IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4419-0820-9_23.html
   My bibliography  Save this book chapter

The Continuous Risk Profile Approach for the Identification of High Collision Concentration Locations on Congested Highways

In: Transportation and Traffic Theory 2009: Golden Jubilee

Author

Listed:
  • Koohong Chung

    (California Department of Transportation)

  • David R. Ragland

    (University of California)

Abstract

This paper documents a new method for monitoring traffic collision data from continuous roadway facilities to detect high collision concentration locations. Many existing methods for detecting collision concentration locations require segmentation of roadways and assume traffic collision data are spatially uncorrelated, resulting in both false positives (i.e., identifying sites for safety improvements that should not have been selected) and false negatives (i.e., not identifying sites that should have been selected). The proposed method does not require segmentation of roadways; spatial correlation in the collision data does not affect the results of analysis. This new method has a lower false positive rate than the conventional sliding moving window approach. This paper shows how the proposed method can proactively identify high collision concentration locations and capture the benefit of safety improvements observed in the project location and in neighboring sites.

Suggested Citation

  • Koohong Chung & David R. Ragland, 2009. "The Continuous Risk Profile Approach for the Identification of High Collision Concentration Locations on Congested Highways," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 463-480, Springer.
  • Handle: RePEc:spr:sprchp:978-1-4419-0820-9_23
    DOI: 10.1007/978-1-4419-0820-9_23
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Grembek, Offer & Kim, Kwangho & Kwon, Oh Hoon & Lee, Jinwoo & Liu, Haotian & Park, Min Ju & Washington, Simon & Ragland, David & Madanat, Samer M., 2012. "Experimental Evaluation of the Continuous Risk Profile (CRP) Approach to the Current Caltrans Methodology for High Collision Concentration Location Identification," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6sg5c0ng, Institute of Transportation Studies, UC Berkeley.
    2. Eui-Jin Kim & Oh Hoon Kwon & Shin Hyoung Park & Dong-Kyu Kim & Koohong Chung, 2021. "Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-21, May.
    3. Elyasi, Mohammad Reza & Saffarzade, Mahmoud & Boroujerdian, Amin Mirza, 2016. "A novel dynamic segmentation model for identification and prioritization of black spots based on the pattern of potential for safety improvement," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 346-357.
    4. Medury, Aditya & Grembek, Offer, 2014. "Dynamic Programming-based Pedestrian Hotspot Identification Approach," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt10d0x1z7, Institute of Transportation Studies, UC Berkeley.
    5. Chung, Koohong & Jang, Kitae & Madanat, Samer & Washington, Simon, 2011. "Proactive detection of high collision concentration locations on highways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 927-934, November.

    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:spr:sprchp:978-1-4419-0820-9_23. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.