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Effectiveness of Variable Message Signs Using Empirical Loop Detector Data

Author

Listed:
  • Hong Huo
  • David Levinson

    (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)

Abstract

The effectiveness of Variable Messages Signs (VMS) on route guidance is assessed by a discrete probit choice model that estimates the proportion of vehicles that diverts to an alternative routes given the characteristics of different messages. A before-and-after study is also conducted to quantitatively evaluate the network wide reduction of travel time and total delay of VMS systems. We find that VMS has no obvious effect on reduction of travel time, but can reduce the total delay.

Suggested Citation

  • Hong Huo & David Levinson, 2003. "Effectiveness of Variable Message Signs Using Empirical Loop Detector Data," Working Papers 000033, University of Minnesota: Nexus Research Group.
    • Handle: RePEc:nex:wpaper:vms
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/11299/179809
    File Function: First version, 2007
    Download Restriction: no
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    Citations

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

    1. Poulopoulou, Maria & Spyropoulou, Ioanna, 2019. "Active traffic management in urban areas: Is it effective for professional drivers? The case of variable message signs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 412-423.
    2. Findley, Daniel J. & Anderson, Tracy J. & Bert, Steven A. & Nye, Timothy & Letchworth, Will, 2018. "Evaluation of wait times and queue lengths at ferry terminals," Research in Transportation Economics, Elsevier, vol. 71(C), pages 27-33.
    3. Franco Basso & Pedro Maldonado & Raúl Pezoa & Nicolás Szoloch & Mauricio Varas, 2022. "The Impact of Flashing on the Efficacy of Variable Message Signs: A Vehicle-by-Vehicle Approach," Sustainability, MDPI, vol. 14(15), pages 1-14, August.
    4. Zhao, Wenjing & Ma, Zhuanglin & Yang, Kui & Huang, Helai & Monsuur, Fredrik & Lee, Jaeyoung, 2020. "Impacts of variable message signs on en-route route choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 335-349.
    5. Devon Farmer & Yeonjung Song & Panju Shin & Hyun Kim & Sanjay Tandan & Jun Lee, 2024. "School Bus Lighting Effectiveness and Improvements: Results from a Driving Experiment," Sustainability, MDPI, vol. 16(2), pages 1-19, January.
    6. Brownstone, David & McBride, Michael & Kong, Si-Yuan & Mahmassani, Amine, 2017. "Experimental Studies for Traffic Incident Management," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6kx670mv, Institute of Transportation Studies, UC Berkeley.
    7. Brownstone, David & McBride, Michael & Kong, Si-Yuan & Mahmassani, Amine, 2018. "Experimental Studies for Traffic Incident Management with Pricing, Private Information, and Diverse Subject," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8nj034g7, Institute of Transportation Studies, UC Berkeley.
    8. Siti Raudhatul Fadilah & Hiroaki Nishiuchi & An Minh Ngoc, 2022. "The Impact of Traffic Information Provision and Prevailing Policy on the Route Choice Behavior of Motorcycles Based on the Stated Preference Experiment: A Preliminary Study," Sustainability, MDPI, vol. 14(23), pages 1-21, November.

    More about this item

    Keywords

    Route Choice; Diversion Behavior; Cost Benefit Analysis;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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