheng Long & Hai-Jun Huang & Ziyou Gao & W. Y. Szeto, 2013. "An Intersection-Movement-Based Dynamic User Optimal Route Choice Problem," Operations Research, INFORMS, vol. 61(5), pages 1134-1147, October.
    19. Jin, Wen-Long & Zhang, H. Michael, 2013. "An instantaneous kinematic wave theory of diverging traffic," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 1-16.
    20. Li, Xue-yan & Li, Xue-mei & Yang, Lingrun & Li, Jing, 2018. "Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 77-92.

    More about this item

    Statistics

    Access and download statistics

    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:eee:retrec:v:8:y:2004:i:1:p:215-241. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/620614/description#description .

    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.